Ophthalmological device

Abstract

An ophthalmological device according to a non-limiting embodiment of the present disclosure comprises a scanning unit, an image construction unit, an optical path length changing unit, and an intraocular distance calculation unit. The scanning unit generates a first interference signal by subjecting the fundus of a subject eye to a first optical coherence tomography scan. The image construction unit constructs a first optical coherence tomography image on the basis of the first interference signal generated by the scanning unit. The optical path length changing unit changes the optical path length of the scanning unit. The intraocular distance calculation unit calculates an intraocular distance on the basis of at least a first optical coherence tomography image constructed by the image construction unit and optical path length information indicating the optical path length when the fundus was subjected to the first optical coherence tomography scan by the scanning unit.

Description

ophthalmology equipment CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to U.S. Provisional Patent Application No. 63 / 557,720, entitled "OPHTHALMIC OPTICAL COHERENCE TOMOGRAPHY," filed February 26, 2024, the entire contents of which are incorporated herein by reference. The present disclosure relates to ophthalmic devices. Various imaging modalities are used in ophthalmology practice, including fundus cameras, scanning laser ophthalmoscopy (SLO), slit lamp microscopes, and optical coherence tomography (OCT). OCT can be used for both structural and functional imaging. OCT structural imaging is a technique for representing the spatial distribution of OCT signal intensity, which varies depending on the structure of a test object, as an image. Images generated by this technique are called OCT intensity images or simply intensity images. OCT intensity images are used to measure eye dimensions. A typical example of dimension measurement is the measurement of a defined distance within the eye (intracorporeal distance). There are various types of intraocular distances, such as axial length, corneal thickness, anterior chamber depth, lens thickness, and vitreous cavity depth. OCT functional imaging is a technique that visualizes changes in OCT signals according to the function of a test object. Applications in the field of ophthalmology include OCT angiography, which visualizes the vascular network at the fundus of the eye, and OCT blood flow measurement, which visualizes the blood flow dynamics within the blood vessels at the fundus of the eye. U.S. Pat. No. 1,101,3400 Donald C. Hood, Mary Durbin, Chris Lee, et al., “Toward a Real-world Optical Coherence Tomography Reference Database: Optometric Practices as a Source of Healthy Eyes”, Optom Vis Sci. 2023 Aug 1; 100(8): 499-506 One non-limiting object of the present disclosure is to provide a novel method for measuring intraocular distance using OCT. An ophthalmic apparatus according to a non-limiting embodiment of the present disclosure includes a scanning unit, an image constructing unit, an optical path length changing unit, and an intraocular distance calculating unit. The scanning unit applies a first optical coherence tomography scan to a fundus of a subject's eye to generate a first interference signal. The image constructing unit constructs a first optical coherence tomography image based on the first interference signal generated by the scanning unit. The optical path length changing unit changes the optical path length of the scanning unit. The intraocular distance calculating unit calculates the intraocular distance based at least on the first optical coherence tomography image constructed by the image constructing unit and optical path length information indicating the optical path length when the first optical coherence tomography scan is applied to the fundus by the scanning unit. According to exemplary embodiments of the present disclosure, a novel method for measuring intraocular distance using OCT can be provided. FIG. 1 is a schematic diagram for explaining fundus OCT scans and vitreous cavity depth; FIG. 2 is a flowchart showing an operation mode according to a non-limiting embodiment; FIG. 3 is a schematic diagram showing a configuration of an ophthalmic apparatus according to a non-limiting embodiment; FIG. 4 is a flowchart showing an operation mode according to a non-limiting embodiment; FIG. 5 is a flowchart showing an operation mode according to a non-limiting embodiment; FIG. 6 is a flowchart showing an operation mode according to a non-limiting embodiment; FIG. 7 is a schematic diagram showing an operation mode according to a non-limiting embodiment; FIG. 8 is a schematic diagram showing an operation mode according to a non-limiting embodiment; FIG. 9 is a schematic diagram showing an operation mode according to a non-limiting embodiment; FIG. 10 is a schematic diagram showing an operation mode according to a non-limiting embodiment; FIG. 11 is a schematic diagram showing an operation mode according to a non-limiting embodiment; FIG. 12 is a schematic diagram showing an operation mode according to a non-limiting embodiment; FIG. 1 is a schematic diagram showing the configuration of an ophthalmic apparatus according to a non-limiting embodiment; FIG. 2 is a flowchart showing an operation mode according to a non-limiting embodiment; FIG. 3 is a schematic diagram showing the configuration of an ophthalmic apparatus according to a non-limiting embodiment; FIG. 4 is a flowchart showing an operation mode according to a non-limiting embodiment; FIG. 5 is a schematic diagram showing the configuration of an ophthalmic apparatus according to a non-limiting embodiment; FIG. 6 is a flowchart showing an operation mode according to a non-limiting embodiment; FIG. 7 is a schematic diagram showing the configuration of an ophthalmic apparatus according to a non-limiting embodiment; FIG. 8 is a flowchart showing an operation mode according to a non-limiting embodiment;Fig. 1 is a schematic diagram showing the configuration of an ophthalmic apparatus according to a non-limiting embodiment; Fig. 2 is a flowchart showing an operation mode according to a non-limiting embodiment; Fig. 3 is a schematic diagram showing the configuration of an ophthalmic apparatus according to a non-limiting embodiment; Fig. 4 is a flowchart showing an operation mode according to a non-limiting embodiment; Fig. 5 is a schematic diagram showing the configuration of an ophthalmic apparatus according to a non-limiting embodiment; An exemplary embodiment according to the present disclosure will now be described. At least a portion of the functionality of some elements of embodiments according to the present disclosure may be implemented using circuitry or processing circuitry. The circuitry or processing circuitry may be a general purpose processor, a special purpose processor, an integrated circuit, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), an Application Specific Integrated Circuit (ASIC), a programmable logic device (e.g., a Simple Programmable Logic Device (SPLD), a Complex Programmable Logic Device (CPLD), a Field Programmable Gate Array (FPGA)), or a combination of these devices configured and / or programmed to perform at least some of the disclosed functions. The term "circuitry," "unit," "means," or the like may refer to hardware that performs at least some of the disclosed functions or that is configured and / or programmed to perform at least some of the disclosed functions. This hardware may be the hardware described in this disclosure or may include known hardware and / or hardware that is configured and / or programmed to perform at least some of the functions described in this disclosure. In the case of a processor, where the hardware can be considered as a certain type of circuitry, the term "circuitry," "unit," "means," or the like may refer to a combination of hardware and software. This software can be used to configure the hardware and / or the processor. The present disclosure provides several embodiments that can achieve improvements in ophthalmic examinations, and in particular, several embodiments that can achieve improvements in OCT-based ophthalmic examinations. Some embodiments provide novel methods for measuring intraocular distances using OCT. Other embodiments provide novel methods for determining the dimensions of an area to apply an OCT scan. Still other embodiments provide novel methods for controlling an OCT scan. Still other embodiments provide novel methods for generating an evaluation metric for an eye. Two or more embodiments according to the present disclosure may be at least partially combined, and the resulting embodiment may at least partially exhibit the functions and effects of the combined embodiments. Screening for ophthalmologic diseases is performed using various imaging modalities. Screening for some ophthalmologic diseases involves evaluating the state of fundus tissue (e.g., nerve fiber layer thickness, ganglion cell layer thickness, etc.) and assessing disease risk based on the evaluation results, using fundus photographs obtained with a fundus camera or SLO, intensity images obtained with OCT, and functional information. In clinical settings, such as screening, there is a demand for automating these processes. Currently, some screening facilities perform examinations using a standalone ophthalmologic device (sometimes called an OCT device) that has both a fundus photography function (e.g., a fundus camera function, an SLO function, etc.) and an OCT function. Such facilities include medical examination facilities and small-scale medical institutions. These facilities desire automated evaluation using a standalone OCT device. On the other hand, in fundus measurements using OCT, the imaging range (OCT scan area) varies depending on individual differences in ocular parameters. For example, in optic disc measurements and retinal thickness measurements, the dimensions of the fundus area to which the OCT scan is applied (scan size) vary depending on the axial length and ocular refractive power of the subject's eye. Therefore, if the ocular parameters of the subject's eye are not taken into consideration, the quality of the fundus measurement (e.g., sensitivity, specificity, accuracy, precision, reproducibility, etc.) will decrease. This problem may become more pronounced in comparative evaluations using standard values ​​(reference databases). In some embodiments, the reference database may be a normal eye database and / or a diseased eye database (e.g., a database of highly myopic eyes), or may be the real-world database described in "Toward a Real-world Optical Coherence Tomography Reference Database: Optometric Practices as a Source of Healthy Eyes" (Non-Patent Document 1). A normal eye database is a database created from a data set collected by examining normal eyes (healthy eyes) that meet certain conditions under favorable conditions. For example, a normal eye database is a database created based on data collected from a large number of sample eyes whose measurement index values ​​are within the normal range. A diseased eye database is a database created based on data collected from a large number of sample eyes with a specific disease. A real-world database is a database created based on "real-world data" collected without restricting attributes. Real-world data is data obtained from various sources related to outcomes of heterogeneous populations in real-world environments. Real-world data is not collected according to a specific research protocol, but rather data generated, for example, from daily clinical practice or personal health management. Real-world data is understood to be a different type of data from data obtained from randomized controlled trials. Real-world data is a dataset collected from various sample eyes that reflect reality and everyday life. Compared to normal eye datasets, real-world data are characterized by a large sample size, a wide range of values, and a large variation in the attributes of the sample eyes (e.g., age). Non-limiting examples of real-world data include electronic medical record data, medical imaging data, image interpretation data, medical fee statements, health insurance claim data, and patient surveys. In conventional screening settings, it has been common to measure the ocular parameters of the subject's eye separately from the OCT scan to correct the OCT imaging range. U.S. Pat. No. 1,013,400 (Patent Document 1) discloses an invention in which the axial length is estimated based on a reference optical path length, a measurement optical path length, and a working distance, and the imaging range is determined based on the estimated axial length. In addition, some conventional techniques define multiple ranges for the axial length, which is the ocular parameter that most affects the imaging range, prepare reference databases corresponding to each range, select a reference database according to the axial length of the subject's eye, and evaluate the subject's eye using the selected reference database. Some embodiments of the present disclosure propose a novel method for estimating the intraocular distance of a subject's eye based on parameters of an ophthalmic device set for OCT scanning. The obtained intraocular distance estimate may be used in any manner. The intraocular distance may be any type of distance parameter that affects the OCT scan area. The intraocular distance according to some aspects may include the axial length of the eye. The intraocular distance according to some embodiments may include a distance parameter obtained by subtracting a factor corresponding to at least a portion of the anterior segment from the axial length. An example of this distance parameter is the vitreous chamber depth (VCD = AEL - (CCT + ACD)), which is obtained by subtracting the central corneal thickness (CCT) and the anterior chamber depth (ACD) from the axial length (AEL). FIG. 1 shows an embodiment of fundus OCT scanning. In many cases, OCT scanning of a fundus imaging area SA is performed by deflecting measurement light using a pivot SP located within or near the pupil. The vitreous chamber depth VCD is an intraocular distance that approximates the distance from the pivot SP to the fundus, and therefore can be considered one of the intraocular distances that affect the imaging area SA. Furthermore, the intraocular distance according to some embodiments may include intraocular distances such as pupil thickness (the dimension of the pupil in the depth direction), anterior chamber depth, and crystalline lens thickness. According to some embodiments, the quality (sensitivity, specificity, etc.) of ophthalmic disease screening can be improved without using an ocular parameter measuring device such as an axial length measuring device separately from the OCT device. According to some embodiments, when scanning an eye to be examined with an OCT device, the scan size can be automatically adjusted using data from the OCT device (e.g., scan parameters). According to some embodiments, by preparing reference data for each value of axial length, it is possible to evaluate the subject's eye without using multiple reference databases corresponding to multiple axial length ranges. In a non-limiting aspect, a regression curve for each value of axial length is prepared and used to calculate a predetermined statistical quantity (e.g., 1st percentile value, 5th percentile value, etc.). It is also possible to prepare multiple reference databases corresponding to multiple axial length ranges, respectively, and selectively use them. The present disclosure particularly describes in detail some non-limiting embodiments related to ophthalmic devices and some non-limiting embodiments related to ophthalmic information processing devices. However, it will be understood by those skilled in the art that the present disclosure also provides embodiments in categories other than these devices. For example, the present disclosure explicitly and / or implicitly provides embodiments of a control method for an ophthalmic device, an control method for an ophthalmic information processing device, an ophthalmic system, an OCT method, an information processing method, a medical method (e.g., an axial length estimation method, a subject's eye evaluation method, an ophthalmic disease screening method, etc.), a program that causes a computer to execute each step of any of the methods, and a recording medium (a computer-readable non-transitory recording medium) on which any of the programs is recorded. The present disclosure also provides embodiments that at least partially combine embodiments of two or more categories freely selected from these various categories. Furthermore, the present disclosure provides embodiments that at least partially combine embodiments of two or more categories related to one category. Subject matter according to several non-limiting embodiments of the present disclosure will now be described. One non-limiting embodiment estimates the axial length of the test eye based on the reference mirror position (i.e., the reference arm length of the OCT optical system) when an OCT scan is applied to the test eye and the average depth position of the retinal image in the OCT image (e.g., a B-scan image) obtained by the OCT scan. In some aspects of this embodiment, information on an element that changes the measurement arm length and / or information on an element that changes the reference arm length may be used instead of the reference mirror position. Furthermore, the "average depth position of the retinal image" may be determined in any manner, such as the average depth position of the entire retinal image or the average depth position of a specific retinal sub-tissue. The retinal sub-tissue may be any tissue, such as the retinal surface (internal limiting membrane (ILM)) or a tissue of particular interest (e.g., nerve fiber layer (NFL), retinal pigment epithelium layer (RPE)). Some aspects of this embodiment are premised on, for example, the following conditions: (1) the working distance is within a predetermined tolerance; and (2) the dimensions of a predetermined intraocular site (e.g., anterior chamber depth, vitreous cavity depth, etc.) can be estimated or assumed. Condition (1) corresponds to a favorable alignment state in the depth direction (z direction). The estimated or assumed value applied in condition (2) may be, for example, any of standard data, measured data, and estimated data derived from another parameter. Some aspects of the present embodiment use an estimate of the axial length of the subject's eye to determine the area (e.g., the size of the area) of an OCT scan to apply to the fundus of the subject's eye, and further evaluate the subject's eye based on data obtained from the OCT scan. In some aspects of the present embodiment, data (wide-area OCT data) collected by applying an OCT scan to a wide area of ​​the fundus of the subject's eye is acquired in advance. In this aspect, a range of partial data of the wide-area OCT data is determined using an estimated value of the axial length of the subject's eye, the determined partial data is extracted from the wide-area OCT data, and the subject's eye is evaluated based on the extracted partial data. In other words, in this aspect, the evaluation range can be changed using the estimated value of the axial length of the subject's eye. In some aspects of this embodiment, multiple reference databases are prepared, each corresponding to a different range of axial lengths. Furthermore, in this aspect, a reference database corresponding to a range to which the estimated axial length of the subject's eye belongs is selected from the multiple reference databases, and the subject's eye is evaluated using the selected reference database. The estimated axial length of the subject's eye in this aspect may be the estimated value obtained by the above process, another estimated value, or a measured value. In some embodiments, multiple reference databases may be prepared corresponding to multiple combinations of the axial length and another parameter, such as the presence or absence of myopia, the degree of myopia, and the magnitude of ocular refractive power. In some aspects of the present embodiment, a regression equation is derived that defines a range of different axial lengths by applying statistical processing (e.g., regression analysis) to the data set used to create a given reference database (original reference database). This regression equation may be, for example, a regression curve or a regression line. In some embodiments, the original reference database can be processed using the obtained regression equation to create multiple reference databases corresponding to multiple different axial length ranges. In other words, the domain of a given reference database can be expanded using a regression equation derived from the reference database. The domain of the reference database in this embodiment may be, for example, a domain in which axial length is an independent variable. In some embodiments, the expanded reference database obtained in this manner can be used to evaluate the subject's eye. Some aspects of this embodiment can use the information obtained by the above process to determine the area of ​​an OCT scan to be applied to the fundus of the test eye. For example, some aspects can determine the OCT scan area based on multiple reference databases corresponding to multiple different axial length ranges. Some aspects can also determine the OCT scan area based on a regression equation calculated based on the original reference database. Some aspects can also determine the OCT scan area based on an extended reference database generated using this regression equation. Some aspects of the present embodiment can estimate the axial length of the subject's eye while performing an alignment operation of the optical system with respect to the subject's eye (i.e., can predict the approximate axial length of the subject's eye). This aspect can calculate the application area (its dimensions) of the OCT scan in real time based on the estimated axial length, and actually perform an OCT scan of the fundus of the subject's eye. Some aspects may perform similar processing while performing an adjustment operation of the OCT optical path length (the optical path length of the measurement arm and / or the optical path length of the reference arm). An overview of some embodiments of the present disclosure will now be provided. Some embodiments relate to devices, systems, methods, programs, and recording media that can be used for fundus examinations using OCT (e.g., calculation of optic disc parameters, calculation of retinal parameters, etc.), and can correct the shooting range (OCT scan area) according to ocular parameters. Some embodiments provide a program that receives as input setting conditions (e.g., parameters such as a scan range and a scan speed) of an ophthalmic apparatus when generating an OCT image, processes the input, and implements an algorithm for estimating the axial length of the subject's eye based on the generated OCT image and the setting condition parameters. Estimating the axial length requires measuring the dimensions of specific anatomical structures (e.g., pupil, lens) in the OCT image. This embodiment may be configured to automatically detect the dimensions of the pupil and lens from the OCT image and calculate an estimated value of the axial length based on the detected dimensions. Alternatively, this embodiment may be configured to obtain preset values ​​for the dimensions of the pupil and lens in advance and calculate an estimated value of the axial length using these preset values. Next, in this embodiment, a formulation for correcting the OCT scan area is performed using the estimated axial length, which makes it possible to ensure a consistent imaging range without being affected by individual differences in axial length. Furthermore, in this embodiment, by preparing and referencing regression curves corresponding to various values ​​of axial length, it is possible to calculate desired statistics (e.g., 1st percentile value, 5th percentile value, etc.) based on the regression curve without preparing and using multiple reference databases (e.g., multiple normal eye databases). A non-limiting example of this will be described. In this example, normal eye data is first collected in advance for each axial length, and a regression curve is derived using this normal eye data. Furthermore, in this example, the axial length is estimated from the acquired OCT image, and the regression curve corresponding to this estimated axial length is used to calculate the normal range of a predetermined parameter of the subject's eye (e.g., optic disc parameter, retinal parameter, etc.). By using the device, system, method, program, and recording medium according to the present embodiment, it is possible to correct the imaging range according to the axial length, and further to improve the quality (e.g., sensitivity, specificity, etc.) of comparative evaluation using a reference database. In addition, since the axial length can be estimated using the OCT device without using other devices such as an axial length measurement device, there is an advantage that it can be easily used for screening, etc. Another advantage is that it is possible to automatically adjust the scan size when performing OCT imaging. Some non-limiting aspects of the operation of some embodiments will now be described. As mentioned above, in ophthalmic disease screening using fundus photographs and OCT images, there is a demand for automating the process of evaluating the state of fundus tissue (e.g., nerve fiber layer thickness, ganglion cell layer thickness, etc.) and the process of evaluating disease risk based on the evaluation results. Fig. 2 shows an example of an operation mode having one non-limiting purpose of satisfying this demand. The operation mode of Fig. 2 shows an example of an examination (e.g., screening) procedure realized using this embodiment. The examination procedure of this example includes a preparation step (S1), an imaging step (S2), an analysis step (S3), and an evaluation step (S4). The preparation step of step S1 prepares evaluation criteria (e.g., a reference database, evaluation thresholds, etc.). The photographing step of step S2 generates an image (image data) of the fundus of the subject's eye by photographing the fundus of the subject's eye using a fundus photography modality such as a fundus camera, SLO, or OCT. The analysis step of step S3 analyzes the image obtained in the photographing step to generate evaluation data. The evaluation step of step S4 obtains an evaluation result of the subject's eye by comparing the evaluation data generated in the analysis step with the evaluation criteria provided in the preparation step. Some non-limiting examples of the operational aspects outlined in Figure 2 are described below. Two or more exemplary operational aspects may be at least partially combined. Any of the features described in U.S. Provisional Patent Application No. 63 / 557,720, which is incorporated by reference into this disclosure, may be at least partially combined with each exemplary operational aspect. Any of the features described in this disclosure may be at least partially combined with each exemplary operational aspect. Any of the features described in any patent application filed by the applicant may be at least partially combined with each exemplary operational aspect. Any of the features written by the applicant or its affiliates, including but not limited to patent applications, may be at least partially combined with each exemplary operational aspect. FIG. 3 shows a non-limiting configuration of an ophthalmic apparatus (OCT apparatus) that can be used in the operational mode of FIG. 2 . FIG. 3 is a schematic diagram showing only some elements of an actual ophthalmic apparatus. The ophthalmic apparatus 300 of this example includes an OCT scanner (scanning unit) 310 and a processor 320. The OCT scanner 310 applies an OCT scan to the fundus of the subject's eye E. Note that the subject's eye E is not a component of the OCT scanner 310. The processor 320 performs various processes according to a program, such as control, calculation, image processing, analysis, and evaluation. The processor 320 may also include a machine learning engine that performs processing using a model created using machine learning. The OCT scanner 310 splits light output from a light source 311 into reference light and measurement light by a fiber coupler 312. The reference light is guided by a reference arm through a lens group 313 to a reference mirror 314. The reference light reflected by the reference mirror 314 is guided by the lens group 313 to the fiber coupler 312. The measurement light is guided by the measurement arm through a lens 315 and an optical scanner 316 to the subject's eye E. Return light of the measurement light from the subject's eye E is guided to the fiber coupler 312 through the optical scanner 316 and the lens 315. The fiber coupler 312 superimposes the return light of the measurement light from the subject's eye E on the return light of the reference light from the reference mirror 314 to generate interference light. The photodetector 317 detects this interference light and generates an electrical signal (interference signal). The photodetector 317 includes a spectrometer when spectral domain OCT is employed, and a balanced photodiode when swept source OCT is employed. The processor 320 controls the OCT scanner 310, constructs an image based on the interference signal from the photodetector 317, and performs image processing, image analysis, evaluation processing, and the like. The first operational example will be described. The main features of the first operational example are an imaging step and an analysis step. In the imaging step of the first operational example, an OCT scanner 310 applies an OCT scan to the fundus of the subject's eye E, and the processor 320 processes data collected by the OCT scan to generate an image. Prior to the OCT scan in the first operating mode example, the ophthalmic apparatus 300 performs alignment (auto-alignment or manual alignment) to adjust the optical path length of the OCT scanner 310 (i.e., the reference Z coordinate (coherence gate position) in interferometry). In the first operating mode example, the reference mirror 314 can be moved by a mechanism (reference mirror moving mechanism) not shown. The reference mirror moving mechanism operates under the control of the processor 320. That is, the processor 320 can adjust the position of the reference mirror 314 by controlling the reference mirror moving mechanism. The OCT scan pattern may be any pattern, and may be, for example, a B-scan or a raster scan. In some non-limiting examples, the position of the reference mirror 314 (coherence gate position) is set to the shallowest position in the image frame (the position closest to the OCT scanner 310) or a position slightly offset in the depth direction from this shallowest position. However, the coherence gate position is not limited to this example and may be set to any depth position. The analysis step is performed by the processor 320. The processor 320 applies segmentation to the OCT image generated in the imaging step to identify the retinal image, and calculates the average depth position (average Z coordinate) of the retinal image (e.g., the retinal surface). Next, the processor 320 estimates the axial length of the subject's eye E based on the position (reference Z position) of the reference mirror 314 when the OCT scan is applied to the fundus of the subject's eye 3 in the imaging process and the average depth position of the retinal image in the OCT image. This calculation is performed using, for example, the following Equations 1 and 2. [Formula 1] Estimated AEL (AU) = Ref mirror position + Z-mean [Formula 2] Estimated AEL (um) = (Ref mirror position + Z-mean / α) * β Here, "Ref mirror position" indicates the position (reference Z position) of the reference mirror 314 when applying an OCT scan, and "Z-mean" indicates the average depth position of the retinal image in the OCT image. Equation 1 indicates the estimated axial length (Estimated AEL) expressed in arbitrary units (AU) corresponding to the ophthalmic apparatus 300 according to the first example operation mode, and Equation 2 indicates the estimated axial length expressed in real-space length units (micrometers (um)). In actual operation, a program based on the algorithm of Equation 2 is implemented to perform an axial length estimation calculation. The value α in Equation 2 is introduced to convert the optical distance in an eye having a specific refractive index (refractive index distribution) into the distance in air. The value α may be the standard refractive index of the human eye. For example, the value α may be the average refractive index of the entire eye, or the average refractive index of ocular tissues (e.g., cornea, aqueous humor, lens, vitreous humor, retina, etc.). As an example, in tests conducted by the inventors, the value α was set to 1.38. Furthermore, β in Equation 2 is a value specific to the OCT device used. The value β may be a constant value or a variable value. As an example, in a test performed by the inventor, the value β was set to a constant value of 4.954. According to the first example of the operating mode described above, an estimate of the axial length of the subject's eye E can be automatically calculated based on the position of the reference mirror 314 when an OCT scan is applied to the fundus of the subject's eye E and the OCT image obtained by this OCT scan. Therefore, examinations such as screening can be performed without preparing a separate device for measuring the axial length of the subject's eye E. Furthermore, examinations can be performed without adding new hardware to existing OCT scanners. Moreover, as can be seen from Equations 1 and 2, the axial length can be estimated by a simple and easy calculation. A second example of the operation will now be described. In the second example of the operation, the processor 320 can use the estimated axial length of the subject's eye E obtained in the first example of the operation to determine the range of an OCT scan to be applied to the fundus of the subject's eye E for an examination such as screening. For example, the processor 320 can be configured to determine an OCT scan area having dimensions corresponding to the dimensions of the reference database used in the evaluation step (S4). The main feature of the second operation example is the photographing process. The photographing process of the second operation example includes a series of sub-processes described below. Figure 4 shows a series of sub-processes in the photographing process of the second operation example. In the first sub-step of step S11, the OCT scanner 310, under the control of the processor 320, applies a first OCT scan to the subject's eye E to collect first data. In a second sub-step of step S12, the processor 320 calculates an estimated value of the axial length of the subject's eye E based on the first data collected in the first sub-step. The processing in this sub-step may be performed using any algorithm. In some non-limiting examples, a high-speed algorithm may be employed to speed up the imaging step, thereby speeding up the examination. In some non-limiting examples, the same algorithm as in the analysis step may be employed. In a third substep of step S13, the processor 320 determines an OCT scan area based on the estimated value of the fundus of the subject's eye E obtained in the second substep. The processing in this substep may be performed using any method. As some non-limiting examples, the method described in U.S. Pat. No. 1,013,400 (Patent Document 1) may be adopted. In the fourth sub-step of step S14, the OCT scanner 310 applies a second OCT scan to the test eye E to collect second data under the control of the processor 320 according to the OCT scan area determined in the third sub-step. In a fifth sub-step of step S15, the processor 320 generates an image of the fundus of the subject's eye E based on the second data collected in the fourth sub-step. The generated image is provided to the analysis step of step S3 in FIG. 2 . According to the second example of the operating mode described above, it is possible to automatically set the OCT scan area, which is greatly influenced by the axial length, without preparing a separate device for measuring the axial length of the subject's eye E. In addition, in a second example operation mode, a combined operation (paired operation) of OCT scanning and axial length estimation is performed at least twice. The first paired operation is a preparatory operation performed in steps S11 and S12 in the imaging process to determine an OCT scan area for the second paired operation. The second paired operation is an analysis process performed in steps S14 and S15 and step S3 in the imaging process, and is performed using the results of the first paired operation. Such stepwise, repetitive operations are advantageous in terms of improving the quality of evaluation and reducing the possibility of re-examination. The subject's eye E may have a long axis and may experience aliasing artifacts in the OCT image. The aliasing artifact, also known as a complex conjugate artifact (ghost image, mirror image), is a virtual image that appears on the opposite side of the real image from the zero-delay position (coherence gate position) where the optical path length of the measurement light irradiated onto the object to be measured is equal to the optical path length of the reference light. The aliasing artifact limits the observable depth range. Eliminating the aliasing artifact enables observation of deep areas of the object to be measured and wide-angle observation. For more information on aliasing artifacts, please refer to U.S. Patent Application Publication No. 2021 / 0038071. In some non-limiting examples, the processor 320 determines whether aliasing artifacts occur in the OCT image based on the first data obtained in the first substep. If aliasing artifacts do not occur, the processor 320 proceeds to the second substep. If aliasing artifacts occur, the processor 320 adjusts the optical path length of the reference arm of the OCT scanner 310 (the position of the reference mirror 314) to suppress the aliasing artifacts, and controls the OCT scanner 310 to execute the first substep again. This makes it possible to perform an inspection using a good-quality OCT image without aliasing artifacts. In some non-limiting examples, the processor 320 determines that aliasing artifacts have occurred if the estimated axial length of the subject's eye E obtained in the second substep is greater than a predetermined threshold. In this case, the processor 320 adjusts the position of the reference mirror 314 to suppress the aliasing artifacts, and controls the OCT scanner 310 to execute the first substep again. This example also makes it possible to perform an examination using a good-quality OCT image free of aliasing artifacts. A third example of the operation mode will be described. In the second example of the operation mode described above, axial length estimation is performed in preparation for an OCT scan to collect data for examination. In contrast, the third example of the operation mode is based on the premise that OCT data (wide-area OCT data, wide-area OCT image) including data corresponding to the area of ​​the fundus required for examination has already been acquired from the fundus of the subject's eye. One non-limiting purpose of the third exemplary operation mode is to satisfy the demand for automation in ophthalmic disease screening described above. The ophthalmic apparatus that executes the third exemplary operation mode may be an ophthalmic imaging apparatus with an imaging function, such as the ophthalmic apparatus 300 in FIG. 3, or an ophthalmic information processing apparatus without an imaging function. 5 shows a non-limiting example of an examination procedure according to the third example operation mode, in which the ophthalmologic apparatus 300 executes the examination procedure. In the preparation process of step S21, the ophthalmic apparatus 300 or another apparatus prepares evaluation criteria, similar to step S1 in Fig. 2. The prepared evaluation criteria are stored in, for example, a storage device (not shown) of the processor 320. In the image acquisition process of step S22, the processor 320 acquires a wide-field OCT image of the fundus generated in a previous examination of the subject's eye E. The wide-field OCT image is acquired, for example, from any one of an ophthalmic apparatus (OCT apparatus), an image archiving system, a storage device, and a recording medium used in the previous examination. If the wide-field OCT image has been generated by the ophthalmic apparatus 300 and stored in the ophthalmic apparatus 300, the processor 320 reads it from the storage device in which it is stored. In the axial length estimation step of step S23, the processor 320 analyzes the wide-area OCT image acquired in step S22 to obtain an estimated value of the axial length of the subject's eye E. The processing of this step may be performed using any algorithm. In some non-limiting examples, by employing a high-speed algorithm, the processing of the imaging step can be speeded up, and thus the examination can be expedited. In some non-limiting examples, the same algorithm as in the analysis step can be employed. In the partial image extraction step of step S24, the processor 320 extracts a partial image for evaluation from the wide-area OCT image acquired in step S22 based on the estimated axial length of the subject's eye E obtained in step S23. The dimensions of the extracted partial image are determined based on the dimensions of the evaluation criteria (e.g., a reference database) prepared in step S21. Typically, the dimensions of the partial image are equal to or larger than the dimensions of the reference database. Furthermore, the position of the extracted partial image (position in the wide-area OCT image) is determined by, for example, referring to the positions of fundus landmarks. Non-limiting examples of fundus landmarks include the optic disc, macula, and blood vessels. This process may include a process similar to step S13 (third sub-step) of FIG. 4 (e.g., the process described in U.S. Pat. No. 1,013,400 (Patent Document 1)). In the analysis step of step S25, the processor 320 analyzes the partial image extracted from the wide-area OCT image in step S24 to generate evaluation data. The processing of this step may include processing similar to that of step S3 (analysis step) in FIG. 2. In the evaluation step of step S26, the processor 320 compares the evaluation data generated in step S25 with the evaluation criteria provided in step S21 to obtain an evaluation result of the subject's eye E. The processing of this step may include processing similar to that of step S4 (evaluation step) in FIG. According to the third example of the operation mode described above, it is possible to promote automation of the process of evaluating the state of the fundus tissue and the process of evaluating the disease risk based on the evaluation results in an examination (such as screening) that uses a wide-area OCT image of the subject's eye that was previously acquired. A fourth example of the operation mode will now be described. The main features of the fourth example of the operation mode are a preparation step of preparing a reference database and an evaluation step performed based on this reference database. Figure 6 shows a series of sub-steps in the preparation step of the fourth example of the operation mode. The fourth example of the operation mode can be performed using any device or any system. The first sub-step of step S31 is to collect a sample data set by measuring the axial length and predetermined fundus parameters for a large number of sample eyes. The axial length measurement in the first substep may be performed using any axial length measurement method and any axial length measurement device. The fundus parameter measurement in the first sub-step measures fundus parameters of the type used in the evaluation of the subject's eye in the evaluation step. The type of fundus parameter, the measurement method for the fundus parameter, and the fundus parameter measurement device may all be determined arbitrarily. A non-limiting example of the fundus parameter is the thickness distribution of a specific tissue in the retina, measured using a fundus OCT scan. The sample data set collected in the first substep may include any type of data. For example, the sample data set may include real-world data, normal eye data, or diseased eye data. The sample data set may also include data extracted from an existing database (e.g., a real-world database, a normal eye database, a diseased eye database, etc.). The sample data set may also include data collected from a newly performed measurement in the fourth example operating mode. Because real-world data is acquired without detailed checks on subjects, it may contain a wide variety of data, such as measurement data on normal eyes, measurement data on diseased eyes, and outliers. Furthermore, it is presumed that the majority of subjects involved in the real-world data are healthy. Therefore, it can be assumed that the small amount of data, such as data on diseased eyes and outliers, is covered by the data on a large number of healthy subjects. Therefore, it can be considered that the real-world database and the normal eye database essentially have similar trends. In some non-limiting examples, the collection of the sample data set is performed using a network including multiple ophthalmic devices and one or more servers. Each ophthalmic device sends an identifier and measurement data of the sample eye to the server. Optionally, each ophthalmic device may send attribute information of the sample (e.g., age, sex, race, name of the present disease, etc.) along with the identifier and measurement data of the sample eye to the server. The server accumulates the information transmitted from the multiple ophthalmic devices. In this way, the sample data set is collected. The following steps S32 to S34 may be executed by the server and / or by another information processing device. The second sub-step of step S32 is to set a plurality of different axial length ranges, each of which may be set arbitrarily. A non-limiting example of the second sub-step is to set a normal axial length range corresponding to a defined range of normal axial lengths, a long axial length range corresponding to a defined range of long axial lengths that are longer than the normal axial length, and a short axial length range corresponding to a defined range of short axial lengths that are shorter than the normal axial length. In some non-limiting examples, the long axial length range may be divided into two or more sub-ranges, and the short axial length range may be divided into two or more sub-ranges. In some non-limiting examples, the axial length ranges may be set according to the attributes of the subject and / or the attributes of the eye to be examined. In some non-limiting examples, the plurality of axial length ranges may be determined by applying a statistical process to a predetermined dataset (e.g., a dataset including at least a portion of the sample dataset acquired in the first substep). In some non-limiting examples, the plurality of axial length ranges may be determined by applying a machine learning engine to the predetermined dataset. The third sub-step of step S33 divides the sample data set acquired in the first sub-step based on the multiple axial length ranges determined in the second sub-step, thereby creating multiple sub-data sets corresponding to the multiple axial length ranges, respectively. The sample data acquired from each sample eye in the first sub-step includes axial length data (axial length value) and fundus parameter data. A non-limiting example of the third sub-step is determining to which of the multiple axial length ranges established in the second sub-step the axial length value of each sample eye belongs. This identifies a group of sample eyes belonging to each of the multiple axial length ranges. That is, each sample eye is assigned to a corresponding axial length range based on the axial length data included in the sample data set. As a result, multiple sub-data sets corresponding to the multiple axial length ranges are created from the sample data acquired in the first sub-step. In the fourth sub-step of step S34, a reference database is created based on each of the sub-data sets obtained in step S33. This creates multiple reference databases corresponding to multiple axial length ranges. The process of creating the reference database from the sub-data sets may be performed using any method. The created multiple reference databases are stored in the memory device of each ophthalmic device (e.g., ophthalmic imaging device, ophthalmic information processing device, system, etc.) that performs the evaluation of the subject's eye, and / or are stored in a memory device accessible by each ophthalmic device. With the above preparations, the ophthalmic apparatus 300 can execute the non-limiting operations shown in Fig. 7. In the photographing process of step S41, the ophthalmic apparatus 300 applies OCT scanning to the fundus of the subject's eye E to generate an image. In the axial length data acquisition process of step S42, the ophthalmic apparatus 300 acquires axial length data (axial length value) of the subject's eye E. In some non-limiting examples, the ophthalmic apparatus 300 acquires axial length data by applying axial length measurement to the subject's eye E. In some non-limiting examples, the processor 320 externally receives separately measured axial length data of the subject's eye E. Steps S41 and S42 may be executed in reverse order. Alternatively, steps S41 and S42 may be executed at least partially in parallel. In the analysis step of step S43, the processor 320 analyzes the image of the fundus of the subject's eye E generated in step S41 to generate evaluation data. In the reference database (RDB) selection step of step S44, the processor 320 identifies the axial length range to which the axial length value of the subject's eye E belongs from among the multiple axial length ranges set in the second sub-step of step S32, based on the axial length data of the subject's eye E acquired in step S42. The processor 320 selects a reference database corresponding to the axial length range to which the axial length value of the subject's eye E belongs from among the multiple reference databases created in step S34. In the evaluation step of step S45, the processor 320 evaluates the eye E by comparing the evaluation data of the fundus of the eye E obtained in the analysis step of step S43 with the reference database selected in step S44. According to the fourth example of the operation mode described above, it is possible to evaluate the subject's eye using a reference database according to the axial length of the subject's eye, which allows for evaluation of the subject's eye with higher quality (e.g., sensitivity, specificity, accuracy, precision, reproducibility, etc.) than when evaluation is performed without taking the axial length of the subject's eye into consideration. Furthermore, according to the fourth operation example, it is possible to automatically select a reference database according to the axial length of the subject's eye and evaluate the subject's eye using the selected reference database. Therefore, the fourth operation example does not complicate the evaluation work. A modification of the fourth example operation mode will now be described. In this modification, multiple reference databases are prepared by taking into consideration other parameters in addition to the axial length. In some non-limiting examples, multiple reference databases may be prepared by taking into consideration at least the presence and / or severity of a specific disease (e.g., myopia). In some non-limiting examples, multiple reference databases may be prepared by taking into consideration at least an optical characteristic of the eye (e.g., eye refractive power). In one specific example, a "no myopia category," a "myopia category," and a "high myopia category" are set. For the no myopia category, one or more reference databases corresponding to one or more axial length ranges are prepared. For the myopia category, one or more reference databases corresponding to one or more axial length ranges are prepared. For the high myopia category, one or more reference databases corresponding to one or more axial length ranges are prepared. According to such a modified example, a comprehensive evaluation can be performed taking into consideration factors other than the axial length, thereby enabling an even higher quality evaluation of the eye to be examined. A fifth example of the operation mode will now be described. The main features of the fifth example of the operation mode are a preparation step of preparing a reference database and an evaluation step performed based on this reference database. Figure 8 shows a series of sub-steps in the preparation step of the fifth example of the operation mode. The fifth example of the operation mode can be performed using any device or any system. The first substep of step S51 is to prepare a reference database defined over a predetermined axial length range. This reference database is called the original reference database. The axial length range for which the original reference database is defined is called the original axial length range. In a non-limiting example shown in Figure 9, an original reference database 901 is defined over an original axial length range 901a. The original reference database may be a standard reference database, for example, may include an existing reference database created using normal eyes as samples and / or a newly created reference database. In a non-limiting example, the original reference database may be a database showing the thickness distribution of a specific retinal tissue defined over a predetermined range of normal axial lengths, i.e., the original reference database in this example may be a reference database created based on the retinal tissue thickness distribution of a large number of sample eyes whose axial lengths fall within the normal range. The second sub-step of step S52 is to extend the original axial length range. That is, an axial length range is set that includes the original axial length range defined by the original reference database and has a wider range than the original axial length range. The axial length range obtained by extending the original axial length range is called the extended axial length range. When an original reference database in which the original axial length range is a normal axial length range is used, the second sub-step can, for example, set the extended axial length range to a range that includes this normal axial length range, a predefined short axial length range, and a predefined long axial length range. In the example shown in Figure 9, the original axial length range (normal axial length range) 901a, which is the definition range of the original reference database 901, is expanded to a range that includes the original axial length range 901a, the short axial length range 903a, and the long axial length range 904a. The third sub-step of step S53 is to apply regression analysis to the original reference database to obtain a regression equation that spans the extended axial length range (i.e., a regression equation whose domain is the extended axial length range). This regression calculation is called extrapolation. The form of the regression equation is determined by the type of regression analysis used and may be, for example, a regression line or a regression curve. The regression calculation performed in the third sub-step may be performed by any method. Extrapolation is a calculation that estimates a value outside the range of known numerical data based on the numerical data. This estimation is performed by fitting the numerical data to a predetermined function. Non-limiting examples of extrapolation methods include linear extrapolation, non-linear extrapolation, Richardson extrapolation, Aitken's delta-squared acceleration algorithm, and Stephensen transformation. The regression calculation performed in the third sub-step may also be a method that uses a machine learning engine. The regression calculation performed in the third sub-step may also be a combination of two or more methods. 9, a regression equation 902 is obtained by applying regression analysis to a large amount of data contained in an original reference database 901. In the regression equation 902, the portion indicated by a solid line represents the regression equation for the original axial length range (normal axial length range) 901a. The portion indicated by a dotted line represents the portion obtained by extrapolation. That is, the portions indicated by dotted lines represent the regression equation for the short axial length range 903a and the regression equation for the long axial length range 904a. In the fourth sub-step of step S54, the regression equation obtained in the third sub-step is applied to the original reference database to create a reference database with an expanded definition range (an expanded reference database). 9, an original reference database 901 is expanded by applying a regression equation 902 to the original reference database 901. The regression equation 902 expands the original axial length range 901a to a range including the original axial length range 901a, a short axial length range 903a, and a long axial length range 904a. The expanded reference database obtained by expanding the original reference database 901 using the regression equation 902 includes the original reference database 901, a short axial length reference database 903, and a long axial length reference database 904. The created extended reference database is stored in the memory device of each ophthalmic device (e.g., ophthalmic imaging device, ophthalmic information processing device, system, etc.) that performs the evaluation of the subject's eye, and / or in a memory device accessible by each ophthalmic device. With the above preparations, the ophthalmic apparatus 300 can execute the non-limiting operations shown in Fig. 10. In the photographing process of step S61, the ophthalmic apparatus 300 applies OCT scanning to the fundus of the subject's eye E to generate an image. In the axial length data acquisition process of step S62, the ophthalmic apparatus 300 acquires axial length data (axial length value) of the subject's eye E. In some non-limiting examples, the ophthalmic apparatus 300 acquires axial length data by applying axial length measurement to the subject's eye E. In some non-limiting examples, the processor 320 externally receives separately measured axial length data of the subject's eye E. Steps S61 and S62 may be executed in reverse order. Alternatively, steps S61 and S62 may be executed at least partially in parallel. In the analysis step of step S63, the processor 320 analyzes the image of the fundus of the subject's eye E generated in step S61 to generate evaluation data. In the evaluation process of step S64, the processor 320 evaluates the subject's eye E based on the extended reference database created in step S54 of FIG. 8, the axial length data acquired in step S62, and the evaluation data created in step S63. As an example, the evaluation process will be described when the extended reference database shown in FIG. 9 (a combination of the original reference database 901, the short eye axis reference database 903, and the long eye axis reference database 904) is used. First, the processor 320 determines which portion of the extended reference database to use for evaluation based on the axial length data acquired in step S62. If the axial length value of the subject's eye E falls within the normal axial length range, the portion of the extended reference database corresponding to the original reference database 901 is selected. If the axial length value of the subject's eye E falls within the short axial length range, the portion of the extended reference database corresponding to the short axial reference database 903 is selected. If the axial length value of the subject's eye E falls within the long axial length range, the portion of the extended reference database corresponding to the long axial reference database 904 is selected. Next, the processor 320 evaluates the eye E by comparing the evaluation data of the fundus of the eye E obtained in the analysis process of step S63 with the portion selected from the extended reference database. According to the fifth example operating mode described above, even if the axial length of the subject's eye is not a standard value, the subject's eye can be evaluated using an extended reference database created from a standard reference database (original reference database). Furthermore, according to the fifth operational mode example, the evaluation of the subject's eye using the extended reference database can be performed automatically, so the evaluation work is not made complicated. Furthermore, according to the fifth example of the operational mode, an extended reference database can be created from the original reference database, which makes it possible to reduce the effort and time required to create a reference database. The regression equation and / or the extended reference database of the fifth operating mode example can be used in the OCT scan area determination process (S13) of the second operating mode example. Similarly, the multiple reference databases of the fourth operating mode example can be used in the OCT scan area determination process (S13) of the second operating mode example. As a result, even if the axial length of the subject's eye is not a standard value, by using any of this information (the regression equation, the extended reference database, or the multiple reference databases), it is possible to perform a fundus OCT scan in an appropriate scan range according to the axial length of the subject's eye, and appropriate evaluation can be performed based on the data obtained thereby. Next, ophthalmic devices according to some non-limiting embodiments will be described. The ophthalmic device according to some embodiments has a function of performing an OCT scan to generate an OCT image and a function of calculating the intraocular distance based on the OCT image. The ophthalmic device according to some embodiments has a function of generating a frontal fundus image and / or a function of externally receiving the frontal fundus image, a function of determining dimensions for the OCT scan, and a function of performing the OCT scan based on the determined dimensions. The ophthalmic device according to some embodiments has a function of calculating the intraocular distance and a function of performing the OCT scan by changing the arm length of the OCT optical system according to the intraocular distance. The OCT method performed by the ophthalmic apparatus according to the embodiment may be any method, and some embodiments use either spectral domain OCT or swept source OCT. Spectral domain OCT is a technique in which light from a low-coherence light source is split into measurement light and reference light, return light from the test object is superimposed on the reference light to generate interference light, the spectral distribution of the generated interference light is detected using a spectroscope, and image construction processing such as Fourier transform is applied to the detected spectral distribution. Swept-source OCT is a technique in which light from a tunable light source is split into measurement light and reference light, return light from the test object is superimposed on the reference light to generate interference light, the generated interference light is detected by a balanced photodiode, and image construction processing such as Fourier transform is applied to the detection data collected in response to the wavelength sweep and scanning of the measurement light. In brief, spectral-domain OCT is an OCT method that acquires the spectral distribution of interference light in a spatially resolved manner, and swept-source OCT is an OCT method that acquires the spectral distribution of interference light in a time-resolved manner. Some embodiments may use other OCT methods (e.g., time-domain OCT). The ophthalmic device of the embodiment mainly described in this disclosure functions as a fundus camera that generates digital fundus photographs. However, the ophthalmic device of another embodiment may be equipped with another fundus imaging modality. For example, the ophthalmic device of some embodiments may function as any of the fundus imaging modalities of an SLO, a slit lamp microscope, and a surgical microscope. Unless otherwise specified, this disclosure may use the term "image data" to refer to a collection of pixel data and the term "image" to refer to visual information generated from this image data interchangeably. 11 to 13 show the configuration of an ophthalmologic apparatus according to a non-limiting embodiment. The ophthalmologic apparatus 1 includes a fundus camera unit 2, an OCT unit 100, and an arithmetic and control unit 200. The fundus camera unit 2 includes elements of a fundus camera and elements of an OCT scanner. The OCT unit 100 includes elements of an OCT scanner. The arithmetic and control unit 200 includes one or more processors that perform various processes (such as calculation, analysis, and control) and a storage device. The fundus camera unit 2 will now be described. Fig. 11 shows a non-limiting configuration of the fundus camera unit 2. The fundus camera unit 2 is capable of photographing the fundus Ef and the anterior segment of the subject's eye E. The digital image generated by the fundus camera unit 2 is typically a front image. The fundus camera unit 2 acquires observation images by video recording using near-infrared fixed light as illumination light, and also acquires photographed images by photography using visible flash light as illumination light. The fundus camera unit 2 includes an illumination optical system 10 and an imaging optical system 30. The illumination optical system 10 irradiates illumination light onto the subject's eye E. The imaging optical system 30 images the subject's eye E being irradiated with the illumination light. The fundus camera unit 2 guides measurement light provided from the OCT unit 100 to the subject's eye E, and also guides return light of the measurement light projected onto the subject's eye E to the OCT unit 100. The observation illumination light output from the observation light source 11 of the illumination optical system 10 is reflected by the concave mirror 12, passes through the condenser lens 13, and passes through the visible cut filter 14 to become near-infrared light.It is then focused near the imaging light source 15, reflected by the mirror 16, and passed through the relay lens system 17, relay lens 18, aperture 19, and relay lens system 20 to be guided to the aperture mirror 21.It is reflected by the mirror portion around the central hole of the aperture mirror 21, passes through the dichroic mirror 46, is refracted by the objective lens 22, and is projected onto the subject's eye E. The return light of the observation illumination light projected onto the subject's eye E is refracted by the objective lens 22, passes through the dichroic mirror 46, passes through the central hole of the aperture mirror 21, passes through the dichroic mirror 55, passes through the photographing focusing lens 31, is reflected by the mirror 32, passes through the half mirror 33A, is reflected by the dichroic mirror 33, and is imaged on the light-receiving surface of the image sensor 35 by the imaging lens 34. The image sensor 35 detects the return light at regular time intervals. The focus of the photographing optical system 30 is adjusted according to the photographing region. The imaging illumination light output from the imaging light source 15 is projected onto the fundus oculi Ef along the same path as the observation illumination light. The return light of the imaging illumination light from the subject's eye E is guided to the dichroic mirror 33 along the same path as the return light of the observation illumination light, passes through the dichroic mirror 33, is reflected by a mirror 36, and is imaged by an imaging lens 37 on the light-receiving surface of an image sensor 38. The liquid crystal display (LCD) 39 displays a fixation target (fixation target image) used to guide and fixate the line of sight. The light beam output from the LCD 39 is reflected by the half mirror 33A, reflected by the mirror 32, passes through the photographing focusing lens 31 and the dichroic mirror 55, passes through the central hole of the aperture mirror 21, transmits through the dichroic mirror 46, is refracted by the objective lens 22, and is projected onto the fundus Ef. The alignment optical system 50 generates an alignment index used to align the ophthalmic apparatus 1 with the subject's eye E. Alignment light output from a light-emitting diode (LED) 51 passes through an aperture 52, an aperture 53, and a relay lens 54, is reflected by a dichroic mirror 55, passes through the central hole of the aperture mirror 21, transmits through the dichroic mirror 46, is refracted by the objective lens 22, and is projected onto the subject's eye E. Return light of the alignment light from the subject's eye E is guided to the image sensor 35 via the same path as the return light of the observation illumination light. By referring to the alignment index image generated by the image sensor 35, a user can perform manual alignment and / or the ophthalmic apparatus 1 can perform automatic alignment. The focusing optical system 60 generates a split index used for focus adjustment of the subject's eye E. The focusing optical system 60 moves along the optical path (illumination optical path) of the illumination optical system 10 in conjunction with movement of the photographing focusing lens 31 along the optical path (photography optical path) of the photographing optical system 30. The reflecting rod 67 is inserted into and removed from the illumination optical path. When performing focus adjustment, the reflective surface of the reflecting rod 67 is tilted and positioned in the illumination optical path. The focusing light output from the LED 61 passes through the relay lens 62, is split into two beams by the split index plate 63, passes through the two-hole diaphragm 64, is reflected by the mirror 65, is once imaged and reflected by the condenser lens 66 on the reflective surface of the reflecting rod 67, passes through the relay lens 20, is reflected by the aperture mirror 21, passes through the dichroic mirror 46, is refracted by the objective lens 22, and is projected onto the subject's eye E. The return light of the focusing light from the subject's eye E is guided to the image sensor 35 through the same path as the return light of the alignment light. By referring to the split target image generated by the image sensor 35, manual focusing by the user and / or autofocusing by the ophthalmic apparatus 1 is performed. The diopter correction lenses 70 and 71 are selectively inserted into the photographing optical path between the aperture mirror 21 and the dichroic mirror 55. The diopter correction lens 70 is a plus lens for correcting farsightedness, and the diopter correction lens 71 is a minus lens for correcting nearsightedness. The dichroic mirror 46 combines the fundus imaging optical path and the OCT optical path (measurement arm). The dichroic mirror 46 reflects light in the wavelength band used for OCT and transmits light for fundus imaging. The measurement arm is provided with, in order from the OCT unit 100 side, a collimator lens unit 40, a retroreflector 41, a dispersion compensation member 42, an OCT focusing lens 43, an optical scanner 44, and a relay lens 45. The retroreflector 41 is movable along the optical path of the measurement light LS incident thereon and is used to correct the optical path length according to the axial length and adjust the interference state. The retroreflector 41 is moved by a retroreflector (RR) driver 41A shown in FIG. 13. The dispersion compensation member 42 is used for dispersion compensation between the measurement arm and the reference arm. The OCT focusing lens 43 is movable along the measurement arm and is used to adjust the focus of the measurement arm. The movement of the OCT focusing lens 43 is coordinated with the movement of the imaging focusing lens 31 and the movement of the focus optical system 60. The optical scanner 44 is positioned at a position substantially conjugate with the pupil of the subject's eye E by alignment, and changes the traveling direction of the measurement light LS. The optical scanner 44 includes, for example, a galvano scanner that deflects the measurement light LS in the x direction and a galvano scanner that deflects it in the y direction. In the present disclosure, the direction of the optical axis of the fundus camera unit 2 (objective lens 22) is defined as the z-direction, one direction perpendicular to the z-direction is defined as the x-direction, and a direction perpendicular to both the z-direction and the x-direction is defined as the y-direction. In many ophthalmic examinations, alignment in the xy directions is performed to align the device optical axis (in this embodiment, the optical axis of the objective lens 22) with the ocular axis of a seated or standing subject, and alignment in the z direction is performed to align the distance between the device optical system (e.g., the objective lens 22) and the subject's eye with a predetermined value (working distance). In accordance with the conventions in the ophthalmic field, the present disclosure defines the direction of the axis of the subject's eye E as the z-direction, the horizontal direction as the x-direction, and the vertical direction (the subject's body axis direction) as the y-direction. When performing an examination on a subject in a different position, directions can be defined in accordance with these definitions. The OCT unit 100 will now be described. FIG. 12 shows a non-limiting configuration of the OCT unit 100. The OCT unit 100 has a spectral domain OCT optical system. This OCT optical system includes an interference optical system. This interference optical system splits light from a low-coherence light source (broadband light source) into measurement light LS and reference light LR, and generates interference light LC by superimposing the return light of the measurement light LS projected onto the subject's eye E by the measurement arm and the reference light LR that has passed through the reference arm. A spectroscope 130 generates an electrical signal (interference signal) that indicates the spectral distribution of the interference light LC. The light source unit 101 outputs broadband low-coherence light L0, and includes an optical output device such as a superluminescent diode (SLD), an LED, or a semiconductor optical amplifier (SOA). Low-coherence light L0 output from light source unit 101 is guided by optical fiber 102 to polarization controller 103, where its polarization state is adjusted, and then guided by optical fiber 104 to fiber coupler 105, where it is split into measurement light LS and reference light LR. The measurement light LS is guided by the measurement arm, and the reference light LR is guided by the reference arm. The reference light LR is guided by an optical fiber 110 to a collimator 111 where it is converted into a parallel beam, passes through an optical path length correction member 112 for compensating for the optical distance between the measurement arm and the reference arm, passes through a dispersion compensation member 113 for compensating for dispersion between the measurement arm and the reference arm, and is then guided to a retroreflector 114. The retroreflector 114 is movable in a direction along the optical path of the reference light LR incident thereon. The retroreflector 114 is moved by a retroreflector (RR) driver 114A shown in FIG. 13. The movement of the retroreflector 114 is used to correct the optical path length based on the axial length of the subject's eye E and to adjust the interference state. The reference light LR that has passed through the retroreflector 114 passes through the dispersion compensation member 113 and the optical path length correction member 112, is converted from a parallel beam into a focused beam by the collimator 116, is guided through the optical fiber 117 to the polarization controller 118 where its polarization state is adjusted, is guided through the optical fiber 119 to the attenuator 120 where its light amount is adjusted, and reaches the fiber coupler 122 via the optical fiber 121. On the other hand, the measurement light LS is guided through the optical fiber 127 to the collimator lens unit 40, where it is converted into a parallel beam, passes through the retroreflector 41, the dispersion compensation member 42, the OCT focusing lens 43, the optical scanner 44, and the relay lens 45, is reflected by the dichroic mirror 46, is refracted by the objective lens 22, and is projected onto the subject's eye E. The measurement light LS is scattered and reflected at various depth positions in the subject's eye E. Return light of the measurement light LS from the subject's eye E is guided by the measurement arm to the fiber coupler 105, and reaches the fiber coupler 122 via the optical fiber 128. The fiber coupler 122 generates interference light LC by superimposing the measurement light LS incident from the optical fiber 128 and the reference light LR incident from the optical fiber 121. The interference light LC is guided to the spectroscope 130 via the optical fiber 129. The spectroscope 130 converts the incident interference light LC into a parallel beam using a collimator lens, resolves this parallel beam into multiple spectral components using a diffraction grating, and projects these spectral components onto an image sensor via a lens. This image sensor is, for example, a line sensor, and detects the multiple spectral components of the interference light LC to generate an electrical signal (interference signal, detection signal). The interference signal, which includes information on the spectral distribution of the interference light LC, is sent to the arithmetic and control unit 200. The OCT unit 100 of some embodiments may include a swept-source OCT optical system. In this case, the light source unit 101 includes, for example, a tunable light source (e.g., a near-infrared tunable laser) that rapidly changes the wavelength of emitted light. Furthermore, the swept-source OCT optical system splits the interference light LC at a predetermined ratio (e.g., 1:1) to generate a pair of interference lights, which are then detected by balanced photodiodes. The balanced photodiodes detect each of the pair of interference lights and output the difference between the pair of detection signals obtained. This difference signal is sent to a data acquisition system (DAQ). The light source unit 101 provides the data acquisition system with a clock synchronized with the wavelength sweep. The data acquisition system samples the difference signal input from the balanced photodiode based on the clock from the light source unit 101. Data (interference signals) obtained by sampling the difference signals are provided to subsequent processing (e.g., image construction). 11 and 12, optical path length changing elements (retroreflectors 41 and 114) are provided in both the measurement arm and the reference arm. In some embodiments, an optical path length changing element may be provided in only one of the measurement arm and the reference arm. Furthermore, the type of optical path length changing element is not limited to that of this embodiment. In some embodiments, the optical path length changing element in the reference arm may be a movable reflecting member (reference mirror) (see reference mirror 314 in FIG. 3). More generally, the optical path length changing element functions to change the relative lengths of the measurement arm and the reference arm, that is, to move the coherence gate of an interference optical system having the measurement arm and the reference arm. The moving mechanism 150 will be described. The moving mechanism 150 moves the optical system of the ophthalmologic apparatus 1. In some embodiments, the moving mechanism 150 moves at least the fundus camera unit 2 three-dimensionally. This three-dimensional movement is realized by, for example, a combination of movement in the x direction, movement in the y direction, and movement in the z direction. The arithmetic and control unit 200 will now be described. The arithmetic and control unit 200 executes various processes such as control, calculation, analysis, etc. This disclosure will describe some non-limiting examples of processes that can be executed by the arithmetic and control unit 200. The hardware elements of the arithmetic control unit 200 include, for example, a processor, random access memory (RAM), read-only memory (ROM), a hard disk drive (HDD), a solid-state drive (SSD), and a communication interface. Storage devices such as the HDD and SSD store various computer programs. In some embodiments, the arithmetic and control unit 200 includes a user interface (also called a human-machine interface) such as an operation device, an input device, a display device, etc. In some embodiments, at least a part of the user interface is arranged as a peripheral device of the ophthalmologic apparatus 1. 13 shows a non-limiting configuration of the processing system of the ophthalmologic apparatus 1, and in particular shows a non-limiting configuration of the arithmetic and control unit 200. The arithmetic and control unit 200 includes a control unit 210, an image construction unit 220, a data processing unit 230, and a user interface 240. The control unit 210 includes a processor and controls each unit of the ophthalmic apparatus 1. The control unit 210 includes a main control unit 211 and a memory unit 212. The main control unit 211 includes a processor and controls each element of the ophthalmic apparatus 1 (including some of the elements shown in FIGS. 11 to 13). In some embodiments, the main control unit 211 controls external equipment (apparatus, device, system, etc.) connected to the ophthalmic apparatus 1. The functions of the main control unit 211 are realized by cooperation between hardware including circuits and control software. The memory unit 212 includes a storage device such as an HDD or SSD. The image constructing unit 220 processes data collected by applying an OCT scan to the fundus Ef of the subject's eye E to generate OCT image data. The image constructing unit 220 includes a processor. The functions of the image constructing unit 220 are realized by cooperation between hardware including circuits and image constructing software. The processing performed by the image constructing unit 220 is similar to image construction in conventional spectral domain OCT. The image constructing unit 220 in some embodiments performs processing similar to image construction in conventional swept-source OCT. The image construction unit 220 of this embodiment constructs cross-sectional image data by processing the data (interference signal including information on the spectral distribution of the interference light LC) generated by the spectroscope 130. This image construction process includes sampling (A / D conversion), denoising, filtering, fast Fourier transform (FFT), and the like, similar to conventional spectral domain OCT. The OCT image data constructed by the image constructor 220 is a data set including a set of image data. This set of image data is a set of A-scan image data generated by imaging the reflection intensity profile of each of a plurality of A-lines arranged in the area where the OCT scan was applied. Such OCT image data is an example of an OCT intensity image. The OCT image data may be stack data constructed by embedding multiple B-scan image data in a single three-dimensional coordinate system. The image constructor 220 can construct volume data (voxel data) by applying voxelization processing to the stack data. The stack data and volume data are examples of three-dimensional image data in which positions are expressed using a three-dimensional coordinate system (x-y-z coordinate system), and are also examples of three-dimensional OCT intensity images. The image constructing unit 220 can process the three-dimensional image data. For example, the image constructing unit 220 can generate new image data by applying rendering to the three-dimensional image data. This rendering method may be any method, such as volume rendering, surface rendering, multiplanar reconstruction (MPR), maximum intensity projection (MIP), minimum intensity projection (MIP), or average intensity projection (AIP). As a non-limiting example of rendering, the image constructor 220 may generate projection image data by integrating 3D image data in the z direction. As another example, the image constructor 220 may construct shadowgram data by integrating a portion of the 3D image data (3D partial image data) in the z direction. The 3D partial image data is extracted from the 3D image data using a known segmentation method. The projection image data and shadowgram data are 2D image data whose positions are expressed using a 2D coordinate system (xy coordinate system). The direction in which the 3D image data is integrated is not limited to the z direction. Therefore, the image constructor 220 can generate 2D image data of any orientation from the 3D image data. In addition to the above-described OCT structural imaging, the ophthalmic apparatus 1 may be configured to perform OCT functional imaging. Non-limiting examples of OCT functional imaging include OCT angiography, OCT blood flow measurement, OCT elastography, and OCT polarimetry. OCT angiography is a technique for imaging a vascular network by measuring and visualizing changes in OCT signals according to blood flow. OCT blood flow measurement is a technique for measuring and visualizing the dynamics of blood flow within blood vessels. OCT elastography is a technique for measuring and visualizing the distribution of strain and stiffness in biological tissue. OCT polarimetry is a technique for measuring and visualizing the structural birefringence of fibrous tissue in a living organism. The data processing unit 230 performs various types of data processing. For example, the data processing unit 230 processes images (fundus images, anterior segment images, etc.) acquired by the fundus camera unit 2 and images (OCT images) acquired using OCT scanning. The data processing unit 230 includes a processor. The data processing unit 230 is realized by cooperation between hardware including circuits and data processing software. Some non-limiting examples of the data processing unit 230 are described below. The user interface 240 includes a display unit 241 and an operation unit 242. The display device 3 in Fig. 11 is an example of the display unit 241. The operation unit 242 includes an operation device and an input device. Examples of devices in the operation unit 242 include a switch, a lever, a mouse, a trackball, a keyboard, and an operation panel. Several non-limiting examples of the ophthalmic apparatus 1 realized by the elements (hardware elements, software elements) shown in Figures 11 to 13 will be described. Two or more of the non-limiting examples may be at least partially combined. Furthermore, any feature of the present disclosure may be combined with the non-limiting examples. 14 is a non-limiting example of the ophthalmic apparatus 1. The ophthalmic apparatus 1000 of this example includes a control unit 1010, a scanning unit 1020, an image constructing unit 1030, an optical path length changing unit 1040, and an intraocular distance calculating unit 1050. The control unit 1010 is configured to control each unit of the ophthalmologic apparatus 1000. The control unit 1010 is realized by cooperation between hardware including circuits and control software. The processor 320 in FIG. 3 provides a non-limiting example of the control unit 1010. The control unit 210 in FIG. 13 also provides a non-limiting example of the control unit 1010. The scanning unit 1020 is configured to apply an OCT scan to the fundus of the subject's eye to generate an electrical signal (interference signal). The OCT scanner 310 in Fig. 3 provides a non-limiting example of the scanning unit 1020. Also, a combination of a part of the fundus camera unit 2 (a group of elements forming the measurement arm) and the OCT unit 100 in Figs. 11 to 13 provides a non-limiting example of the scanning unit 1020. The image constructing unit 1030 is configured to construct an OCT image based on the interference signal generated by the scanning unit 1020. The image constructing unit 1030 is realized by cooperation between hardware including circuits and image constructing software. The processor 320 in FIG. 3 provides a non-limiting example of the image constructing unit 1030. The arithmetic and control unit 200 in FIG. 11 and the image constructing unit 220 in FIG. 13 provide non-limiting examples of the scanning unit 1020. The optical path length changing unit 1040 is configured to change the optical path length of the scanning unit 1020. The scanning unit 1020 is configured to be able to perform OCT scanning and includes an interference optical system having a measurement arm and a reference arm. The optical path length changing unit 1040 is configured to change at least one of the optical path length of the measurement arm and the optical path length of the reference arm. 13 provides a non-limiting example of the optical path length changing unit 1040. In addition, in the configurations shown in FIGS. 11 to 13, the retroreflector driving unit 41A (and the control unit 210 that controls it), which is an element that moves the retroreflector 41, provides a non-limiting example of the optical path length changing unit 1040. Similarly, the retroreflector driving unit 114A (and the control unit 210 that controls it), which is an element that moves the retroreflector 114, provides a non-limiting example of the optical path length changing unit 1040. The intraocular distance calculation unit 1050 is configured to calculate the intraocular distance of the test eye based at least on the OCT image constructed by the image construction unit 1030 and optical path length information indicating the optical path length of the scan unit 1020 when the OCT scan corresponding to this OCT image is applied to the fundus of the test eye. As mentioned above, the intraocular distance may be either the axial length (AEL) or the vitreous cavity depth (VCD), which are merely examples of intraocular distances and are not intended to limit the types of intraocular distances. The optical path length information indicates at least one of the optical path length of the measurement arm and the optical path length of the reference arm. In the example of Fig. 3, the optical path length information indicates the position of the reference mirror 314. In the examples of Figs. 11 to 13, the optical path length information indicates at least one of the positions of the retroreflector 41 and the retroreflector 114. In an example where only one of the retroreflectors 41 and 114 is provided, the optical path length information indicates the position of that retroreflector. The type of information included in the optical path length information may be arbitrary. For example, the optical path length information may include position information indicating the positions of optical components (such as the reference mirror 314, the retroreflector 41, and the retroreflector 114) that define the optical path length. This position information can be generated by detecting the positions of the optical components using a position sensor such as a potentiometer, an encoder, or a laser sensor. The position information in this example is generated, for example, by cooperation between a position sensor (not shown) and the control unit 1010. Another example of optical path length information includes information equivalent to the position information. For example, the optical path length information may include status information indicating the status of a mechanism (such as a reference mirror moving mechanism, retroreflector driving unit 41A, or retroreflector driving unit 114A) that moves an optical member that determines the optical path length. This status information can be generated, for example, by detecting the status of the mechanism using a sensor such as an encoder. The status information in this example is generated, for example, by cooperation between a sensor (not shown) and the control unit 1010. In yet another example, the optical path length information is generated based on the content of control (such as a control history) that a control element (such as the processor 320 or the control unit 210) has executed on the mechanism. The optical path length information in this example is generated, for example, by the control unit 1010. If the optical path length changing unit 1040 includes a control element (such as the processor 320 or the control unit 210), the control element may generate the optical path length information in this example. The intraocular distance calculation unit 1050 is realized by cooperation between hardware including a circuit and intraocular distance calculation software. The processor 320 in Fig. 3 provides a non-limiting example of the intraocular distance calculation unit 1050. The data processing unit 230 in Fig. 13 also provides a non-limiting example of the intraocular distance calculation unit 1050. Next, some non-limiting examples of the processing performed by the intraocular distance calculation unit 1050 will be described. The intraocular distance calculation unit 1050 analyzes the OCT image of the fundus of the test eye constructed by the image construction unit 1030 to identify an image corresponding to a specific region of the fundus (referred to as a regional image). In this example, the regional image identification process applies segmentation to the OCT image to detect an image of a specific region of the fundus from the OCT image. The segmentation method used in this example may be of any type, including a method using a machine learning model, a method not using a machine learning model, or a method that at least partially combines these methods. Furthermore, the region of the fundus identified as the regional image may be any region, such as the internal limiting membrane (ILM), nerve fiber layer (NFL), or retinal pigment epithelium (RPE), which may be a pre-specified retinal tissue. Furthermore, the intraocular distance calculation unit 1050 calculates the intraocular distance based at least on the position of the identified regional image in the OCT image and the optical path length information. The type of position of the local image in the OCT image may be any type, and may be, for example, the average depth position of the local image. A specific example will be described with reference to Figs. 15A to 15D. Fig. 15A shows an OCT image 2000 of the fundus of the subject's eye constructed by the image construction unit 1030. The intraocular distance calculation unit 1050 applies segmentation to the OCT image 2000 to identify an internal limiting membrane image 2010 shown in Fig. 15B. Next, the intraocular distance calculation unit 1050 calculates the average value of the z coordinates of each pixel of the internal limiting membrane image 2010. This results in an average depth position 2020 of the internal limiting membrane image 2010 shown in Fig. 15C. Fig. 15D shows the z coordinate "z ILM -mean" and the coherence gate position "z ０ The intraocular distance calculation unit 1050 calculates the z coordinate "z ILM -mean" and coherence gate position "z ０ " is substituted into "Z-mean" and "Ref mirror position" in the above-mentioned [Equation 2] to calculate the intraocular distance "Estimated AEL (um)" of the subject's eye. This intraocular distance is an air-equivalent value. The flowchart in FIG. 16 illustrates an example of the operation of the ophthalmic apparatus 1000 of this embodiment. First, in step S71, the ophthalmic apparatus 1000 adjusts the optical path length of the scan unit 1020. For example, the control unit 1010 controls the scan unit 1020 to apply a B-scan to the fundus of the subject's eye. The image construction unit 1030 constructs a B-scan image based on the interference signal generated by the B-scan. The control unit 1010 controls the optical path length change unit 1040 so that the image of the fundus depicted in the B-scan image is positioned at a predetermined depth position. The operation performed by this series of processes is auto-alignment of the OCT scan position in the depth direction, and is also referred to as Auto-Z. The ophthalmic apparatus 1000 may perform tracking to maintain the alignment state achieved by Auto-Z. Next, in step S72, the ophthalmologic apparatus 1000 stores optical path length information indicating the state of the optical path length of the scanning unit 1020 achieved by the optical path length adjustment in step S71. For example, the control unit 1010 stores the optical path length information in a storage device (not shown) (for example, the storage unit 212 in FIG. 13 ). Next, in step S73, the ophthalmologic apparatus 1000 generates an interference signal by applying an OCT scan to the fundus of the subject's eye using the scan unit 1020. Furthermore, in step S74, the ophthalmologic apparatus 1000 generates an OCT image of the fundus of the subject's eye using the image construction unit 1030 based on the interference signal generated in step S73. Next, in step S75, the ophthalmologic apparatus 1000 calculates the intraocular distance of the subject's eye using the intraocular distance calculation unit 1050 based on the OCT image of the fundus of the subject's eye constructed in step S74 and the optical path length information stored in step S72. The calculated intraocular distance may be a value indicating the distance in air (air-equivalent value). However, the present invention is not limited to this, and the intraocular distance may be an optical distance value that takes into account the refractive index of the eye, or a value defined in another way. The ophthalmologic apparatus 1000 described above can provide a novel method for measuring intraocular distance using OCT. This novel method automatically calculates the intraocular distance of the subject's eye based on the state of the optical path length of the scan unit 1020 when applying an OCT scan to the fundus of the subject's eye and the OCT image obtained by the OCT scan. Therefore, there is no need to prepare a separate device for measuring the intraocular distance, and there is no need to add new hardware to existing OCT scanners. Moreover, the intraocular distance can be calculated through a simple and easy calculation. An ophthalmic apparatus 1000A shown in Fig. 17 is one non-limiting example of the ophthalmic apparatus 1. Similar to the ophthalmic apparatus 1000 of Fig. 14 , the ophthalmic apparatus 1000A of this example includes a control unit 1010, a scanning unit 1020, an image constructing unit 1030, an optical path length changing unit 1040, and an intraocular distance calculating unit 1050. Unless otherwise specified, each of these elements has the same configuration and performs the same operation as the corresponding element of the ophthalmic apparatus 1000. In addition to these elements, the ophthalmic apparatus 1000A of this example includes an alignment unit 1060. The alignment unit 1060 is configured to align the scan unit 1020 with the subject's eye. For example, the alignment unit 1060 performs alignment in both the xy direction and the z direction. In the configurations shown in FIGS. 11 to 13, the alignment optical system 50 and the movement mechanism 150 (and the control unit 210 that controls them) provide non-limiting examples of the alignment unit 1060. The intraocular distance calculation unit 1050 of the present example calculates the intraocular distance of the subject's eye based on at least an OCT image based on an interference signal generated by an OCT scan applied to the fundus of the subject's eye after completion of alignment by the alignment unit 1060, and optical path length information indicating the optical path length when this scan was applied to the fundus. That is, the ophthalmologic apparatus 1000A of the present example calculates the intraocular distance using an OCT image obtained with the alignment adjusted. The intraocular distance calculation unit 1050 in this example may be configured to calculate the intraocular distance based on an OCT image based on an interference signal generated by an OCT scan after alignment is completed, optical path length information, and dimensional information indicating the dimensions of a specific part of the test eye that has been acquired in advance. The type of dimensional information may be any type, such as corneal thickness, anterior chamber depth, lens thickness, or vitreous cavity depth. The dimensional information may be a standard value of a dimension of a predetermined portion, a measurement value obtained by actually examining a living eye (e.g., the subject's eye), or an estimated value calculated from data on the living eye (e.g., the subject's eye). The ophthalmic device 1000A may acquire the dimensional information from an external source, or may generate the dimensional information based on data on the subject's eye acquired from an external source. Alternatively, the ophthalmic device 1000A may acquire data by measuring or photographing the subject's eye and generate the dimensional information based on this data. 18 shows an example of the operation of the ophthalmologic apparatus 1000A of this embodiment. First, in step S81, the ophthalmologic apparatus 1000A acquires dimensional information related to a predetermined portion of the subject's eye. The acquired dimensional information is stored in a storage device (not shown) (e.g., the storage device 212 in FIG. 13 ) by, for example, the control unit 1010. In step S82, the ophthalmologic apparatus 1000A aligns the scanning unit 1020 with respect to the subject's eye using the alignment unit 1060. This places the scanning unit 1020 at an appropriate position with respect to the subject's eye. After the alignment operation is completed, tracking may be performed to maintain this alignment state. In steps S83 to S86, the ophthalmic apparatus 1000A executes the same processes as steps S71 to S74 in Fig. 16. That is, the ophthalmic apparatus 1000A adjusts the optical path length of the scan unit 1020, stores the optical path length information, applies an OCT scan to the fundus of the subject's eye to generate an interference signal, and constructs an OCT image of the fundus based on the interference signal. In step S87, the ophthalmologic apparatus 1000A calculates the intraocular distance of the subject's eye using the intraocular distance calculation unit 1050, based on the OCT image of the fundus of the subject's eye constructed in step S86, the optical path length information saved in step S84, and the dimension information acquired in step S81. The calculated intraocular distance may be an air-equivalent value. However, the present invention is not limited to this, and the intraocular distance may be an optical distance value that takes into account the refractive index of the eye, or a value defined in another way. The intraocular distance calculation unit 1050 of this example can calculate the intraocular distance using the above-mentioned [Equation 2]. In this case, the intraocular distance calculation unit 1050 may calculate the intraocular distance "Estimated AEL (um)" from the OCT image and the optical path length information, and use this as the output information of step S87. Alternatively, the intraocular distance calculation unit 1050 may calculate the intraocular distance as the output information of step S87 based on the intraocular distance "Estimated AEL (um)" and the dimension information. For example, if the dimension information includes the central corneal thickness (CCT) and the anterior chamber depth (ACD), the intraocular distance calculation unit 1050 may calculate the vitreous cavity depth VCD by subtracting the corneal thickness and the anterior chamber depth from the intraocular distance "Estimated AEL (um)": VCD = AEL - (CCT + ACD). Such an ophthalmic apparatus 1000A has the same effects as the above-described ophthalmic apparatus 1000. Furthermore, the ophthalmic apparatus 1000A is configured to determine the intraocular distance using an OCT image obtained in a suitable alignment state, which contributes to improving the quality (e.g., accuracy, reproducibility, etc.) of intraocular distance measurements. The ophthalmic apparatus 1000B shown in FIG. 19 is one non-limiting example of the ophthalmic apparatus 1. Similar to the ophthalmic apparatus 1000 of FIG. 14 , the ophthalmic apparatus 1000B of this example includes a control unit 1010, a scanning unit 1020, an image constructing unit 1030, an optical path length changing unit 1040, and an intraocular distance calculating unit 1050. Unless otherwise specified, each of these elements has the same configuration and performs the same operation as the corresponding element of the ophthalmic apparatus 1000. In addition to these elements, the ophthalmic apparatus 1000B of this example also includes a scan area determining unit 1070 and a measurement and analysis unit 1080. The control unit 1010 of this example also includes a scan control unit 1011. The scan area determination unit 1070 is configured to determine the range of the OCT scan (scan area) to be applied to the subject's eye based on the intraocular distance of the subject's eye calculated by the intraocular distance calculation unit 1050. The scan area determination process of this example includes at least a step of determining the dimensions of the scan area. Furthermore, the scan area determination process of this example may include a step of determining the position of the scan area. The position of the scan area may be defined by, for example, any of the position of a fixation target, the position of an alignment target, and the position of a landmark on the fundus (such as the optic disc, macula, or blood vessels). The scan area determination unit 1070 can determine the scan area based on the intraocular distance of the subject's eye using any of the non-limiting scan area determination methods described above. Information on the scan area determined by the scan area determination unit 1070 is provided to the control unit 1010. The scan area determiner 1070 is realized by cooperation between hardware including a circuit and scan area determiner software. The processor 320 in Fig. 3 provides a non-limiting example of the scan area determiner 1070. The data processor 230 in Fig. 13 also provides a non-limiting example of the scan area determiner 1070. The measurement and analysis unit 1080 applies measurement and analysis to the OCT image of the subject's eye. The measurement and analysis is an analytical process for measuring predetermined parameters. For example, the measurement and analysis unit 1080 derives a distribution of predetermined measurement values ​​at the fundus of the subject's eye from the OCT image of the subject's eye. An example of a measurement value related to the fundus is the thickness of a predetermined tissue of the retina (e.g., the nerve fiber layer, the ganglion cell layer, etc.). In this case, the measurement and analysis unit 1080 generates a measurement value distribution of retinal tissue thickness (retinal tissue thickness distribution) in at least a partial region of the fundus of the subject's eye. The process of generating a retinal tissue thickness distribution from a fundus OCT image is known. For example, the measurement and analysis unit 1080 can generate a thickness distribution of the retinal tissue at the fundus by performing segmentation to detect an image of the retinal tissue to be measured from the OCT image, thickness measurement to measure the thickness of the detected retinal tissue image at multiple positions, and a recording process to record the measurement positions and measurement values ​​(thickness values) in association with each other. In some non-limiting examples, the measurement and analysis unit 1080 may be configured to generate a measurement value distribution from the OCT image using a machine learning engine. The measurement and analysis unit 1080 is realized by cooperation between hardware including circuits and measurement and analysis software. The processor 320 in Fig. 3 provides a non-limiting example of the measurement and analysis unit 1080. The data processing unit 230 in Fig. 13 also provides a non-limiting example of the measurement and analysis unit 1080. The scan control unit 1011 is configured to control the scan unit 1020 based on the scan area determined by the scan area determination unit 1070. For example, the scan control unit 1011 controls the scan unit 1020 (for example, the optical scanner 316 shown in FIG. 3 or the optical scanner 44 shown in FIGS. 11 and 13) to deflect the measurement light within a deflection angle range corresponding to the dimensions of the scan area determined by the scan area determination unit 1070. The scan control unit 1011 is realized by cooperation between hardware including circuits and scan control software. A process that can be adopted when the ophthalmic apparatus 1000B is equipped with a fixation target projection system (for example, the liquid crystal display 39 shown in FIGS. 11 and 13) will be described. The scan control unit 1011 can control the fixation target projection system so as to guide the line of sight of the subject's eye in a direction corresponding to the scan area determined by the scan area determination unit 1070. The following describes processing that can be employed when the ophthalmologic apparatus 1000B is equipped with the alignment unit 1060. The scan control unit 1011 can control the alignment unit 1060 to place the scan unit 1020 at a position corresponding to the scan area determined by the scan area determination unit 1070. A process that can be employed when the ophthalmic apparatus 1000B is equipped with a fundus photography system (e.g., the fundus camera unit 2 in FIGS. 11 and 13 ) will be described. The ophthalmic apparatus 1000B photographs the fundus of the subject's eye using the fundus photography system and identifies landmarks on the fundus from the fundus image (typically, a frontal fundus image) thus acquired. Furthermore, the scan control unit 1011 can control the scan unit 1020 so that the fundus landmarks identified from the fundus image coincide with the landmarks indicated by the scan area determined by the scan area determination unit 1070. Note that the scan control unit 1011 may control at least one of the fixation target projection system and the alignment unit 1060 in addition to or instead of controlling the scan unit 1020. The flowchart in Fig. 20 shows an example of the operation of the ophthalmic apparatus 1000B of this example. In steps S91 to S94, the ophthalmic apparatus 1000B executes the same processes as steps S71 to S74 in Fig. 16. That is, the ophthalmic apparatus 1000B adjusts the optical path length of the scan unit 1020, stores the optical path length information, applies an OCT scan to the fundus of the subject's eye to generate an interference signal, and constructs an OCT image of the fundus based on the interference signal. In this example, the OCT image obtained in step S94 is referred to as the first OCT image, the OCT scan in step S92 is referred to as the first OCT scan, and the interference signal generated by this first OCT scan is referred to as the first interference signal. In step S95, the ophthalmologic apparatus 1000B calculates the intraocular distance of the subject's eye using the intraocular distance calculation unit 1050 based on at least the first OCT image obtained in step S94 and the optical path length information stored in step S92. This intraocular distance calculation is performed in the same manner as, for example, step S75 in Fig. 16 or step S87 in Fig. 18. In step S96, the ophthalmologic apparatus 1000B determines a scan area based on the intraocular distance calculated in step S95 using the scan area determination unit 1070. Information on the determined scan area is sent to the scan control unit 1011. In step S97, the ophthalmologic apparatus 1000B controls the scan unit 1020 based on the scan area determined in step S96 using the scan control unit 1011. Under the control of the scan control unit 1011, the scan unit 1020 applies an OCT scan to the fundus of the subject's eye to generate an interference signal. In this example, the OCT scan in step S97 is called the second OCT scan, and the interference signal generated by this second OCT scan is called the second interference signal. In step S98, the ophthalmologic apparatus 1000B constructs an OCT image of the fundus of the subject's eye based on the second interference signal generated in step S97 using the image construction unit 1030. The OCT image obtained in step S98 is referred to as a second OCT image. In step S99, the ophthalmologic apparatus 1000B causes the measurement analysis unit 1080 to apply measurement analysis to the second OCT image obtained in step S98, thereby generating a measurement value distribution on the fundus of the subject's eye. The ophthalmic apparatus 1000B has the same effects as the above-described ophthalmic apparatus 1000. Furthermore, the ophthalmic apparatus 1000B is configured to automatically determine a scan area based on the intraocular distance of the subject's eye and perform an OCT scan based on the determined scan area, thereby enabling easy and smooth OCT scanning in an appropriate scan area for the subject's eye. Additionally, the ophthalmic apparatus 1000B is configured to generate a measurement value distribution based on an OCT image obtained by an OCT scan in an appropriate scan area for the subject's eye, thereby enabling a high-quality measurement value distribution for the subject's eye to be acquired. As described above, the ophthalmologic apparatus 1000B can evaluate the state of fundus tissue and the risk of disease based on the acquired measurement value distribution. Therefore, the ophthalmologic apparatus 1000B can perform evaluation based on an appropriate fundus area measurement value distribution for the subject eye. Therefore, the ophthalmologic apparatus 1000B contributes to the automation of examinations such as screening and also contributes to improving the quality of examinations. Furthermore, the ophthalmologic apparatus 1000B can prevent evaluation from being performed based on an inappropriate fundus area measurement value distribution, thereby reducing the possibility of re-examination. The ophthalmic apparatus 1000C shown in FIG. 21 is one non-limiting example of the ophthalmic apparatus 1. Similar to the ophthalmic apparatus 1000B of FIG. 19 , the ophthalmic apparatus 1000C of this example includes a control unit 1010 including a scan control unit 1011, a scanning unit 1020, an image constructing unit 1030, an optical path length changing unit 1040, an intraocular distance calculation unit 1050, a scan area determination unit 1070, and a measurement and analysis unit 1080. Unless otherwise specified, each of these elements has the same configuration and performs the same operation as the corresponding element of the ophthalmic apparatus 1000B. In addition to these elements, the ophthalmic apparatus 1000C of this example includes an artifact determination unit 1090. The control unit 1010 of this example also includes an optical path length control unit 1012. The artifact determination unit 1090 is configured to determine whether or not an OCT image contains aliasing artifacts. Aliasing artifacts are likely to occur when the axial length of the subject's eye is long. The artifact determination unit 1090 applies a known aliasing artifact detection process to the OCT image to determine whether or not the OCT image contains aliasing artifacts. The artifact determination unit 1090 is realized by cooperation between hardware including a circuit and artifact determination software. The processor 320 in Fig. 3 provides a non-limiting example of the artifact determination unit 1090. The data processing unit 230 in Fig. 13 also provides a non-limiting example of the artifact determination unit 1090. The optical path length control unit 1012 is configured to control the optical path length changing unit 1040 to change the optical path length of the scanning unit 1020. The optical path length control unit 1012 is realized by cooperation between hardware including a circuit and optical path length control software. The flowchart in Fig. 22 shows an example of the operation of the ophthalmic apparatus 1000C of this example. In steps S101 to S104, the ophthalmic apparatus 1000C executes the same processes as steps S91 to S94 in Fig. 20. That is, the ophthalmic apparatus 1000C executes optical path length adjustment of the scan unit 1020, stores optical path length information, applies a first OCT scan to the fundus of the subject's eye to generate a first interference signal, and constructs a first OCT image of the fundus based on the first interference signal. In step S105, the ophthalmologic apparatus 1000C determines whether or not the first OCT image acquired in step S104 contains aliasing artifacts using the artifact determination unit 1090. If it is determined that the first OCT image contains aliasing artifacts (S106: YES), the procedure proceeds to step S107. On the other hand, if it is determined that the first OCT image does not contain aliasing artifacts (S106: NO), the procedure proceeds to step S108. In step S107, the ophthalmic apparatus 1000C controls the optical path length changing unit 1040 via the optical path length control unit 1012 to change the optical path length of the scanning unit 1020. The amount of change in the optical path length (e.g., the movement distance of the retroreflector 41 or 114) may be determined based on, for example, the dimensions of the aliasing artifact (particularly, the dimension in the depth direction). Alternatively, the ophthalmic apparatus 1000C may be configured to remove the aliasing artifact by changing the optical path length while checking the state of the aliasing artifact. After changing the optical path length, the procedure proceeds to step S108. In steps S108 to S112, the ophthalmic apparatus 1000C executes processes similar to steps S95 to S99 in Fig. 20. That is, the ophthalmic apparatus 1000C calculates the intraocular distance based on the first OCT image acquired in step 94, determines a scan area based on this intraocular distance, executes a second OCT scan based on this scan area to generate a second interference signal, constructs a second OCT image based on the second interference signal, and applies measurement analysis to the second OCT image to generate a measurement value distribution. The ophthalmic apparatus 1000C has the same effects as the ophthalmic apparatus 1000B. Furthermore, the ophthalmic apparatus 1000C enables measurement analysis and evaluation using high-quality OCT images free of aliasing artifacts. Furthermore, the ophthalmic apparatus 1000C has the advantage of being able to automatically remove aliasing artifacts. The ophthalmic apparatus 1000D shown in FIG. 23 is one non-limiting example of the ophthalmic apparatus 1. Similar to the ophthalmic apparatus 1000B of FIG. 19 , the ophthalmic apparatus 1000D of this example includes a control unit 1010 including a scan control unit 1011, a scanning unit 1020, an image constructing unit 1030, an optical path length changing unit 1040, an intraocular distance calculation unit 1050, a scan area determination unit 1070, and a measurement and analysis unit 1080. Unless otherwise specified, each of these elements has the same configuration and performs the same operation as the corresponding element of the ophthalmic apparatus 1000B. In addition to these elements, the ophthalmic apparatus 1000D of this example includes an evaluation unit 1100. The control unit 1010 of this example includes a storage unit 1013. The storage unit 1013 stores a reference value distribution 1014. The processor 320 (a storage device not shown) in FIG. 3 provides a non-limiting example of the storage unit 1013. The storage unit 212 in FIG. 13 also provides a non-limiting example of the storage unit 1013. The reference value distribution 1014 is information indicating the distribution of reference values ​​in a fundus area having a predetermined dimension. This fundus area is defined as a partial region of the fundus. The dimensions of the fundus area are the area to which the evaluation of the subject's eye is applied using the results of the measurement and analysis performed by the measurement and analysis unit 1080. In this example, the fundus area in which the reference value distribution 1014 is defined is called the reference fundus area, and the dimensions of this reference area are called reference dimensions. The reference value distribution 1014 may be any of the various reference databases described above. The reference value is, for example, the value of the fundus parameter (and / or another fundus parameter that can be derived therefrom) obtained by the measurement and analysis, and may be any of a standard value, a measured value, a statistical value, and an estimated value. The scan area determination unit 1070 of this example determines the scan area based on the reference dimension of the reference value distribution 1014 and the intraocular distance of the subject's eye calculated by the intraocular distance calculation unit 1050. For example, the scan area determination unit 1070 may be configured to determine a scan area having a dimension larger than the reference dimension. In other words, the scan area determination unit 1070 can determine, as the scan area, a fundus area that truly includes the reference fundus area for which the reference value distribution 1014 is defined. For example, the scan area determination unit 1070 can determine a provisional scan area based on the intraocular distance of the test eye in the manner described above, compare the dimensions of this provisional scan area with the reference dimensions, correct the provisional scan area (if necessary) based on the comparison results, and determine the scan area obtained by this correction as the final scan area. In this example, the reference dimension may be referred to as the first dimension, and the dimension of the scan area determined by the scan area determination unit 1070 may be referred to as the second dimension. The scan area determined by the scan area determination unit 1070 is provided to the control unit 1010. The scan control unit 1011 controls the scan unit 1020 based on this scan area to apply an OCT scan to the fundus of the subject's eye. The scan unit 1020, under the control of the scan control unit 1011, applies an OCT scan (second OCT scan) to the fundus of the subject's eye to generate an interference signal (second interference signal). The image construction unit 1030 constructs an OCT image (second optical coherence tomography image) based on the second interference signal. The measurement analysis unit 1080 applies measurement analysis to this OCT image to generate a measurement value distribution at the fundus of the subject's eye. The generated measurement value distribution is provided to the evaluation unit 1100. The evaluation unit 1100 evaluates this measurement value distribution based on the reference value distribution 1014. The evaluation unit 1100 is realized by cooperation between hardware including circuits and evaluation software. The reference value distribution 1014 is information indicating the distribution of reference values ​​of a predetermined fundus parameter in a reference fundus area having a reference dimension, while the measurement value distribution is information indicating the distribution of measurement values ​​of the fundus parameter in the fundus area to which the second OCT scan was applied. In some non-limiting examples, the fundus area to which the second OCT scan was applied includes a reference fundus area, and the measurement value distribution includes measurement values ​​at each position in the reference fundus area. In this case, the evaluation unit 1100 can compare the measurement values ​​with the reference value throughout the reference fundus area. That is, for each measurement value in the measurement value distribution, the evaluation unit 1100 identifies a position in the reference fundus area corresponding to the position of the measurement value, and compares the measurement value with the reference value at the identified corresponding position. If the fundus area to which the second OCT scan was applied truly includes the reference fundus area, the evaluation unit 1100 identifies a partial distribution having the first dimension (reference dimension) from the measurement value distribution in the fundus area corresponding to the second dimension, and compares each measurement value in the identified partial distribution with a reference value at a corresponding position in the reference value distribution. At least a portion of the fundus area to which the second OCT scan was applied and at least a portion of the reference fundus area overlap with each other, in which case the evaluation unit 1100 can compare the measurement value with the reference value at each position within the overlapping area. The number of reference value distributions 1014 stored in the storage unit 1013 may be one or two or more. An example will be described in which two or more reference value distributions 1014 are stored in the storage unit 1013. Although not shown in the drawings, the two or more reference value distributions 1014 will be referred to as first to Nth reference value distributions 1014(1) to 1014(N), where N is an integer of two or more. In some non-limiting examples, the N reference value distributions 1014(1) to 1014(N) correspond to multiple ranges of values ​​of a predetermined ocular parameter. For example, the N reference value distributions 1014(1) to 1014(N) correspond to multiple ranges of values ​​of an ocular parameter that affect the value of a fundus parameter determined by measurement analysis. If the ocular parameter determined by measurement analysis is retinal tissue thickness, N reference value distributions 1014(1) to 1014(N) corresponding to N intraocular distance ranges (N axial length ranges) can be created in advance and stored in the storage unit 1013. In this case, the N reference value distributions 1014(1) to 1014(N) are information indicating the distribution of reference values ​​in reference fundus areas with different reference dimensions. In other words, the N reference value distributions 1014(1) to 1014(N) correspond to different reference fundus areas. The relationship between the N reference value distributions 1014(1) to 1014(N) and the N reference dimensions (N reference fundus areas) is based on the relationship between the intraocular distance and the scan area described above. When the memory unit 1013 stores multiple reference value distributions 1014, the evaluation unit 1100 can select one or more reference value distributions from the multiple reference value distributions 1014 based on specified ocular parameters of the test eye, and evaluate the measurement value distribution based on the selected one or more reference value distributions. For example, if the storage unit 1013 stores N reference value distributions 1014(1) to 1014(N) corresponding to N intraocular distance ranges, the evaluation unit 1100 selects one or more reference value distributions from the N reference value distributions 1014(1) to 1014(N) based on the intraocular distance of the subject's eye calculated by the intraocular distance calculation unit 1050, and evaluates the measurement value distribution generated by the measurement analysis unit 1080 based on each selected reference value distribution. In this example, the ophthalmologic apparatus 1000D provides information indicated by the dashed line in FIG. 23 (provision of intraocular distance information from the intraocular distance calculation unit 1050 to the evaluation unit 1100). One specific aspect of this example is described below. The storage unit 1013 of this specific embodiment stores three reference value distributions 1014 corresponding to three axial length ranges: a normal axial length reference value distribution corresponding to the normal axial length range, a long axial length reference value distribution corresponding to the long axial length range, and a short axial length reference value distribution corresponding to the short axial length range. The evaluation unit 1100 determines to which range the intraocular distance (axial length) of the subject's eye calculated by the intraocular distance calculation unit 1050 belongs: the normal axial length range, the long axial length range, or the short axial length range. The evaluation unit 1100 selects a reference value distribution corresponding to the range to which the axial length of the subject's eye belongs from the normal axial length reference value distribution, the long axial length reference value distribution, and the short axial length reference value distribution. The evaluation unit 1100 evaluates the measurement value distribution generated by the measurement and analysis unit 1080 based on the selected reference value distribution. The flowchart in Fig. 24 shows an example of the operation of the ophthalmic apparatus 1000D of this example. A reference value distribution 1014 is stored in the storage unit 1013. In steps S121 to S125, the ophthalmic apparatus 1000D executes the same processes as steps S91 to S95 in Fig. 20. That is, the ophthalmic apparatus 1000D adjusts the optical path length of the scan unit 1020, stores the optical path length information, applies an OCT scan to the fundus of the subject's eye to generate an interference signal, constructs an OCT image of the fundus based on this interference signal, and calculates the intraocular distance of the subject's eye based on this OCT image. In step S126, the ophthalmologic apparatus 1000D determines a scan area using the scan area determination unit 1070 based on the intraocular distance of the subject's eye calculated in step S125 and the dimensions of the reference value distribution 1014 stored in the storage unit 1013. Information on the determined scan area is sent to the scan control unit 1011. Steps S127 to S129 respectively execute the same processes as steps S97 to S99 in Fig. 20. That is, the ophthalmologic apparatus 1000D applies an OCT scan to the fundus of the subject's eye based on the scan area determined in step S126 to generate an interference signal, constructs an OCT image of the fundus of the subject's eye based on this interference signal, and generates a measurement value distribution of the fundus of the subject's eye based on this OCT image. The generated measurement value distribution is provided to the evaluation unit 1100. In step S130, the ophthalmologic apparatus 1000D causes the evaluation unit 1100 to evaluate the measurement value distribution generated in step S129 based on the reference value distribution 1014. The ophthalmic apparatus 1000D has the same effects as the above-described ophthalmic apparatus 1000B. Furthermore, the ophthalmic apparatus 1000B can automatically evaluate the distribution of measurement values ​​of the fundus of the subject's eye, which contributes to further automation of examinations such as screening. An ophthalmic apparatus 2000 shown in Fig. 25 is one non-limiting example of the ophthalmic apparatus 1 according to Fig. 11 to Fig. 13. The ophthalmic apparatus 2000 of this example includes a control unit 2010, a scanning unit 2020, an image constructing unit 2030, a measurement and analysis unit 2040, an evaluation unit 2050, an alignment unit 2060, a front image acquiring unit 2070, and a scan dimension determining unit 2080. The control unit 2010 is configured to control each unit of the ophthalmologic apparatus 2000. The control unit 2010 may have the same configuration and functions as the control unit 1010 described above. The control unit 2010 includes a scan control unit 2011. The scan control unit 2011 is configured to control the scan unit 2020 to apply an OCT scan to the fundus of the subject's eye. The scan control unit 2011 may have the same configuration and function as the scan control unit 1011 described above. The control unit 2010 includes a storage unit 2012. The storage unit 2012 stores a reference value distribution 2013. The storage unit 2012 may have the same configuration and function as the storage unit 1013 described above. The reference value distribution 2013 is information indicating the distribution of reference values ​​in a fundus area (reference fundus area) having a predetermined dimension (first dimension, reference dimension). The reference value distribution 2013 may be information similar to the reference value distribution 1014 described above. The scanning unit 2020 is configured to perform an OCT scan on the fundus of the subject's eye. The OCT scan generates an interference signal. The scanning unit 2020 may have the same configuration and function as the scanning unit 1020 described above. The image construction unit 2030 is configured to generate an OCT image based on an interference signal generated by applying an OCT scan to the fundus of the subject's eye by the scan unit 2020. The image construction unit 2030 may have the same configuration and function as the image construction unit 1030 described above. The measurement and analysis unit 2040 is configured to apply measurement analysis to the OCT image to generate a distribution of measurement values ​​on the fundus of the subject's eye. The measurement and analysis unit 2040 may have the same configuration and functions as the measurement and analysis unit 1080 described above. The evaluation unit 2050 is configured to evaluate a measurement value distribution corresponding to a scan dimension determined by a scan dimension determination unit 2080 (described later) based on a reference value distribution 2013 stored in the storage unit 2012. The evaluation unit 2050 may have the same configuration and function as the evaluation unit 1100 described above. The alignment unit 2060 is configured to align the scan unit 2020 with the subject's eye. The alignment unit 2060 may have the same configuration and function as the alignment unit 1060 described above. The front image acquisition unit 2070 is configured to acquire a front image of the fundus of the subject's eye. The front image acquisition unit 2070 has either or both of a function to generate a front fundus image and a function to externally receive a front fundus image. When the front image acquisition unit 2070 has a function of generating a front fundus image, it includes a front imaging unit 2071. The front imaging unit 2071 generates a front image by imaging the subject's eye from the front. The front imaging unit 2071 may be capable of performing front imaging of the anterior segment and the fundus, as in the fundus camera unit 2 shown in FIGS. 11 and 13 , and may also be capable of performing video imaging. Any imaging modality may be applicable to the front imaging unit 2071, and may typically include at least one of a fundus camera and an SLO. If the front image acquisition unit 2070 does not have the function of generating a front fundus image, it has the function of externally receiving a front image of the fundus of the subject's eye. This front image receiving function may be implemented, for example, by at least one of a communication device configured to receive data via a communication line and a reading device configured to read data recorded on a recording medium. The communication device may be the communication interface (described above) of the arithmetic and control unit 200 in FIG. 11. The front image acquisition unit 2070 having the communication device acquires images stored in an external device (e.g., an image archiving system, an ophthalmic imaging device, a storage device, etc.) via the communication line. The reading device includes a recording medium gate (not shown) and the control unit 210 shown in FIGS. 11 and 13. The control unit 210 in this example functions as a gate controller that controls the recording medium gate. Furthermore, in some non-limiting examples where the function of generating a front fundus image is not provided, it is possible to employ a front image acquisition unit 2070 that does not include a front imaging unit 2071. However, in the case where the alignment unit 2060 is provided, the front image acquisition unit 2070 includes a front imaging unit 2071 configured to be able to generate at least a front moving image (anterior eye front moving image, fundus front moving image) used for alignment. The scan dimension determination unit 2080 is configured to determine the dimensions (scan dimensions) of the OCT scan to be applied to the fundus of the test eye based on the front image of the fundus of the test eye acquired by the front image acquisition unit 2070. The non-limiting example of the scan area determination unit 1070 described above can execute a process for determining the dimensions of the scan area (scan dimension determination process) and a process for determining the position of the scan area (scan position determination process). The scan dimension determination unit 2080 in this example executes an alternative process to the scan dimension determination process. The scan dimension determination unit 2080 may be configured to execute a similar scan position determination process. The scan dimension determination unit 2080 determines scan dimensions using a machine learning engine. The scan dimension determination unit 2080 has a trained model 2081. The trained model 2081 is created by machine learning. This machine learning may be performed using training data including a frontal fundus image and label data indicating scan dimensions. The trained model 2081 is configured to receive an input of a frontal fundus image of the subject's eye and output scan dimensions. The trained model 2081 is created by applying machine learning to a neural network, for example, a convolutional neural network (CNN). Any type of machine learning technique may be applied. Examples of such machine learning techniques include supervised learning, unsupervised learning, reinforcement learning, semi-supervised learning, transduction, multitask learning, active learning, decision tree learning, association rule learning, genetic programming, inductive logic programming, support vector machines, clustering, Bayesian networks, representation learning, and extreme learning machines. Techniques that can be used to construct the scan dimension determination unit 2080 include those described in the following documents. Richul Oh, Myeongkyun Kang, Jeeyun Ahn, et al., “Prediction of Axial Length From Macular Optical Coherence Tomography Using Deep Learning Model”, TVST | September 2024 | Vol. 13 | No. 9 | Article 14 | pp. 1-8 Li Dong1, Xin Yue Hu, Yan Ni Yan, et al., “Deep Learning-Based Estimation of Axial Length and Subfoveal Choroidal Thickness From Color Fundus Photographs”, Frontiers in Cell and Developmental Biology | April 2021 | Volume 9 | Article 653692 These documents propose a technique for estimating axial length from a frontal fundus image using a machine learning engine. As described above, there is a correspondence between the axial length and the dimensions of the scan area. A machine learning engine for estimating scan dimensions from a frontal fundus image can be constructed by combining a technique for estimating axial length from a frontal fundus image using a machine learning engine with a technique for estimating appropriate scan dimensions from the axial length. The scan dimension determination unit 2080 is an example of such a machine learning engine. The trained model 2081 of the scan dimension determination unit 2080 is created by machine learning using training data including a frontal fundus image and label data indicating scan dimensions that are directly or indirectly associated with each other. In some non-limiting examples, the scan dimension determination unit 2080 has a trained model 2081 created by machine learning using training data including a directly associated frontal fundus image and label data indicating scan dimensions. The trained model 2081 in this example receives an input of a frontal fundus image of the subject's eye and outputs scan dimension information. The scan dimension determination unit 2080 can output the scan dimension value output from the trained model 2081 as the final scan dimension. Alternatively, the scan dimension determination unit 2080 can output a corrected value obtained by correcting the scan dimension value output from the trained model 2081 as the final scan dimension. In contrast, in some other non-limiting examples, the scan dimension determination unit 2080 has a trained model 2081 created by machine learning using training data including an indirectly associated frontal fundus image and label data indicating scan dimensions. The trained model 2081 in this example includes, for example, a first trained model created by machine learning using training data including a frontal fundus image and label data indicating axial length, and a second trained model created by machine learning using training data including information on axial length and label data indicating scan dimensions. The processing performed by the scan dimension determination unit 2080 in this example includes a first step in which the first trained model receives an input of a frontal fundus image of the subject's eye and outputs information on the axial length, and a second step in which the second trained model receives an input of the axial length information output from the first step and outputs information on the scan dimensions. The scan dimension determination unit 2080 can output the scan dimension values ​​generated in the second step as final scan dimensions. Alternatively, the scan dimension determination unit 2080 can correct the scan dimension value generated in the second step and output the corrected value as the final scan dimension. In still other non-limiting examples, the trained model 2081 includes the first trained model described above. The scan dimension determination unit 2080 in this example first inputs a front image of the fundus of the subject's eye into the first trained model and obtains the output, which is information on the axial length. Next, the scan dimension determination unit 2080 in this example can substitute the value of the axial length obtained using the first trained model into a predetermined calculation formula and output the calculation result as the final scan dimension. 26 shows an example of the operation of the ophthalmic apparatus 2000 of this example. First, in step S141, the ophthalmic apparatus 2000 starts capturing moving images of the subject's eye using the front image capturing unit 2071. The front moving image generated by this moving image capturing is provided to the alignment unit 1060 and the scan dimension determination unit 2080. In step S142, the ophthalmologic apparatus 2000 aligns the scan unit 2020 with the subject's eye based on the front moving image using the alignment unit 1060. The alignment is performed in parallel with the generation of the front moving image. In step S143, the ophthalmologic apparatus 2000 causes the scan dimension determination unit 2080 to input frames of the front video image, which acquisition has started in the video capture started in step S141, to the trained model 2081. The input of the frames of the front video image to the trained model 2081 is performed in parallel with the generation and alignment of the front video image. In step S144, the ophthalmologic apparatus 2000 determines the scan dimensions using the scan dimension determination unit 2080 based on the output from the trained model 2081 corresponding to the input frame of the front moving image. Information on the determined scan dimensions is provided to the control unit 2010. After the alignment is completed, in step S145, the ophthalmologic apparatus 2000 applies an OCT scan to the fundus of the subject's eye using the scan unit 2020. More specifically, the scan control unit 2011 applies an OCT scan to the fundus of the subject's eye by controlling the scan unit 2020 based on the scan dimensions determined in step S144. An interference signal generated by the OCT scan is provided to the image construction unit 2030. In step S146, the ophthalmologic apparatus 2000 constructs an OCT image of the fundus of the subject's eye based on the interference signal generated in step S145 using the image constructing unit 2030. The constructed OCT image is provided to the measurement and analysis unit 2040. In step S147, the ophthalmologic apparatus 2000 generates a measurement value distribution of the fundus of the subject's eye by applying measurement analysis to the OCT image constructed in step S146 using the measurement analysis unit 2040. The generated measurement value distribution is provided to the evaluation unit 2050. In step S148, the ophthalmologic apparatus 2000 causes the evaluation unit 2050 to evaluate the measurement value distribution generated in step S147 based on the reference value distribution 2013. In step S144, the scan dimension determination unit 2080 can determine, as the scan dimension, a second dimension that is larger than the reference dimension (first dimension) of the reference value distribution 2013. In this case, in step S148, the evaluation unit 2050 can extract a partial distribution having the first dimension from the measurement value distribution corresponding to the second dimension and compare this partial distribution with the reference value distribution 2013, thereby evaluating the measurement value distribution. The ophthalmic apparatus 2000 can provide a novel method for determining the dimensions of the area to which the OCT scan is applied. Furthermore, since the ophthalmic apparatus 2000 can determine the scan dimensions while performing alignment, the examination time is not prolonged. Furthermore, since the ophthalmic apparatus 2000 can perform the OCT scan based on the determined scan dimensions, it is possible to easily and smoothly perform an OCT scan with an appropriate scan dimension for the subject's eye. In addition, since the ophthalmic apparatus 2000 can generate a measurement value distribution based on an OCT image obtained by an OCT scan in an appropriate scan area for the subject's eye, it is possible to obtain a high-quality measurement value distribution for the subject's eye. Furthermore, since the ophthalmic apparatus 2000 can automatically evaluate the measurement value distribution of the fundus of the subject's eye, it contributes to further automation of examinations such as screening. The ophthalmic apparatus 2000A shown in FIG. 27 is a non-limiting example of the ophthalmic apparatus 1. Similar to the ophthalmic apparatus 2000 of FIG. 25 , the ophthalmic apparatus 2000A of this example includes a control unit 2010, a scanning unit 2020, an image constructing unit 2030, a measurement / analysis unit 2040, an evaluation unit 2050, a front image acquisition unit 2070, and a scan dimension determination unit 2080. Unless otherwise specified, each of these elements has the same configuration and performs the same operation as the corresponding element of the ophthalmic apparatus 2000. In addition to these elements, the ophthalmic apparatus 2000A of this example includes an optical path length changing unit 2090 and an artifact determining unit 2100. The ophthalmic apparatus 2000A of this example may also include an alignment unit 2060 similar to that of the ophthalmic apparatus 2000. Although not shown, the scan dimension determination unit 2080 includes a trained model 2081. The control unit 2010 of this example further includes an optical path length control unit 2014 in addition to a scan control unit 2011 and a storage unit 2012 (reference value distribution 2013) similar to those of the ophthalmologic apparatus 2000. The optical path length changing unit 2090 is configured to change the optical path length of the scanning unit 2020. The optical path length changing unit 2090 may have the same configuration and function as the optical path length changing unit 1040 described above. The optical path length control unit 2014 is configured to control the optical path length changing unit 2090 to change the optical path length of the scanning unit 2020. The optical path length control unit 2014 may have the same configuration and function as the optical path length control unit 1012 described above. The artifact determining unit 2100 is configured to determine whether or not aliasing artifacts are included in the OCT image. The artifact determining unit 2100 may have the same configuration and function as the artifact determining unit 1090 described above. 28 shows an example of the operation of the ophthalmologic apparatus 2000A of this example. First, in step S151, the ophthalmologic apparatus 2000A acquires a front image of the fundus of the subject's eye by the front image acquisition unit 2030. The acquired front image is provided to the scan dimension determination unit 2080. In step S152, the ophthalmologic apparatus 2000A inputs the front image acquired in step S151 into the trained model 2081 via the scan dimension determination unit 2080. In step S153, the ophthalmologic apparatus 2000A determines the scan dimensions using the scan dimension determination unit 2080 based on the output from the trained model 2081 corresponding to the input of the front image. Information on the determined scan dimensions is provided to the control unit 2010. In step S154, the ophthalmologic apparatus 2000A applies an OCT scan (first OCT scan) to the fundus of the subject's eye by controlling the scan unit 2020 based on the scan dimensions determined in step S153 using the scan control unit 2011. A first interference signal generated by the first OCT scan is provided to the image construction unit 2030. In step S155, the ophthalmologic apparatus 2000A constructs an OCT image of the fundus of the subject's eye (first OCT image) based on the first interference signal generated in step S154 using the image constructing unit 2030. The constructed first OCT image is provided to the artifact determining unit 2100. In step S156, the ophthalmologic apparatus 2000A determines whether or not the first OCT image acquired in step S155 contains aliasing artifacts using the artifact determination unit 2100. If it is determined that the first OCT image contains aliasing artifacts (S157: YES), the procedure proceeds to step S158. On the other hand, if it is determined that the first OCT image does not contain aliasing artifacts (S157: NO), the procedure proceeds to step S161. In step S158, the ophthalmic apparatus 2000A controls the optical path length changing unit 2090 by the optical path length control unit 2014 to change the optical path length of the scanning unit 2020. The amount of change in the optical path length may be determined based on, for example, the dimensions of the aliasing artifact (particularly, the dimension in the depth direction). Alternatively, the ophthalmic apparatus 2000A may be configured to remove the aliasing artifact by changing the optical path length while checking the state of the aliasing artifact. After the change of the optical path length is completed, in step S159, the ophthalmologic apparatus 2000A applies an OCT scan (second OCT scan) to the fundus of the subject's eye by controlling the scan unit 2020 using the scan control unit 2011. The second OCT scan may be performed based on the scan dimensions determined in step S153. A second interference signal generated by the second OCT scan is provided to the image construction unit 2030. In step S160, the ophthalmologic apparatus 2000A constructs an OCT image of the fundus of the subject's eye (second OCT image) based on the second interference signal generated in step S159 using the image constructing unit 2030. The constructed second OCT image is provided to the measurement and analysis unit 2040. If it is determined in step S157 that aliasing artifacts are present, in step S161, the ophthalmologic apparatus 2000A generates a measurement value distribution at the fundus of the subject's eye by applying measurement analysis to the second OCT image constructed in step S160 using the measurement analysis unit 2040. The generated measurement value distribution is provided to the evaluation unit 2050. In other words, when the second OCT scan is performed, the measurement analysis unit 2040 applies the measurement analysis to the second OCT image without applying the measurement analysis to the first OCT image. On the other hand, if it is determined in step S157 that there are no aliasing artifacts, in step S161, the ophthalmologic apparatus 2000A generates a measurement value distribution at the fundus of the subject's eye by applying measurement analysis to the first OCT image constructed in step S155 using the measurement analysis unit 2040. In other words, if a first OCT image without aliasing artifacts is obtained, the process proceeds to measurement analysis without performing a second OCT scan. In step S162, the ophthalmologic apparatus 2000A causes the evaluation unit 2050 to evaluate the measurement value distribution generated in step S161 based on the reference value distribution 2013. The ophthalmic apparatus 2000A has the same effects as the above-described ophthalmic apparatus 2000. Furthermore, the ophthalmic apparatus 2000A enables measurement analysis and evaluation using high-quality OCT images free of aliasing artifacts. Another advantage is that aliasing artifacts can be automatically removed. The ophthalmic apparatus 2000B shown in FIG. 29 is one non-limiting example of the ophthalmic apparatus 1. Similar to the ophthalmic apparatus 2000 of FIG. 25 , the ophthalmic apparatus 2000B of this example includes a control unit 2010, a scanning unit 2020, an image constructing unit 2030, a measurement / analysis unit 2040, an evaluation unit 2050, a front image acquiring unit 2070, and a scan dimension determining unit 2080. Unless otherwise specified, each of these elements has the same configuration and performs the same operation as the corresponding element of the ophthalmic apparatus 2000. In addition to these elements, the ophthalmic apparatus 2000B of this example includes an intraocular distance acquiring unit 2110. The ophthalmic apparatus 2000B of this example may also include an alignment unit 2060 similar to that of the ophthalmic apparatus 2000. Although not shown, the scan dimension determining unit 2080 includes a trained model 2081. The control unit 2010 of this example has a scan control unit 2011 and a storage unit 2012 similar to those of the ophthalmologic apparatus 2000. However, the storage unit 2012 of this example stores a plurality (N) of reference value distributions 2013. The N reference value distributions 2013 may be similar to the N reference value distributions 1014 described above. The N reference value distributions 2013 are referred to as first to Nth reference value distributions 2013(1) to 2013(N). Here, N is an integer of 2 or greater. The intraocular distance acquisition unit 2110 acquires intraocular distance information indicating the intraocular distance of the subject's eye. Any method may be used to acquire the intraocular distance information. The intraocular distance acquisition unit 2110 may generate intraocular distance data by applying intraocular distance measurement (e.g., axial length measurement) to the subject's eye, or may receive separately measured intraocular distance data of the subject's eye from an external source. The generation of intraocular distance data may include, for example, the calculation performed by the intraocular distance calculation unit 1050 described above. In FIG. 29 , the dashed arrow from the image construction unit 2030 to the intraocular distance acquisition unit 2110 indicates the flow of data (OCT images) when calculating the intraocular distance based on OCT images. The flowchart in Fig. 30 shows an example of the operation of the ophthalmic apparatus 2000B of this example. In steps S171 to S175, the ophthalmic apparatus 2000B executes processes similar to steps S151 to S155 in Fig. 28. That is, the ophthalmic apparatus 2000B acquires a front image of the fundus of the subject's eye, inputs this front image to the trained model 2081, determines scan dimensions based on the output from the trained model 2081, applies an OCT scan to the fundus of the subject's eye based on this scan dimension to generate an interference signal, and constructs an OCT image of the fundus based on this interference signal. In step S176, the ophthalmologic apparatus 2000B calculates the intraocular distance of the subject's eye based on at least the OCT image constructed in step S175 using the intraocular distance acquisition unit 2110. The acquired intraocular distance information is provided to the evaluation unit 2050. In step S177, the ophthalmologic apparatus 2000B selects, by the evaluation unit 2050, one or more reference value distributions from among the N reference value distributions 2013(1) to 2013(N) based on the intraocular distance information acquired in step S176. In step S178, the ophthalmologic apparatus 2000B generates a measurement value distribution by applying measurement analysis to the OCT image constructed in step S175 using the measurement analysis unit 2040. The generated measurement value distribution is provided to the evaluation unit 2050. In step S179, the ophthalmologic apparatus 2000B causes the evaluation unit 2050 to evaluate the measurement value distribution generated in step S178 based on the reference value distribution selected in step S177. Such an ophthalmic apparatus 2000B has the same effects as the above-described ophthalmic apparatus 2000. Furthermore, the ophthalmic apparatus 2000B can perform high-quality evaluation by selectively using a reference value distribution according to the intraocular distance of the subject's eye. An ophthalmic apparatus 3000 shown in Fig. 31 is one non-limiting example of the ophthalmic apparatus 1 according to Fig. 11 to Fig. 13. The ophthalmic apparatus 3000 of this example includes a control unit 3010, a scanning unit 3020, an image constructing unit 3030, an optical path length changing unit 3040, an intraocular distance calculating unit 3050, an intraocular distance comparing unit 3060, a scan area determining unit 3070, a measurement and analyzing unit 3080, and an evaluating unit 3090. The control unit 3010 is configured to control each unit of the ophthalmologic apparatus 3000. The control unit 3010 may have the same configuration and functions as the control unit 1010 described above. The control unit 3010 includes a scan control unit 3011. The scan control unit 3011 is configured to control the scan unit 3020 to apply an OCT scan to the fundus of the subject's eye. The scan control unit 3011 may have the same configuration and function as the scan control unit 1011 described above. The control unit 3010 includes an optical path length control unit 3012. The optical path length control unit 3012 is configured to control the optical path length changing unit 3040 to change the optical path length of the scanning unit 3020. The optical path length control unit 3012 may have the same configuration and function as the optical path length control unit 1012 described above. The control unit 3010 includes a storage unit 3013. The storage unit 3013 stores a reference value distribution 3014. The storage unit 3013 may have the same configuration and function as the storage unit 1013 described above. The reference value distribution 3014 is information indicating the distribution of reference values ​​in a fundus area (reference fundus area) having a predetermined dimension (first dimension, reference dimension). The reference value distribution 3014 may be information similar to the reference value distribution 1014 described above. The scanning unit 3020 is configured to perform an OCT scan on the fundus of the subject's eye. The OCT scan generates an interference signal. The scanning unit 3020 may have the same configuration and function as the scanning unit 1020 described above. The image construction unit 3030 is configured to generate an OCT image based on an interference signal generated by applying an OCT scan to the fundus of the subject's eye by the scan unit 3020. The image construction unit 3030 may have the same configuration and function as the image construction unit 1030 described above. The scan unit 3020 and the image construction unit 3030 provide non-limiting examples of data acquisition units that acquire data of the subject's eye used to calculate the intraocular distance. The optical path length changing unit 3040 is configured to change the optical path length of the scanning unit 3020. The optical path length changing unit 3040 may have the same configuration and function as the optical path length changing unit 1040 described above. The intraocular distance calculation unit 3050 is configured to calculate the intraocular distance of the subject's eye based at least on data previously acquired from the subject's eye. The intraocular distance calculation unit 3050 may have the same configuration and function as the above-mentioned intraocular distance calculation unit 1050. The intraocular distance comparison unit 3060 compares the value of the intraocular distance of the subject's eye calculated by the intraocular distance calculation unit 3050 with a threshold value. The threshold value is determined in advance. In a non-limiting example, the threshold value is a boundary value between the normal axial length range and the long axial length range. The intraocular distance comparison unit 3060 of this example acts to determine whether the axial length of the subject's eye is within or exceeds the normal range. The function of the intraocular distance comparison unit 3060 is realized by cooperation between hardware including a circuit and intraocular distance comparison software. The form of the threshold value is not limited to the above example. Furthermore, the configuration and operation of the intraocular distance comparison unit 3060 are not limited to the above example. The scan area determiner 3070 is configured to calculate the intraocular distance of the subject's eye based at least on the intraocular distance of the subject's eye calculated by the intraocular distance calculator 3050. In some non-limiting examples, the scan area determiner 3070 may be configured to calculate the intraocular distance of the subject's eye based on the dimensions (reference dimensions, first dimensions) of the fundus area (reference fundus area) where the reference value distribution 3014 is defined and the intraocular distance of the subject's eye, as described above. In this example, the scan area determiner 3070 can determine a scan area having a second dimension greater than the first dimension, as described above. The scan area determiner 3070 may have the same configuration and function as the scan area determiner 1070 described above. The measurement and analysis unit 3080 is configured to apply measurement analysis to the OCT image to generate a distribution of measurement values ​​on the fundus of the subject's eye. The measurement and analysis unit 3080 may have the same configuration and functions as the measurement and analysis unit 1080 described above. The evaluation unit 3090 is configured to evaluate the measurement value distribution corresponding to the scan area determined by the scan area determination unit 3070, based on the reference value distribution 3014 stored in the storage unit 3013. The evaluation unit 3090 may have the same configuration and function as the evaluation unit 1100 described above. 32 shows an example of the operation of the ophthalmologic apparatus 3000 of this example. First, in step S181, the ophthalmologic apparatus 3000 applies an OCT scan to the fundus of the subject's eye using the scan unit 3020. This OCT scan is a preliminary OCT scan performed to estimate the intraocular distance of the subject's eye before an OCT scan for measurement analysis. An interference signal generated by this preliminary OCT scan is provided to the image construction unit 3030. In this operation example, a preliminary OCT scan is performed by the ophthalmic apparatus 3000. However, in some non-limiting examples, the ophthalmic apparatus 3000 may be configured to externally acquire data of the subject's eye that has been acquired in advance, and to calculate the intraocular distance based on the data using the intraocular distance calculation unit 3050. In step S182, the ophthalmologic apparatus 3000 constructs an OCT image of the fundus of the subject's eye using the image constructing unit 3030 based on the interference signal obtained in the preliminary OCT scan in step S181. This OCT image is called a preliminary OCT image. The preliminary OCT image is provided to the intraocular distance calculating unit 3050. In step S183, the ophthalmologic apparatus 3000 calculates the intraocular distance of the subject's eye based on at least the preliminary OCT image acquired in step S182 using the intraocular distance calculation unit 3050. Information on the calculated intraocular distance is provided to the intraocular distance comparison unit 3060 and the scan area determination unit 3070. In some non-limiting examples, the ophthalmic apparatus 3000 provides the intraocular distance calculation unit 3050 with optical path length information indicating the optical path length of the scan unit 3020 when the preliminary OCT scan is applied to the fundus of the test eye in step S181. The optical path length information in this example may be information similar to the optical path length information described above. The intraocular distance calculation unit 3050 in this example can calculate the intraocular distance of the test eye based at least on the preliminary OCT image and the optical path length information. In some non-limiting examples, the intraocular distance calculation unit 3050 analyzes the preliminary OCT image acquired in step S182 to identify a region image corresponding to a predetermined region of the fundus of the subject's eye. Furthermore, the intraocular distance calculation unit 3050 can calculate the intraocular distance of the subject's eye based at least on the position of the region image in the preliminary OCT image and the optical path length information. Here, a non-limiting example of the region image may be an internal limiting membrane image. Another non-limiting example of the position of the region image used to calculate the intraocular distance may be the average depth position of the internal limiting membrane image. In step S184, the ophthalmologic apparatus 3000 compares the intraocular distance calculated in step S183 with a threshold value using the intraocular distance comparison unit 3060. If it is determined that the intraocular distance is greater than the threshold value (S185: Yes), the procedure proceeds to step S186. On the other hand, if it is determined that the intraocular distance is equal to or less than the threshold value (S185: No), the procedure proceeds to step S187. In step S186 , the ophthalmologic apparatus 3000 controls the optical path length changing unit 3040 by the optical path length control unit 3012 to change the optical path length of the scanning unit 3020 . The process of step S186 is executed as an alternative to step S107 in Fig. 22. In step S107, the optical path length is changed based on information obtained by actually detecting aliasing artifacts (presence or absence and state of aliasing artifacts). In contrast, in step S186, the possibility of the occurrence of aliasing artifacts is evaluated based on the magnitude of the value of the intraocular distance of the subject's eye without detecting aliasing artifacts, and the optical path length of the scan unit 3020 is changed if the possibility is high (for example, if the axial length of the subject's eye exceeds the normal axial length range). In step S186, the optical path length control unit 3012 can determine the amount of change in the optical path length based on the difference between the intraocular distance of the subject's eye and a threshold (for example, the difference value obtained by dividing the intraocular distance by the threshold). After changing the optical path length, the procedure proceeds to step S187. In step S187, the ophthalmologic apparatus 3000 determines a scan area based on the intraocular distance of the subject's eye calculated in step S183 using the scan area determination unit 3070. Information on the determined scan area is provided to the control unit 3010. In step S188, the ophthalmologic apparatus 3000 controls the scanning unit 3020 based on the scan area determined in step S187 using the scan control unit 3011. Under the control of the scan control unit 3011, the scanning unit 3020 applies an OCT scan to the fundus of the subject's eye to generate an interference signal. In step S189, the ophthalmologic apparatus 3000 constructs an OCT image of the fundus of the subject's eye based on the interference signal generated in step S188 using the image constructing unit 3030. The acquired OCT image is provided to the measurement and analysis unit 3080. In this example, both the first image construction unit that performs the image construction in step S182 and the second image construction unit that performs the image construction in step S189 are performed by the same image construction unit 3030. In contrast, in some non-limiting examples, the first image construction unit and the second image construction unit may be separate elements. In step S190, the ophthalmologic apparatus 3000 applies measurement analysis to the OCT image obtained in step S189 using the measurement analysis unit 3080 to generate a measurement value distribution at the fundus of the subject's eye. The obtained measurement value distribution is provided to the evaluation unit 3090. In step S191, the ophthalmologic apparatus 3000 causes the evaluation unit 3090 to evaluate the measurement value distribution acquired in step S190 based on the reference value distribution 3014 stored in the storage unit 3013. The ophthalmic apparatus 3000 can provide a novel method for controlling an OCT scan. More specifically, the ophthalmic apparatus 3000 can perform an OCT scan by changing the optical path length of the scan unit 3020 based on the magnitude of the intraocular distance of the subject's eye, without actually performing a process for detecting aliasing artifacts. This OCT scan control contributes to speeding up and facilitating examinations such as screening. In some non-limiting examples, the storage unit 3013 of the ophthalmologic apparatus 3000 may store a plurality of reference value distributions 3014. Furthermore, the evaluation unit 3090 may be configured to select one or more reference value distributions from the plurality of reference value distributions 3014 based on the intraocular distance of the subject's eye calculated by the intraocular distance calculation unit 3050, and to evaluate the measurement value distribution based on the selected reference value distribution. This can improve the quality of the evaluation. An ophthalmic apparatus 4000 shown in Fig. 33 is one non-limiting example of the ophthalmic apparatus 1 according to Figs. 11 to 13. The ophthalmic apparatus 4000 of this example is used in the preparation step of Fig. 2. The preparation step is a step of preparing information (e.g., a reference database) to be used as an evaluation criterion for ophthalmic examination data. The ophthalmic apparatus 4000 includes a control unit 4010, an interface unit 4020, an information acquisition unit 4030, and an information generation unit 4040. The ophthalmic apparatus 4000 may or may not have a function for performing imaging operations such as OCT scans. When the ophthalmic apparatus 4000 does not have an imaging function, it is an ophthalmic information processing apparatus. The processor 320 in FIG. 3 provides a non-limiting example of this ophthalmic information processing apparatus. The arithmetic control unit 200 (and the display device 3) in FIG. 11 also provides a non-limiting example of this ophthalmic information processing apparatus. The control unit 210 and data processing unit 230 (and the image construction unit 220) in FIG. 13 also provide a non-limiting example of this ophthalmic information processing apparatus. The ophthalmic device 4000 is configured to generate evaluation reference information of a predetermined measurement index related to the subject's eye. The measurement index (metric) is any type of index derived from data acquired by applying an OCT scan to the subject's eye, and is used to understand and evaluate the condition of the subject's eye. A non-limiting example of the measurement index is the retinal tissue thickness described above. The evaluation reference information generated by the ophthalmic device 4000 is any type of information referenced as a standard in the evaluation of the subject's eye. A non-limiting example of the evaluation reference information is the reference database described above. The control unit 4010 is configured to control each unit of the ophthalmologic apparatus 4000. The control unit 4010 is realized by cooperation between hardware including circuits and control software. The processor 320 in FIG. 3 provides a non-limiting example of the control unit 4010. The control unit 210 in FIG. 13 also provides a non-limiting example of the control unit 4010. A processor of a computer (information processing device) (not shown) also provides a non-limiting example of the control unit 4010. The interface unit 4020 may include a communication device or a reading device for exchanging data with an external device. The interface unit 4020 may also include a user interface (man-machine interface) for exchanging information between users. The display device 3 in FIG. 11 provides a non-limiting example of this user interface. The user interface 240 in FIG. 13 also provides a non-limiting example of this user interface. The information acquisition unit 4030 acquires evaluation criterion information (first evaluation criterion information) indicating the relationship between the value of the intraocular distance and the value of the measurement index within a predetermined range (first range). Here, the intraocular distance may be, for example, the axial length or the vitreous cavity depth. An example of the first evaluation criterion information is the aforementioned original reference database. The arithmetic and control unit 200 in FIG. 11 and the control unit 210 in FIG. 13 provide non-limiting examples of the information acquisition unit 4030. In some non-limiting examples, the information acquisition unit 4030 may be configured to generate the first evaluation criterion information by performing a process according to any of the methods described above. Also, in some non-limiting examples, the information acquisition unit 4030 may be configured to receive the already created first evaluation criterion information using a communication device or a reading device. In some non-limiting examples, the first evaluation criterion information acquired by the information acquisition unit 4030 may include real-world data. As described above, real-world data is data collected without limiting the attributes of samples. The real-world data included in the first evaluation criterion information in this example is data (dataset) showing the relationship between the intraocular distance value and the measurement index value in a heterogeneous population. In some non-limiting examples, the first evaluation reference information acquired by the information acquisition unit 4030 may include normal eye data (normal eye database). As described above, the normal eye data is data collected using normal eyes as samples. The normal eye data included in the first evaluation reference information in this example is data (dataset) showing the relationship between the intraocular distance value and the measurement index value in a population of normal eyes. The information generation unit 4040 is configured to generate second evaluation criterion information indicating the relationship between the value of the intraocular distance and the value of the measurement index in a second range different from the definition range (first range) of the first evaluation criterion information by applying regression analysis to at least the first evaluation criterion information. The second range, which is the definition range of the second evaluation criterion information generated by the information generating unit 4040, may be an arbitrarily set range. In some non-limiting examples, the second range may be a range that properly includes the first range. That is, the definition range of the first evaluation criterion information may be a proper subset of the definition range of the second evaluation criterion information. In some non-limiting examples, the second range may be a range that partially overlaps with the first range. That is, a portion of the definition range of the second evaluation criterion information may overlap with the first evaluation criterion information. In some non-limiting examples, the second range may be a range that does not overlap with the first range. That is, the definition range of the first evaluation criterion information and the definition range of the second evaluation criterion information may not have a common portion. If the definition range of the second evaluation criterion information truly includes the definition range of the first evaluation criterion information, the information generating unit 4040 executes the process shown in Figures 8 and 9, i.e., the process of generating an extended reference database from the original reference database. Those skilled in the art will understand that similar regression analysis can be applied in other cases as well. The regression analysis performed by the information generating unit 4040 may include extrapolation. In this case, the information generating unit 4040 calculates an estimated value of the measurement index for the value of the intraocular distance in a range outside the first range by applying extrapolation to at least the first evaluation criterion information. This extrapolation may be performed as described above. Furthermore, the information generating unit 4040 can generate second evaluation criterion information using the estimated value of the measurement index obtained by the extrapolation. For example, the information generating unit 4040 can generate second evaluation criterion information as an extended reference database using the first evaluation criterion information as the original reference database by combining the estimated value obtained by the extrapolation with the first evaluation criterion information. In this case, the definition range of the second evaluation criterion information is wider than the definition range of the first evaluation criterion information. Furthermore, the information generating unit 4040 can generate second evaluation criterion information having a definition range that does not overlap with the definition range of the first evaluation criterion information using the estimated value obtained by the extrapolation. 34 shows an example of the operation of the ophthalmic apparatus 4000 of this example. First, in step S201, the ophthalmic apparatus 4000 acquires evaluation criterion information (first evaluation criterion information) defined in a predetermined intraocular distance range (first range) using the information acquisition unit 4030. The acquired first evaluation criterion information is provided to the information generation unit 4040. In step S202, the ophthalmic device 4000 uses the information generation unit 4040 to apply extrapolation to the first evaluation criterion information acquired in step S201 to estimate a measurement index value for an intraocular distance value that falls outside the intraocular distance range of the first evaluation criterion information. In step S203, the ophthalmologic apparatus 4000 generates extended evaluation criterion information defined over an extended range obtained by extending the intraocular distance range of the first evaluation criterion information by combining the estimated value of the measurement index obtained in step S202 with the first evaluation criterion information acquired in step S201, using the information generation unit 4040. This results in an extended reference database that uses the first evaluation criterion information as the original reference database. The ophthalmologic apparatus 4000 can provide a novel method for generating evaluation criteria for a subject's eye. This novel method is advantageous in that it can be executed automatically and that the definition range can be changed (especially, the definition range can be expanded). Furthermore, by using real-world data, it is possible to generate evaluation criteria information useful for screening and the like. Furthermore, by using normal eye data, it is possible to generate evaluation criteria information useful for definitive diagnosis and the like. An ophthalmic apparatus 5000 shown in Fig. 35 is one non-limiting example of the ophthalmic apparatus 1 according to Fig. 11 to Fig. 13. The ophthalmic apparatus 5000 of this example is used in the photographing step, analysis step, and evaluation step of Fig. 2. The ophthalmic apparatus 5000 includes a control unit 5010, an image acquisition unit 5020, a measurement / analysis unit 5030, and an evaluation unit 5040. The control unit 5010 is configured to control each unit of the ophthalmic apparatus 5000. The control unit 5010 is realized by cooperation between hardware including circuits and control software. The processor 320 in FIG. 3 provides a non-limiting example of the control unit 5010. The control unit 210 in FIG. 13 also provides a non-limiting example of the control unit 5010. The control unit 5010 includes a storage unit 5011. The storage unit 5011 stores evaluation criterion information 5012. The evaluation criterion information 5012 is generated by, for example, the ophthalmic apparatus 4000 shown in Figs. 33 and 34 and provided to the ophthalmic apparatus 5000 of this example. The image acquisition unit 5020 is configured to acquire an OCT image of the fundus of the subject's eye. In some non-limiting examples, the image acquisition unit 5020 includes a scan unit that applies an OCT scan to the fundus of the subject's eye and an image construction unit that constructs an OCT image based on data (interference signals) generated by the scan unit. In some non-limiting examples, the image acquisition unit 5020 includes an interface that externally receives data obtained by applying an OCT scan to the fundus of the subject's eye, and an image construction unit that constructs an OCT image based on this data. In some non-limiting examples, the image acquisition unit 5020 includes an interface that externally receives an OCT image of the fundus of the subject's eye. The image acquisition unit 5020 is realized by the ophthalmologic apparatus described above. The measurement analysis unit 5030 calculates measurement values ​​of the measurement indexes by applying measurement analysis to the OCT image of the fundus of the subject's eye acquired by the image acquisition unit 5020. For example, the measurement analysis unit 5030 generates a retinal tissue thickness distribution in the fundus of the subject's eye by applying layer thickness analysis to the OCT image of the fundus of the subject's eye. The measurement and analysis unit 5030 is realized by cooperation between hardware including circuits and measurement and analysis software. The processor 320 in Fig. 3 provides a non-limiting example of the measurement and analysis unit 5030. The data processing unit 230 in Fig. 13 also provides a non-limiting example of the measurement and analysis unit 5030. The evaluation unit 5040 evaluates the measurement values ​​of the measurement indexes generated by the measurement and analysis unit 5030 based on the evaluation reference information 5012 stored in the storage unit 5011. For example, the evaluation unit 5040 evaluates the retinal tissue thickness distribution at the fundus of the subject's eye generated by the measurement and analysis unit 5030 based on the reference value distribution as the evaluation reference information 5012. The evaluation unit 5040 is realized by cooperation of hardware including a circuit and evaluation software. The processor 320 in Fig. 3 provides a non-limiting example of the evaluation unit 5040. Also, the data processing unit 230 in Fig. 13 provides a non-limiting example of the evaluation unit 5040. The ophthalmic apparatus 5000 configured in this manner can perform operations similar to those of some of the above-described ophthalmic apparatuses. For example, the ophthalmic apparatus 5000 can perform at least a part of the operations of the ophthalmic apparatus 1000D in Fig. 23 , at least a part of the operations of the ophthalmic apparatus 2000 in Fig. 25 , at least a part of the operations of the ophthalmic apparatus 2000A in Fig. 27 , at least a part of the operations of the ophthalmic apparatus 2000B in Fig. 29 , and at least a part of the operations of the ophthalmic apparatus 3000 in Fig. 31 . Although several embodiments according to the present disclosure have been described above with reference to the drawings, these are non-limiting examples, and various configurations other than those described above may also be adopted. In addition, in the flowcharts used in the above description, multiple steps (processes) are described in order. However, the order of the steps performed in each embodiment is not limited to the order described. In each embodiment, the order of the steps shown in the drawings can be changed to the extent that the content is not affected. Furthermore, the above embodiments can be at least partially combined to the extent that the content is not contradictory. Some or all of the above embodiments can be described as follows: However, the embodiments according to the present disclosure are not limited to the following supplementary notes. [1] a scanning unit that applies a first optical coherence tomography scan to a fundus of a subject's eye to generate a first interference signal; an image constructing unit that constructs a first optical coherence tomography image based on the first interference signal; an optical path length changing unit that changes the optical path length of the scanning unit; an intraocular distance calculation unit that calculates an intraocular distance based on at least the first optical coherence tomography image and optical path length information indicating the optical path length when the first optical coherence tomography scan is applied to the fundus; An ophthalmic device comprising: [2] The intraocular distance calculation unit analyzing the first optical coherence tomography image to identify a site image corresponding to a predetermined site of the fundus of the subject's eye; calculating the intraocular distance based at least on a position of the region image in the first optical coherence tomography image and the optical path length information; The ophthalmic device according to item 1 above. [3] The intraocular distance calculation unit calculates the intraocular distance as an air-equivalent value. 1 or 2. An ophthalmic device according to 1 or 2 above. [4] An alignment unit that aligns the scan unit with the subject's eye, the intraocular distance calculation unit calculates the intraocular distance based on at least the first optical coherence tomography image based on the first interference signal generated after the alignment is completed and the optical path length information; Any one of the ophthalmic devices 1 to 3 above. [5] The intraocular distance calculation unit calculates the intraocular distance based on at least the first optical coherence tomography image based on the first interference signal generated after the alignment is completed, the optical path length information, and dimension information indicating dimensions of a predetermined portion of the subject's eye that has been acquired in advance. The ophthalmic devices listed above. [6] a scan area determination unit that determines a scan area based on the intraocular distance; a scan control unit that controls the scan unit based on the scan area; Further provided with the scanning unit applies a second optical coherence tomography scan to the fundus of the subject's eye under the control of the scan control unit to generate a second interference signal; the image constructing unit constructs a second optical coherence tomography image based on the second interference signal. Any one of the ophthalmic devices 1 to 5 above. [7] an artifact determination unit that determines whether the first optical coherence tomography image contains aliasing artifacts; an optical path length control unit that controls the optical path length changing unit to change the optical path length when the artifact determining unit determines that the aliasing artifact is included; Further provided with After the optical path length is changed by the optical path length changing unit under the control of the optical path length control unit, the scan control unit causes the scanning unit to perform the second optical coherence tomography scan. The ophthalmic devices listed above. [8] The apparatus further includes a measurement analysis unit that applies measurement analysis to the second optical coherence tomography image to generate a measurement value distribution at the fundus of the subject's eye. 8. The ophthalmic device according to claim 6 or 7. [9] Further comprising a storage unit that stores a reference value distribution indicating a distribution of the reference value in a fundus area of ​​a first dimension; the scan area determination unit determines the scan area based on the intraocular distance and the first dimension; an evaluation unit that evaluates the measurement value distribution corresponding to the scan area based on the reference value distribution; The ophthalmic devices listed above.

[10] The scan area determination unit determines the scan area having a second dimension larger than the first dimension; the evaluation unit compares a partial distribution having the first dimension in the measurement value distribution corresponding to the second dimension with the reference value distribution having the first dimension; The ophthalmic devices listed above.

[11] The storage unit stores a plurality of the reference value distributions, The evaluation unit selecting one or more reference value distributions from the plurality of reference value distributions based on the intraocular distance; evaluating the distribution of measured values ​​based on the one or more reference distributions; 11. The ophthalmic device according to claim 9 or 10.

[12] A scanning unit that applies an optical coherence tomography scan to the fundus of the subject's eye; a front image acquisition unit for acquiring a front image of the fundus of the subject's eye; a scan dimension determination unit that has a trained model that receives an input of a front image of the fundus and outputs scan dimensions, the trained model being created by machine learning using training data including a front image of the fundus and label data indicating scan dimensions, and that determines scan dimensions based on an output from the trained model corresponding to the input of the front image acquired by the front image acquisition unit; a scan control unit that controls the scan unit based on the scan dimension determined by the scan dimension determination unit to apply a first optical coherence tomography scan to the fundus of the subject's eye; An ophthalmic device comprising:

[13] The front image acquisition unit includes a front photographing unit that photographs the subject's eye from the front and generates a front moving image, an alignment unit that aligns the scan unit with the subject's eye based on the front moving image in parallel with the generation of the front moving image by the front photographing unit, the scan dimension determination unit determines the scan dimensions based on an output from the trained model corresponding to an input frame of the front video sequence, in parallel with the generation of the front video sequence and the alignment; the scan control unit causes the scan unit to perform the first optical coherence tomography scan after the alignment is completed; The above 12 ophthalmic devices.

[14] The scanning unit generates a first interference signal by the first optical coherence tomography scan; an image constructor that generates a first optical coherence tomography image based on the first interference signal; a measurement analysis unit that applies measurement analysis to the first optical coherence tomography image to generate a measurement value distribution on the fundus of the subject's eye; Further comprising: 14. The ophthalmic device according to claim 12 or 13.

[15] an optical path length changing unit that changes the optical path length of the scanning unit; an artifact determination unit that determines whether the first optical coherence tomography image includes an aliasing artifact; an optical path length control unit that controls the optical path length changing unit to change the optical path length when the artifact determining unit determines that the aliasing artifact is included; Further provided with After the optical path length is changed by the optical path length changing unit under the control of the optical path length control unit, the scan control unit controls the scan unit to apply a second optical coherence tomography scan to the fundus of the subject's eye. 14 ophthalmic devices listed above.

[16] The scanning unit generates a second interference signal by the second optical coherence tomography scan; the image constructing unit generates a second optical coherence tomography image based on the second interference signal; the measurement and analysis unit applies the measurement and analysis to the second optical coherence tomography image. The above 15 ophthalmic devices.

[17] When the second optical coherence tomography scan is performed, the measurement and analysis unit applies the measurement and analysis to the second optical coherence tomography image without applying the measurement and analysis to the first optical coherence tomography image. 16 ophthalmic devices as mentioned above.

[18] Further comprising a storage unit that stores a reference value distribution indicating a distribution of the reference value in a fundus area of ​​a first dimension; the scan dimension determination unit determines the scan dimension based on the output from the trained model and the first dimension; the measurement analysis unit generates the measurement value distribution corresponding to the scan dimension determined based on the first dimension; an evaluation unit that evaluates the measurement value distribution corresponding to the scan dimension based on the reference value distribution; 18. Any one of the ophthalmic devices described in 14 to 17 above.

[19] The scan dimension determination unit determines a second dimension larger than the first dimension as the scan dimension; the evaluation unit compares a partial distribution having the first dimension in the measurement value distribution corresponding to the second dimension with the reference value distribution having the first dimension; 18 ophthalmic devices as mentioned above.

[20] An intraocular distance acquisition unit that acquires intraocular distance information indicating the intraocular distance of the subject's eye, the storage unit stores a plurality of the reference value distributions; The evaluation unit selecting one or more reference value distributions from the plurality of reference value distributions based on the intraocular distance; evaluating the distribution of measured values ​​based on the one or more reference distributions; 19. The ophthalmic device according to claim 18 or 19.

[21] A scanning unit that applies an optical coherence tomography scan to the fundus of the subject's eye; an optical path length changing unit that changes the optical path length of the scanning unit; an intraocular distance calculation unit that calculates an intraocular distance based on data previously acquired from the subject's eye; an intraocular distance comparison unit that compares the intraocular distance with a predetermined threshold; an optical path length control unit that controls the optical path length changing unit to change the optical path length when the intraocular distance comparing unit determines that the intraocular distance is greater than the threshold value; a scan control unit that controls the scanning unit to apply an optical coherence tomography scan to the fundus of the subject's eye after the optical path length is changed by the optical path length changing unit under the control of the optical path length control unit; An ophthalmic device comprising:

[22] Further comprising a data acquisition unit that acquires the data of the subject's eye. The 21 ophthalmic devices mentioned above.

[23] The data acquisition unit: the scanning unit applying a preliminary optical coherence tomography scan to the fundus of the subject's eye to generate a preliminary interference signal; a first image constructing unit that constructs a preliminary optical coherence tomography image based on the preliminary interference signal; Including, the data of the subject's eye includes the preliminary optical coherence tomography image. The 22 ophthalmic devices mentioned above.

[24] The intraocular distance calculation unit calculates the intraocular distance based at least on the preliminary optical coherence tomography image and optical path length information indicating the optical path length when the preliminary optical coherence tomography scan is applied to the fundus. 23 ophthalmic devices listed above.

[25] The intraocular distance calculation unit analyzing the preliminary optical coherence tomography image to identify a region image corresponding to a predetermined region of the fundus of the subject's eye; calculating the intraocular distance based at least on a position of the region image in the preliminary optical coherence tomography image and the optical path length information; The 24 ophthalmic devices mentioned above.

[26] Further comprising a scan area determination unit that determines a scan area based on the intraocular distance, after the control by the optical path length control unit, the scan control unit controls the scan unit based on the scan area to apply the optical coherence tomography scan to the fundus of the subject's eye; 26. Any one of the ophthalmic devices of 21 to 25 above.

[27] The scanning unit generates an interference signal by the optical coherence tomography scan executed after the control by the optical path length control unit, a second image constructing unit that constructs an optical coherence tomography image based on the interference signal; a measurement analysis unit that applies measurement analysis to the optical coherence tomography image to generate a measurement value distribution on the fundus of the subject's eye; Further comprising: 26 above ophthalmic devices.

[28] Further comprising a storage unit that stores a reference value distribution indicating a distribution of the reference value in a fundus area of ​​a first dimension; the scan area determination unit determines the scan area based on the intraocular distance and the first dimension; an evaluation unit that evaluates the measurement value distribution corresponding to the scan area based on the reference value distribution; 27 ophthalmic devices as mentioned above.

[29] The scan area determination unit determines the scan area having a second dimension larger than the first dimension; the evaluation unit compares a partial distribution having the first dimension in the measurement value distribution corresponding to the second dimension with the reference value distribution having the first dimension; 28 ophthalmic devices as mentioned above.

[30] The storage unit stores a plurality of the reference value distributions, The evaluation unit selecting one or more reference value distributions from the plurality of reference value distributions based on the intraocular distance; evaluating the distribution of measured values ​​based on the one or more reference distributions; 28. The ophthalmic device according to claim 29.

[31] An ophthalmologic information processing device that generates evaluation reference information for a predetermined measurement index related to a subject's eye, an information acquisition unit that acquires first evaluation reference information indicating a relationship between a value of the intraocular distance in a first range and a value of the measurement index; an information generating unit that applies regression analysis to at least the first evaluation criterion information to generate second evaluation criterion information that indicates a relationship between the value of the intraocular distance and the value of the measurement index in a second range that is different from the first range; An ophthalmological information processing device comprising:

[32] The regression analysis includes extrapolation, The information generation unit applying the extrapolation to at least the first evaluation metric information to calculate an estimate of the measurement index for values ​​of the intraocular distance outside the first range; generating the second metric information using the estimated value of the measurement index; 31 above, an ophthalmology information processing device.

[33] The information generation unit generates the second evaluation criterion information in the second range, which is wider than the first range, using the estimated value of the measurement index. 32 above ophthalmology information processing devices.

[34] The first evaluation criteria information includes real-world data showing the relationship between the intraocular distance value and the measurement index value in a heterogeneous population. 34. An ophthalmology information processing device according to any one of 31 to 33 above.

[35] The first evaluation reference information includes normal eye data indicating a relationship between the value of the intraocular distance and the value of the measurement index in a group of normal eyes. 34. An ophthalmology information processing device according to any one of 31 to 33 above.

[36] The measurement index indicates the thickness of a predetermined layer tissue in the fundus. 36. An ophthalmology information processing device according to any one of items 31 to 35 above.

[37] The intraocular distance is any one of the axial length, the vitreous cavity depth, and the anterior chamber depth. 37. The ophthalmology information processing device according to any one of 31 to 36 above.

[38] A storage unit that stores the second evaluation criterion information generated by any one of the ophthalmologic information processing devices of

[31] to

[37] ; an image acquisition unit that acquires an optical coherence tomography image of the fundus of the subject's eye; a measurement analysis unit that applies measurement analysis to the optical coherence tomography image to calculate a measurement value of the measurement index; an evaluation unit that evaluates the measurement value of the measurement index based on the second evaluation criterion information; An ophthalmic device comprising: It will be understood by those skilled in the art that the present disclosure also provides embodiments in categories other than ophthalmic devices and ophthalmic information processing devices. For example, the present disclosure may provide an embodiment of a method for controlling an ophthalmic device, an embodiment of a method for controlling an ophthalmic information processing device, an embodiment of a program for causing a computer to execute each step of any of the methods, and an embodiment of a computer-readable non-transitory recording medium on which any of the programs is recorded. The recording medium may take any form. For example, the recording medium may be any of a magnetic disk, an optical disk, a magneto-optical disk, and a semiconductor memory. The present disclosure is merely an example of how to implement the present invention, and those who intend to implement the present invention can make any modifications (omissions, substitutions, additions, etc.) within the scope of the gist of the present invention. 1 Ophthalmological equipment 300 Ophthalmological equipment 310 OCT scanner 320 processor 1000, 1000A, 1000B, 1000C Ophthalmic equipment 1010 control unit 1011 Scan control unit 1012 Optical path length control section 1013 Storage section 1014 Reference Value Distribution 1020 Scanning unit 1030 Image construction unit 1040 Optical path length changing unit 1050 Intraocular distance calculation unit 1060 Alignment section 1070 Scan area determination unit 1080 Measurement and Analysis Section 1090 Artifact determination unit 1100 Evaluation Department

Claims

1. An ophthalmic device comprising: a scanning unit that applies a first optical coherence tomography scan to the fundus of a subject's eye to generate a first interference signal; an image constructing unit that constructs a first optical coherence tomography image based on the first interference signal; an optical path length changing unit that changes the optical path length of the scanning unit; and an intraocular distance calculating unit that calculates an intraocular distance based at least on the first optical coherence tomography image and optical path length information that indicates the optical path length when the first optical coherence tomography scan is applied to the fundus.

2. The ophthalmic device of claim 1, wherein the intraocular distance calculation unit analyzes the first optical coherence tomography image to identify an image of a region corresponding to a predetermined region of the fundus of the subject's eye, and calculates the intraocular distance based at least on the position of the image of the region in the first optical coherence tomography image and the optical path length information.

3. The ophthalmologic apparatus according to claim 1 or 2, wherein the intraocular distance calculation unit calculates the intraocular distance as an air-equivalent value.

4. An ophthalmic device according to any one of claims 1 to 3, further comprising an alignment unit that aligns the scanning unit with the subject's eye, and the intraocular distance calculation unit calculates the intraocular distance based at least on the first optical coherence tomography image based on the first interference signal generated after the alignment is completed and the optical path length information.

5. The ophthalmic device of claim 4, wherein the intraocular distance calculation unit calculates the intraocular distance based at least on the first optical coherence tomography image based on the first interference signal generated after the alignment is completed, the optical path length information, and dimension information indicating the dimensions of a predetermined part of the subject's eye that has been acquired in advance.

6. An ophthalmic device according to any one of claims 1 to 5, further comprising: a scan area determination unit that determines a scan area based on the intraocular distance; and a scan control unit that controls the scan unit based on the scan area, wherein the scan unit applies a second optical coherence tomography scan to the fundus of the subject's eye under the control of the scan control unit to generate a second interference signal, and the image construction unit constructs a second optical coherence tomography image based on the second interference signal.

7. An ophthalmic device according to claim 6, further comprising: an artifact determination unit that determines whether the first optical coherence tomography image contains a folding artifact; and an optical path length control unit that controls the optical path length changing unit to change the optical path length when the artifact determination unit determines that the folding artifact is contained, wherein after the optical path length is changed by the optical path length changing unit under the control of the optical path length control unit, the scan control unit causes the scan unit to execute the second optical coherence tomography scan.

8. The ophthalmologic apparatus according to claim 6 or 7, further comprising a measurement analysis unit that applies measurement analysis to the second optical coherence tomography image to generate a distribution of measurement values ​​at the fundus of the subject's eye.

9. An ophthalmologic device according to claim 8, further comprising a memory unit that stores a reference value distribution indicating the distribution of reference values ​​in a fundus area of ​​a first dimension, wherein the scan area determination unit determines the scan area based on the intraocular distance and the first dimension, and further comprising an evaluation unit that evaluates the measurement value distribution corresponding to the scan area based on the reference value distribution.

10. The ophthalmic device of claim 9, wherein the scan area determination unit determines the scan area having a second dimension larger than the first dimension, and the evaluation unit compares a partial distribution having the first dimension in the measurement value distribution corresponding to the second dimension with the reference value distribution having the first dimension.

11. An ophthalmic device according to claim 9 or 10, wherein the memory unit stores a plurality of the reference value distributions, and the evaluation unit selects one or more reference value distributions from the plurality of reference value distributions based on the intraocular distance, and evaluates the measurement value distribution based on the one or more reference value distributions.

12. An ophthalmologic apparatus comprising: a scanning unit that applies an optical coherence tomography scan to the fundus of the subject's eye; a front image acquisition unit that acquires a front image of the fundus of the subject's eye; a scan dimension determination unit that has a trained model that receives an input of a front image of the fundus and outputs scan dimensions, the trained model being created by machine learning using training data including a front image of the fundus and label data indicating scan dimensions, and that determines scan dimensions based on output from the trained model corresponding to the input of the front image acquired by the front image acquisition unit; and a scan control unit that controls the scanning unit based on the scan dimensions determined by the scan dimension determination unit to apply a first optical coherence tomography scan to the fundus of the subject's eye.

13. The ophthalmological device of claim 12, wherein the front image acquisition unit includes a front photographing unit that photographs the test eye from the front and generates a front video image, and further includes an alignment unit that aligns the scan unit with the test eye based on the front video image in parallel with the generation of the front video image by the front photographing unit, the scan dimension determination unit determines the scan dimensions based on output from the trained model corresponding to input frames of the front video image in parallel with the generation of the front video image and the alignment, and the scan control unit causes the scan unit to perform the first optical coherence tomography scan after the alignment is completed.

14. An ophthalmic device according to claim 12 or 13, wherein the scanning unit further comprises: an image construction unit that generates a first interference signal by the first optical coherence tomography scan and generates a first optical coherence tomography image based on the first interference signal; and a measurement analysis unit that applies measurement analysis to the first optical coherence tomography image to generate a measurement value distribution at the fundus of the subject's eye.

15. An ophthalmic device according to claim 14, further comprising: an optical path length changing unit that changes the optical path length of the scanning unit; an artifact determination unit that determines whether the first optical coherence tomography image contains a folding artifact; and an optical path length control unit that controls the optical path length changing unit to change the optical path length when the artifact determination unit determines that the folding artifact is contained, wherein after the optical path length is changed by the optical path length changing unit under the control of the optical path length control unit, the scan control unit controls the scanning unit to apply a second optical coherence tomography scan to the fundus of the subject's eye.

16. The ophthalmic device of claim 15, wherein the scanning unit generates a second interference signal by the second optical coherence tomography scan, the image constructing unit generates a second optical coherence tomography image based on the second interference signal, and the measurement and analysis unit applies the measurement and analysis to the second optical coherence tomography image.

17. The ophthalmic device of claim 16, wherein, when the second optical coherence tomography scan is performed, the measurement and analysis unit applies the measurement and analysis to the second optical coherence tomography image without applying the measurement and analysis to the first optical coherence tomography image.

18. An ophthalmologic device according to any one of claims 14 to 17, further comprising: a memory unit that stores a reference value distribution indicating a distribution of reference values ​​in a fundus area of ​​a first dimension; the scan dimension determination unit determines the scan dimension based on the output from the trained model and the first dimension; the measurement analysis unit generates the measurement value distribution corresponding to the scan dimension determined based on the first dimension; and an evaluation unit that evaluates the measurement value distribution corresponding to the scan dimension based on the reference value distribution.

19. The ophthalmic device of claim 18, wherein the scan dimension determination unit determines a second dimension larger than the first dimension as the scan dimension, and the evaluation unit compares a partial distribution having the first dimension in the measurement value distribution corresponding to the second dimension with the reference value distribution having the first dimension.

20. An ophthalmic device according to claim 18 or 19, further comprising an intraocular distance acquisition unit that acquires intraocular distance information indicating the intraocular distance of the subject eye, wherein the memory unit stores a plurality of the reference value distributions, and the evaluation unit selects one or more reference value distributions from the plurality of reference value distributions based on the intraocular distance, and evaluates the measurement value distribution based on the one or more reference value distributions.

21. An ophthalmic device comprising: a scanning unit that applies an optical coherence tomography scan to the fundus of the subject's eye; an optical path length changing unit that changes the optical path length of the scanning unit; an intraocular distance calculation unit that calculates the intraocular distance based on data previously acquired from the subject's eye; an intraocular distance comparison unit that compares the intraocular distance with a predetermined threshold; an optical path length control unit that controls the optical path length changing unit to change the optical path length when the intraocular distance comparison unit determines that the intraocular distance is greater than the threshold; and a scan control unit that controls the scanning unit to apply an optical coherence tomography scan to the fundus of the subject's eye after the optical path length has been changed by the optical path length changing unit under the control of the optical path length control unit.

22. The ophthalmologic apparatus according to claim 21, further comprising a data acquisition unit that acquires the data of the subject's eye.

23. The ophthalmic device of claim 22, wherein the data acquisition unit includes: a scanning unit that applies a preliminary optical coherence tomography scan to the fundus of the subject's eye to generate a preliminary interference signal; and a first image construction unit that constructs a preliminary optical coherence tomography image based on the preliminary interference signal; and the data of the subject's eye includes the preliminary optical coherence tomography image.

24. The ophthalmic device of claim 23, wherein the intraocular distance calculation unit calculates the intraocular distance based at least on the preliminary optical coherence tomography image and optical path length information indicating the optical path length when the preliminary optical coherence tomography scan is applied to the fundus.

25. An ophthalmic device according to claim 24, wherein the intraocular distance calculation unit analyzes the preliminary optical coherence tomography image to identify a region image corresponding to a predetermined region of the fundus of the subject's eye, and calculates the intraocular distance based at least on the position of the region image in the preliminary optical coherence tomography image and the optical path length information.

26. An ophthalmic device according to any one of claims 21 to 25, further comprising a scan area determination unit that determines a scan area based on the intraocular distance, and after the control by the optical path length control unit, the scan control unit controls the scan unit based on the scan area to apply the optical coherence tomography scan to the fundus of the subject's eye.

27. The ophthalmologic apparatus of claim 26, wherein the scanning unit further comprises: a second image construction unit that generates an interference signal by the optical coherence tomography scan executed after the control by the optical path length control unit and constructs an optical coherence tomography image based on the interference signal; and a measurement analysis unit that applies measurement analysis to the optical coherence tomography image to generate a measurement value distribution at the fundus of the subject's eye.

28. An ophthalmologic device according to claim 27, further comprising a memory unit that stores a reference value distribution indicating the distribution of reference values ​​in a fundus area of ​​a first dimension, wherein the scan area determination unit determines the scan area based on the intraocular distance and the first dimension, and further comprising an evaluation unit that evaluates the measurement value distribution corresponding to the scan area based on the reference value distribution.

29. The ophthalmic device of claim 28, wherein the scan area determination unit determines the scan area having a second dimension larger than the first dimension, and the evaluation unit compares a partial distribution having the first dimension in the measurement value distribution corresponding to the second dimension with the reference value distribution having the first dimension.

30. An ophthalmic device according to claim 28 or 29, wherein the memory unit stores a plurality of the reference value distributions, and the evaluation unit selects one or more reference value distributions from the plurality of reference value distributions based on the intraocular distance, and evaluates the measurement value distribution based on the one or more reference value distributions.

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