Scanning imaging device, its control method, program, and recording medium

Abstract

To expedite determination on success or failure of scanning.SOLUTION: An ophthalmologic examination device 1 (a scanning type imaging device) is configured so as to collect a data set by applying, to a specimen, optical scanning according to a two-dimensional pattern including a series of cycles that intersect with each other, and construct image data on the basis of the data set. Furthermore, the ophthalmologic examination device 1 is configured to change the number of samples in sampling for constructing the image data.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to a scanning imaging apparatus, a control method thereof, a program, and a recording medium. [Background technology]

[0002] Scanning imaging is one type of imaging technology. Scanning imaging is a technique in which a beam is sequentially irradiated onto multiple locations on an object to be inspected, data is collected, and an image of the object is constructed from the collected data. Scanning imaging techniques include, for example, spot-type scanning techniques that use a beam that projects a spot-shaped image, line-type scanning techniques that use a beam that projects a line-shaped image, and area-type scanning techniques that use a beam that projects an area-shaped image. Representative examples of these techniques include Fourier-domain optical coherence tomography (OCT), line scan cameras, and full-field OCT, respectively.

[0003] Optical Coherence Tomography (OCT) is an example of a scanning imaging modality that uses light. OCT is a technology that can image light-scattering media with a resolution of micrometers or less, and is used in medical imaging and non-destructive testing.

[0004] OCT is a technology based on low-coherence interferometry. In medical imaging, a probe light (measurement light) in the near-infrared region is used, taking into account its depth and invasiveness. However, scanning imaging using light (electromagnetic waves) in wavelength bands other than near-infrared, ultrasound, and radiation are also known.

[0005] Ophthalmology is one of the most advanced fields in the application of OCT, with products equipped with Fourier-domain OCT functionality now widespread in clinics. Ophthalmic imaging diagnostics not only provides two-dimensional imaging, but also three-dimensional imaging, structural analysis, and functional analysis, making it a widely used, powerful diagnostic tool. In addition to Fourier-domain OCT, scanning optical ophthalmoscopes (SLOs), line scan cameras, and full-field OCT are also used in ophthalmology.

[0006] There are various scanning modes used in OCT and SLO, but the so-called "Lissajous scan" intended for the purpose of correcting motion artifacts has been attracting attention in recent years (see, for example, Patent Documents 1 to 3).

[0007] A Lissajous scan is a scan performed according to a two-dimensional pattern generated as a Lissajous curve by synthesizing two mutually orthogonal simple harmonic motions. In a Lissajous scan, the measurement light is scanned at high speed to trace multiple loops (multiple cycles that intersect with each other) of a certain size, making it possible to virtually ignore the difference in data acquisition time from one cycle. Furthermore, because the intersection areas of different cycles can be referenced to align the cycles, it is possible to correct motion artifacts caused by the movement of the subject. These characteristics of the Lissajous scan are being utilized in the field of ophthalmology to address motion artifacts caused by eye movement. [Prior art documents] [Patent documents]

[0008] [Patent Document 1] Japanese Patent Application Publication No. 2018-68578 [Patent Document 2] Japanese Patent Application Laid-Open No. 2018-140004 [Patent Document 3] Japanese Patent Application Laid-Open No. 2018-140049 Summary of the Invention [Problem to be solved by the invention]

[0009] Events that occur during data collection (e.g., eye movement, blinking) or the operation of the device (e.g., control parameters) can sometimes prevent the acquisition of image data of sufficient quality for diagnosis. With conventional Lissajous scanning technology, it is not possible to determine whether a scan was successful until data collection from the subject and the construction of image data from this data are complete. Furthermore, in Lissajous scanning, compared to other scanning modes (e.g., raster scanning), data processing for constructing image data requires a significant amount of time and resources. Therefore, determining the success or failure of a Lissajous scan requires more time and effort than in other scanning modes, and there may be situations in which redoing (rescanning) a Lissajous scan is practically difficult.

[0010] One object of the present invention is to speed up the determination of the success or failure of a scan. [Means for solving the problem]

[0011] A scanning imaging apparatus according to an exemplary aspect of an embodiment includes a data set collection unit, an image data construction unit, and a sampling control unit. The data set collection unit collects a data set by applying an optical scan to a test object according to a two-dimensional pattern including a series of cycles that intersect with each other. The image data construction unit constructs image data based on the data set collected by the data set collection unit. The sampling control unit changes the number of samples in sampling for constructing the image data. [Effects of the Invention]

[0012] According to an exemplary aspect of the embodiment, it is possible to speed up the determination of the success or failure of a scan. [Brief explanation of the drawings]

[0013] [Figure 1]1 is a schematic diagram illustrating an example of the configuration of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 2] 1 is a schematic diagram illustrating an example of the configuration of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 3] 1 is a schematic diagram illustrating an example of the configuration of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 4A] 1 is a schematic diagram illustrating an example of the configuration of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 4B] 1 is a schematic diagram illustrating an example of the configuration of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 4C] 1 is a schematic diagram illustrating an example of the configuration of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 5] 1 is a schematic diagram showing an example of a Lissajous scan pattern performed by a scanning imaging device (ophthalmic examination device) according to an exemplary aspect of the embodiment. [Figure 6A] 1 is a flowchart illustrating an example of the operation of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 6B] 1 is a flowchart illustrating an example of the operation of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 6C] 1 is a flowchart illustrating an example of the operation of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 6D] 1 is a flowchart illustrating an example of the operation of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 6E] 1 is a flowchart illustrating an example of the operation of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 7A] 1A to 1C are diagrams for explaining an example of the operation of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 7B] 1A to 1C are diagrams for explaining an example of the operation of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 7C] 1A to 1C are diagrams for explaining an example of the operation of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 8] 1A to 1C are diagrams for explaining an example of the operation of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 9] 1 is a flowchart illustrating an example of the operation of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 10] 1 is a flowchart illustrating an example of the operation of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 11] 1 is a flowchart illustrating an example of the operation of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 12] 1 is a flowchart illustrating an example of the operation of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 13] 1A to 1C are diagrams for explaining an example of the operation of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 14] 1 is a flowchart illustrating an example of the operation of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 15] 1 is a flowchart illustrating an example of the operation of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 16] 1 is a flowchart illustrating an example of the operation of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 17] 1 is a flowchart illustrating an example of the operation of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. [Figure 18]1 is a schematic diagram illustrating an example of the configuration of a scanning imaging apparatus (ophthalmic examination apparatus) according to an exemplary aspect of an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0014] The present disclosure will now be described with reference to the drawings, with respect to some exemplary aspects of the embodiments. The exemplary aspects described below relate to a scanning imaging device, a control method for a scanning imaging device, a program, and a recording medium, but the embodiments are not limited to these aspects.

[0015] Furthermore, while the exemplary aspects described below provide some applications in the field of ophthalmology, embodiments are not limited to these aspects and may be applied to any field, such as applications in medical departments other than ophthalmology, applications in medical methods such as diagnostic methods, and applications in fields other than the medical field (biology, non-destructive testing, etc.).

[0016] Any matter disclosed in the documents cited in this specification, any matter related to publicly known technologies in the technical field related to the embodiment, or any matter related to publicly known technologies in other technical fields can be combined with an exemplary aspect. Furthermore, in this specification, unless otherwise specified, no distinction is made between "image data" and an "image" formed and / or output based on the image data, and no distinction is made between a "site" of a subject (especially the subject's eye) and its "image data" and "image."

[0017] A scanning imaging device according to an exemplary embodiment described below is a device used in ophthalmic examinations (referred to as an ophthalmic examination device), and is configured to be able to measure and image the fundus of a living eye using Fourier-domain OCT (more specifically, swept-source OCT). The type of OCT that can be employed in the embodiment is not limited to swept-source OCT, and may be, for example, spectral-domain OCT or time-domain OCT.

[0018] The scanning imaging device according to some exemplary embodiments may be capable of using a scanning imaging modality other than OCT, for example, some exemplary embodiments may employ any optical scanning imaging modality such as SLO.

[0019] In addition to processing data collected by OCT scans and / or SLO scans, the ophthalmic examination apparatus according to some exemplary embodiments may be capable of processing data acquired by other imaging modalities. The "other imaging modalities" may be any ophthalmic imaging modalities, such as a fundus camera, a slit lamp microscope, or an ophthalmic surgical microscope. The ophthalmic examination apparatus according to some exemplary embodiments may have the functionality of imaging modalities other than OCT and SLO. Furthermore, the ophthalmic examination apparatus according to some exemplary embodiments may be capable of performing an alignment method using two or more anterior segment cameras (e.g., referred to as stereo alignment) as disclosed in Japanese Patent Application Publication No. 2013-248376 (U.S. Patent Application Publication No. 2015 / 085252 and U.S. Patent Application Publication No. 2016 / 345822).

[0020] The scanning imaging device according to the exemplary embodiment described below uses a spot-type scanning technique, but it will be understood by those skilled in the art that any aspect of the present disclosure can be applied to a scanning imaging device that uses other types of scanning techniques (e.g., a line-type scanning technique, an area-type scanning technique).

[0021] Furthermore, although the scanning imaging device according to the exemplary embodiment described below uses an optical scanning imaging modality, it will be understood by those skilled in the art that any aspect of the present disclosure can be applied to a scanning imaging device that uses other types of scanning imaging modalities (e.g., a scanning imaging modality that uses electromagnetic waves other than light, or a scanning imaging modality that uses ultrasound).

[0022] The object (subject) to which scanning imaging is applied may be any object. In the ophthalmic application described in the exemplary embodiments, scanning imaging is applied to the fundus, but it may also be applied to any part of the eye, such as the anterior segment or the vitreous body. The configurations and functions of some exemplary embodiments may be applied to measurement and imaging of biological parts (tissues) other than the eye, and may also be applied to measurement and imaging of non-biological objects (e.g., objects that move) or parts thereof. That is, the industrial application fields of some exemplary embodiments are not limited to ophthalmology-related fields, but may also include medical, veterinary, and biological fields, and may more generally include fields related to any subject that moves locally and / or globally. Note that the industrial application fields of some exemplary embodiments may also include fields related to subjects that do not move.

[0023] All aspects of the embodiments described below are merely examples and are not intended to limit the invention according to the present disclosure.

[0024] A first aspect of the embodiment is a scanning imaging device including a dataset collection unit that applies an optical scan according to a two-dimensional pattern including a series of cycles that intersect with each other to a test object to collect a dataset, an image data construction unit that constructs image data based on the dataset, and a sampling control unit that changes the number of samples in the sampling for constructing the image data.

[0025] A second aspect of the embodiment is a scanning imaging device of the first aspect, wherein the sampling control unit changes the number of samples in the sampling to a first number of samples and a second number of samples greater than the first number of samples, and the image data construction unit constructs first image data based on a first data set obtained in the first sampling to which the first number of samples is applied, and constructs second image data based on a second data set obtained in the second sampling to which the second number of samples is applied.

[0026] A third aspect of the embodiment is the scanning imaging apparatus of the second aspect, wherein the sampling control unit applies the second number of samples after applying the first number of samples.

[0027] A fourth aspect of the embodiment is the scanning imaging apparatus of the third aspect, wherein the sampling control unit increases the number of samples in the sampling stepwise.

[0028] A fifth aspect of the embodiment is a scanning imaging device of any of the first to fourth aspects, wherein the sampling control unit determines whether the quality of the image data constructed by the image data construction unit is good, and changes the number of samples if it is determined that the quality of the image data is not good.

[0029] A sixth aspect of the embodiment is a scanning imaging device of any of the first to fifth aspects, wherein the sampling control unit determines whether the quality of the image data constructed by the image data construction unit is good, and changes the number of samples to a predetermined maximum number if it is determined that the quality of the image data is good.

[0030] A seventh aspect of the embodiment is a scanning imaging device of any of the first to fourth aspects, further including a display control unit that causes a display device to display an image based on image data constructed by the image data construction unit, and an operation unit through which a user inputs instructions based on the image displayed on the display device, and the sampling control unit changes the number of samples based on the instructions input to the operation unit.

[0031] An eighth aspect of the embodiment is a scanning imaging device according to any one of the first to seventh aspects, wherein the sampling control unit includes a first sampling control unit that controls the data set collection unit to change the number of scan points in the optical scanning in order to change the number of samples.

[0032] A ninth aspect of the embodiment is the scanning imaging apparatus of the eighth aspect, wherein the first sampling control unit controls the data set collection unit to change the interval between scan points in the optical scanning.

[0033] A tenth aspect of the embodiment is a scanning imaging device of the eighth or ninth aspect, wherein the first sampling control unit controls the dataset collection unit to change the number of cycles included in the series of cycles in the optical scan.

[0034] An eleventh aspect of the embodiment is a scanning imaging device according to any one of the eighth to tenth aspects, wherein the first sampling control unit controls the data set collection unit to change the dimensions of the application area of ​​the optical scanning.

[0035] A twelfth aspect of the embodiment is a scanning imaging device of any of the first to eleventh aspects, wherein the image data construction unit performs data sampling to extract a sub-dataset from the data set collected by the image data collection unit, and constructs the image data based on the sub-dataset extracted from the data set by the data sampling, and the sampling control unit includes a second sampling control unit that controls the image data construction unit to change the number of samples and changes the number of data included in the sub-dataset extracted from the data set in the data sampling.

[0036] A thirteenth aspect of the embodiment is the scanning imaging apparatus of the twelfth aspect, wherein the second sampling control unit controls the image data constructing unit to change a data extraction interval in the data sampling.

[0037] A fourteenth aspect of the embodiment is a scanning imaging device of the twelfth or thirteenth aspect, wherein the second sampling control unit controls the image data construction unit to change the number of cycles from which data is extracted in the data sampling among the series of cycles in the optical scanning.

[0038] A fifteenth aspect of the embodiment is a scanning imaging device of any of the twelfth to fourteenth aspects, wherein the second sampling control unit controls the image data construction unit to change the dimensions of an area within the application area of ​​the optical scanning that is the target of data extraction in the data sampling.

[0039] A sixteenth aspect of the embodiment is a scanning imaging device according to any one of the first to fifteenth aspects, wherein the data set collection unit includes a deflector capable of deflecting light for optical scanning in two directions different from each other, and applies the first optical scan to the sample by repeatedly changing the deflection direction along one of the two directions in a first period while repeatedly changing the deflection direction along the other direction in a second period different from the first period.

[0040] A seventeenth aspect of the embodiment is a method for controlling a scanning imaging device including a scanner that performs optical scanning and a processor that constructs image data from a data set collected by the optical scanning, wherein control of at least one of the scanner and the processor is performed to change the number of samples in sampling to construct the image data.

[0041] An 18th aspect of embodiment is the method of the 17th aspect, wherein the control for changing the number of samples includes at least one of control of the scanner to change the number of scan points in the optical scan and control of the processor to change the number of data extracted from the dataset by data sampling.

[0042] A nineteenth aspect of the embodiment is a program for causing a computer to execute the method of the seventeenth or eighteenth aspect.

[0043] A twentieth aspect of the embodiment is a computer-readable non-transitory recording medium having the program of the nineteenth aspect recorded thereon.

[0044] The aspects of the embodiment are not limited to the above-described aspects 1 to 20. For example, features that can be combined with aspect 1 (e.g., features related to aspects 2 to 16, any feature in the embodiments of the present disclosure, any known technology, etc.) can be combined with aspects 17 to 20.

[0045] The exemplary embodiments described below utilize the Lissajous scanning technology described in the following document: Yiwei Chen, Young-Joo Hong, Shuichi Makita, and Yoshiaki Yasuno, "Three-dimensional eye motion correction by Lissajous scan optical coherence tomography," Biomedical Optics EXPRESS, Vol. 8, No. 3, 1 Mar 2017, pp. 1783-1802. This document is referred to as "Chen." Scanning technologies that can be used in the embodiments are not limited thereto. Some exemplary embodiments may at least partially utilize scanning technologies (Lissajous scanning technology or technologies related to other scanning modes) described in documents other than Chen.

[0046] The technique described in Chen divides a data set acquired from a Lissajous scan into multiple subvolumes that do not involve significant motion, and constructs en face projection images of each subvolume. These en face projection images are called strips. Registration between these strips results in an image that is motion artifact-corrected.

[0047] First Embodiment A first embodiment will be described. The scanning imaging apparatus according to this embodiment is a scanning imaging apparatus that constructs image data based on a data set collected from a test object by optical scanning such as a Lissajous scan, and has a function for changing the number of samples in sampling for constructing the image data. A sample is data (for example, a value or a set of values) acquired by sampling.

[0048] This sampling may include sampling during the optical scan (referred to as scan sampling) and / or sampling during the processing of data collected during the optical scan (referred to as data sampling).

[0049] Scan sampling may be the act of (selectively) acquiring data from multiple portions of a specimen. In this embodiment, scan sampling may be, for example, applying an optical scan to the specimen, collecting a data set from the specimen, etc. In this embodiment, several exemplary aspects of scan sampling and related processes are described.

[0050] Data sampling may be an operation of extracting multiple partial data sets from data collected by optical scanning or data generated based on the collected data. Data sampling according to the present disclosure may be, for example, a process of extracting discrete data sets from continuous data (converting a continuous signal into a discrete signal, converting an analog signal into a digital signal, or A / D conversion), a process of extracting multiple continuous partial data sets from continuous data, a process of extracting one or more continuous partial data sets and one or more discrete partial data sets from continuous data, a process of extracting multiple discrete partial data sets from discrete data, or a combination of any of these processes. Furthermore, data sampling according to the present disclosure may be, for example, a process of extracting multiple partial image data sets from image data, a process of extracting multiple partial data sets from data generated based on image data, a process of extracting multiple partial data sets (subsets of a set consisting of multiple image data sets) from an image data set (a set consisting of multiple image data sets), or a combination of any of these processes. Some examples of data sampling and related processes will be described in the second embodiment.

[0051] <Configuration of ophthalmic examination device> 1 is an exemplary embodiment of a scanning imaging apparatus according to the present invention. The ophthalmic examination apparatus 1 includes a fundus camera unit 2, an OCT unit 100, and a processing unit 200.

[0052] The fundus camera unit 2 is provided with a group of elements (optical elements, mechanisms, etc.) for photographing the subject's eye E from the front. Instead of or in addition to the fundus camera unit 2, an SLO unit may be provided.

[0053] The OCT unit 100 is provided with a part of a group of elements (optical elements, mechanisms, etc.) for applying an OCT scan to the subject's eye E. Another part of the group of elements for the OCT scan is provided in the fundus camera unit 2.

[0054] The processing unit 200 includes one or more processors that perform various processes (such as arithmetic operations, image processing, conversion, analysis, and control).

[0055] In addition to these units, the ophthalmic examination apparatus 1 may also include elements for supporting the subject's face and elements for switching the region where the OCT scan is applied. Examples of the former elements include a chin rest and a forehead rest. Examples of the latter elements include a lens unit used to switch the region where the OCT scan is applied from the fundus to the anterior segment.

[0056] The functionality of some elements disclosed herein is implemented using circuitry or processing circuitry. Circuitry or processing circuitry includes any of 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), conventional circuitry, and any combination thereof, configured and / or configured to perform the disclosed functions. A processor is considered to be processing circuitry or circuitry that includes transistors and / or other circuitry. In this disclosure, circuitry, unit, means, or similar terms is hardware that performs the disclosed functions or hardware that is programmed to perform the disclosed functions. The hardware may be hardware disclosed herein or may be known hardware that is programmed and / or configured to perform the described functions. In the case of a processor, where the hardware can be considered to be a type of circuitry, the circuitry, unit, means, or similar terms is a combination of hardware and software, and the software is used to configure the hardware and / or processor.

[0057] <Fundus camera unit 2> The fundus camera unit 2 is provided with an optical system for photographing the fundus Ef of the subject's eye E. The acquired image of the fundus Ef (called a fundus image, fundus photograph, etc.) is a front image such as an observed image or a photographed image. The observed image is obtained by, for example, video shooting using near-infrared light, and is used for alignment, focusing, tracking, etc. The photographed image is a still image obtained using, for example, flash light in the visible or infrared range.

[0058] 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 detects return light of the illumination light from the subject's eye E. The measurement light from the OCT unit 100 is guided to the subject's eye E through an optical path within the fundus camera unit 2, and the return light is guided to the OCT unit 100 through the same optical path.

[0059] Light (observation illumination light) output from an observation light source 11 of an illumination optical system 10 is reflected by a concave mirror 12, passes through a condenser lens 13, and is transmitted through a visible light cut filter 14 to become near-infrared light. The observation illumination light is then focused near an imaging light source 15, reflected by a mirror 16, and passes through a relay lens system 17, a relay lens 18, an aperture 19, and a relay lens system 20. The observation illumination light is then reflected by the peripheral portion (the area surrounding the hole) of a perforated mirror 21, passes through a dichroic mirror 46, and is refracted by an objective lens 22 to illuminate the subject's eye E (fundus oculi Ef). Return light of the observation illumination light from the subject's eye E is refracted by the objective lens 22, passes through the dichroic mirror 46, passes through a hole formed in the central region of the perforated mirror 21, passes through a dichroic mirror 55, passes through an imaging focusing lens 31, and is reflected by a mirror 32. Furthermore, this returned light 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 returned light at a predetermined frame rate. The focus (focal position) of the photographing optical system 30 is adjusted to match the fundus Ef or the anterior segment of the eye.

[0060] Light (photography illumination light) output from the photography light source 15 is irradiated onto the fundus oculi Ef through the same path as the observation illumination light. Return light of the photography illumination light from the subject's eye E is guided to the dichroic mirror 33 through 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.

[0061] The liquid crystal display (LCD) 39 displays a fixation target (fixation target image). A portion of 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, and passes through the hole in the aperture mirror 21. The light beam that passes through the hole in the aperture mirror 21 passes through the dichroic mirror 46, is refracted by the objective lens 22, and is projected onto the fundus Ef. By changing the display position of the fixation target image on the LCD 39, the direction in which the gaze of the subject's eye E is guided (fixation direction, fixation position) can be changed. Instead of a display device such as an LCD, for example, a light-emitting element array, or a combination of a light-emitting element and a mechanism for moving it, may be used.

[0062] The alignment optical system 50 generates an alignment index used to align the optical system 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 hole in the aperture mirror 21, transmits through the dichroic mirror 46, and is projected onto the subject's eye E via the objective lens 22. Return light of the alignment light from the subject's eye E (such as corneal reflection light) is guided to the image sensor 35 via the same path as the return light of the observation illumination light. Manual alignment or automatic alignment can be performed based on the received light image (alignment index image).

[0063] 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 (photographing 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 reflecting surface of the reflecting rod 67 is tilted and positioned in the illumination optical path. 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, and is first imaged and reflected on the reflecting surface of the reflecting rod 67 by the condenser lens 66. The focusing light then passes through the relay lens 20, is reflected by the aperture mirror 21, passes through the dichroic mirror 46, and is projected onto the subject's eye E via the objective lens 22. The return light (fundus reflected light, etc.) of the focusing light from the subject's eye E passes through the same path as the return light of the alignment light and is guided to the image sensor 35. Manual focusing or autofocusing can be performed based on the received light image (split target image).

[0064] Diopter correction lenses 70 and 71 can be 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 (convex lens) for correcting severe hyperopia. The diopter correction lens 71 is a minus lens (concave lens) for correcting severe myopia.

[0065] The dichroic mirror 46 combines the optical path for fundus imaging and the optical path for OCT (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.

[0066] The retroreflector 41 is movable in the direction of the arrow shown in Figure 1, thereby changing the length of the measurement arm. Changing the length of the measurement arm is used, for example, to correct the optical path length according to the axial length of the eye, adjust the interference state, and so on.

[0067] The dispersion compensation member 42, together with a dispersion compensation member 113 (described later) disposed in the reference arm, acts to match the dispersion characteristics of the measurement light LS with the dispersion characteristics of the reference light LR.

[0068] The OCT focusing lens 43 is moved along the measurement arm to adjust the focus of the measurement arm. The movement of the imaging focusing lens 31, the movement of the focus optical system 60, and the movement of the OCT focusing lens 43 can be controlled in a coordinated manner.

[0069] The optical scanner 44 is disposed at a position that is substantially optically conjugate with the pupil of the subject's eye E. The optical scanner 44 deflects the measurement light LS guided by the measurement arm. The optical scanner 44 is, for example, a galvanometer scanner capable of two-dimensional scanning, including a galvanometer mirror for scanning in the x direction and a galvanometer mirror for scanning in the y direction.

[0070] <OCTユニット100> As illustrated in FIG. 2, the OCT unit 100 is provided with an optical system for applying swept-source OCT. This optical system includes an interference optical system. This interference optical system splits light from a wavelength-tunable light source (swept-wavelength light source) into measurement light and reference light, and generates interference light by superimposing the return light of the measurement light guided to the subject's eye E by the measurement arm on the reference light guided by the reference arm, and detects this interference light. Data (detection signal) obtained by the interference optical system is an analog signal representing the spectrum of the interference light, and is sent to the processing unit 200.

[0071] The light source unit 101 includes, for example, a near-infrared tunable laser that changes the output wavelength at high speed at least in the near-infrared wavelength band. Light L0 output from the light source unit 101 is guided by an optical fiber 102 to a polarization controller 103, where its polarization state is adjusted. The light L0 is further guided by an optical fiber 104 to a fiber coupler 105, where it is split into measurement light LS and reference light LR. The optical path of the measurement light LS is called a measurement arm, and the optical path of the reference light LR is called a reference arm.

[0072] The reference light LR is guided by an optical fiber 110 to a collimator 111, where it is converted into a parallel beam, and then guided to a retroreflector 114 via an optical path length correction element 112 and a dispersion compensation element 113. The optical path length correction element 112 acts to match the optical path length of the reference light LR with that of the measurement light LS. The dispersion compensation element 113, together with a dispersion compensation element 42 arranged in the measurement arm, acts to match the dispersion characteristics between the reference light LR and the measurement light LS. The retroreflector 114 is movable along the optical path of the reference light LR incident thereon, thereby changing the length of the reference arm. Changing the reference arm length is used, for example, to correct the optical path length according to the axial length of the eye, adjust the interference state, and so on.

[0073] 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 convergent beam by the collimator 116, and enters an optical fiber 117. The reference light LR that has entered the optical fiber 117 is guided to a polarization controller 118 where its polarization state is adjusted, is guided through an optical fiber 119 to an attenuator 120 where its light amount is adjusted, and is guided through an optical fiber 121 to a fiber coupler 122.

[0074] On the other hand, the measurement light LS generated by the fiber coupler 105 is guided by the optical fiber 127 and converted into a parallel beam by the collimator lens unit 40, 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. The returning light of the measurement light LS from the subject's eye E travels the same path as the outward path in the opposite direction and is guided to the fiber coupler 105, and reaches the fiber coupler 122 via the optical fiber 128.

[0075] The fiber coupler 122 generates interference light by superimposing the measurement light LS incident via the optical fiber 128 and the reference light LR incident via the optical fiber 121. The fiber coupler 122 splits the generated interference light at a predetermined splitting ratio (for example, 1:1) to generate a pair of interference lights LC. The pair of interference lights LC are guided to the detector 125 via optical fibers 123 and 124, respectively.

[0076] The detector 125 includes, for example, a balanced photodiode. The balanced photodiode has a pair of photodetectors that respectively detect a pair of interference light LC, and outputs the difference between the pair of detection results obtained by these. The output (detection signal) from the detector 125 is sent to the image data constructing unit 220.

[0077] In this example, both an element for changing the measurement arm length (e.g., retroreflector 41) and an element for changing the reference arm length (e.g., retroreflector 114 or reference mirror) are provided, but only one of these elements may be provided. Furthermore, the element for changing the difference between the measurement arm length and the reference arm length (optical path length difference) is not limited to these and may be any element (optical member, mechanism, etc.).

[0078] <Control system / processing system> 3, 4A, 4B, and 4C show configuration examples of the control system and processing system of the ophthalmic examination apparatus 1. The control unit 210, image data creation unit 220, and data processing unit 230 are provided in, for example, the processing unit 200. The ophthalmic examination apparatus 1 may include a communication device for performing data communication with an external device. The ophthalmic examination apparatus 1 may also include a drive device (reader / writer) for reading data from a recording medium and writing data to the recording medium.

[0079] <Control unit 210> The control unit 210 performs various types of control. The control unit 210 includes a main control unit 211 and a memory unit 212. As shown in Fig. 4A, the main control unit 211 includes a scan control unit 2111, and the memory unit 212 stores a scan protocol 2121. A scan control unit 2111A shown in Fig. 4C is an exemplary embodiment of the scan control unit 2111, and includes a sampling control unit 2112.

[0080] <Main control unit 211> The main control unit 211 controls each element of the ophthalmic examination apparatus 1. The main control unit 211 is realized by cooperation between hardware including a processor and control software. The scan control unit 2111 controls the OCT scan.

[0081] The imaging focusing driver 31A moves the imaging focusing lens 31 arranged in the imaging optical path and the focus optical system 60 arranged in the illumination optical path under the control of the main controller 211. The retroreflector (RR) driver 41A moves the retroreflector 41 provided on the measurement arm under the control of the main controller 211. The OCT focusing driver 43A moves the OCT focusing lens 43 arranged in the measurement arm under the control of the main controller 211. The retroreflector (RR) driver 114A moves the retroreflector 114 arranged in the reference arm under the control of the main controller 211. Each driver includes an actuator such as a pulse motor that operates under the control of the main controller 211. The optical scanner 44 operates under the control of the main controller 211 (scan controller 2111). The moving mechanism 150 is configured to move the fundus camera unit 2 three-dimensionally.

[0082] <Storage section 212> The storage unit 212 stores various types of data. The data stored in the storage unit 212 includes OCT images, fundus images, subject eye information, and control information. The subject eye information includes subject information such as patient ID and name, left / right eye identification information, and electronic medical record information. The control information is information related to specific controls. The control information in this embodiment includes a scanning protocol 2121.

[0083] The scanning protocol 2121 is an agreement regarding the control content for an OCT scan, and includes a set of various control parameters (scanning control parameters). The scanning protocol 2121 includes a protocol for each scanning mode. The scanning protocol 2121 of this embodiment includes at least a protocol for a Lissajous scan, and may further include protocols for a B scan (line scan), a cross scan, a radial scan, a raster scan, etc.

[0084] The scan control parameters of this embodiment include at least parameters indicating the content of control over the optical scanner 44. These parameters include, for example, a parameter indicating the scan pattern, a parameter indicating the scan speed, a parameter indicating the number of scan points (xy positions of the A-scans), a parameter indicating the interval between scan points (scan interval), a parameter indicating the dimensions of the area to which the scan is applied (scan area), a parameter indicating the shape of the scan area, and a parameter indicating the position of the scan area. The scan pattern indicates the shape of the scan path, and examples thereof include a Lissajous pattern, a line pattern, a cross pattern, a radial pattern, and a raster pattern. The scan speed may be defined, for example, as the repetition rate of the A-scans. The number of scan points may be defined, for example, as the number of scan points included in the entire scan pattern or the number of scan points included in a portion of the scan pattern. As an example of the latter, the number of scan points for a Lissajous scan may be defined as the number of scan points included in one cycle. The scan interval may be defined, for example, as the interval between adjacent A-scans (i.e., the arrangement interval between scan points) or the distribution density of the scan points. The dimensions of the scanning area may be defined, for example, as a distance in real space (e.g., centimeters) or as a driving range (deflection angle range) of the optical scanner 44. The shape of the scanning area may be defined, for example, as a shape in real space or as a driving range in the x direction and a driving range in the y direction of the optical scanner 44. The position of the scanning area may be defined, for example, as a partial area of ​​the maximum scanning area or a partial range of the maximum driving range of the optical scanner 44.

[0085] Similar to the conventional techniques disclosed in Patent Documents 1 to 3 and Chen, the "Lissajous scan" of this embodiment may be not only a "narrowly defined" Lissajous scan whose path is a pattern (Lissajous pattern, Lissajous figure, Lissajous curve, Lissajous function, Bowditch curve) formed by the locus of points obtained by an ordered pair of two mutually perpendicular simple harmonic motions, but also a "broadly defined" Lissajous scan that follows a predetermined two-dimensional pattern including a series of cycles.

[0086] The optical scanner 44 of this embodiment includes, for example, a first galvanometer mirror that deflects the measurement light LS in the x direction and a second galvanometer mirror that deflects the measurement light LS in the y direction. Lissajous scanning is achieved by controlling the first galvanometer mirror so that the deflection direction along the x direction repeatedly changes in a first period, while controlling the second galvanometer mirror so that the deflection direction along the y direction repeatedly changes in a second period. Here, the first period and the second period are different from each other.

[0087] For example, the Lissajous scan of this embodiment may not only be a scan of a narrowly defined Lissajous pattern obtained by combining two sine waves, but also a scan of a pattern obtained by adding a specific term (e.g., an odd-order polynomial) to a sine wave, or a scan of a pattern based on a triangular wave.

[0088] A "cycle" generally refers to an object consisting of a plurality of sampling points having a certain length. The cycle in this embodiment may be, for example, a closed curve or an almost closed curve (a substantially closed curve, an approximately closed curve). In other words, the start point and end point of the cycle in this embodiment may coincide or nearly coincide.

[0089] Typically, the scanning protocol 2121 is set based on the Lissajous function. As shown in Chen's equation (9), the Lissajous function can be expressed, for example, by the following system of parametric equations (x(t i ), y(t i )) is expressed as: x(t i )=A·cos(2π·(f A / n)·t i ), y(t i )=A·cos(2π·(f A (n-2) / n 2 )·t i ).

[0090] Here, "x" is the horizontal axis of the two-dimensional coordinate system in which the Lissajous curve is defined, "y" is the vertical axis, and "t i” is the acquisition time of the i-th A-line in the Lissajous scan, “A” is the scan range (amplitude), and “f A " indicates the A-line acquisition rate (scan speed, A-scan repetition rate), and n indicates the number of A-lines in each cycle in the x-direction (horizontal axis).

[0091] An example of the distribution of scan lines (scan pattern) in such an exemplary Lissajous scan is shown in FIG.

[0092] Any pair of cycles included in a Lissajous scan (either narrowly or broadly defined) intersects with each other at at least one point (particularly two or more points). Using such intersections, it is possible to perform registration between pairs of data collected from any pair of cycles in a Lissajous scan, and it is possible to implement the method disclosed in Chen (a combination of an image construction method and a motion artifact correction method). Unless otherwise specified, the following description will be made in the context of applying the method described in Chen. However, it is also possible to apply methods equivalent and / or similar to the method described in Chen, or other methods.

[0093] The control information stored in the storage unit 212 is not limited to the above example. For example, the control information may include information for performing focus control (focus control parameters).

[0094] The focus control parameters are parameters that indicate the content of control over the OCT focusing drive unit 43A. Examples of focus control parameters include a parameter that indicates the focal position of the measurement arm, a parameter that indicates the moving speed of the focal position, and a parameter that indicates the moving acceleration of the focal position. The parameter that indicates the focal position is, for example, a parameter that indicates the position of the OCT focusing lens 43. The parameter that indicates the moving speed of the focal position is, for example, a parameter that indicates the moving speed of the OCT focusing lens 43. The parameter that indicates the moving acceleration of the focal position is, for example, a parameter that indicates the moving acceleration of the OCT focusing lens 43. The moving speed may or may not be constant. The same applies to the moving acceleration.

[0095] Such focus control parameters enable focus adjustment according to the shape of the fundus oculi Ef (typically a concave shape with a deep center and a shallow periphery) and aberration distribution. Focus control is performed, for example, in conjunction with scan control (repeated control of Lissajous scan). This allows motion artifacts to be corrected and high-quality images that are in focus across the entire scan range to be obtained.

[0096] <Scanning control unit 2111> The scanning control unit 2111 controls at least the optical scanner 44 based on the scanning protocol 2121. The scanning control unit 2111 may further control the light source unit 101 in coordination with the control of the optical scanner 44 based on the scanning protocol 2121. The elements operating under the control of the scanning control unit 2111A are not limited to the optical scanner 44 and the light source unit 101, and may be any element among the group of elements that perform optical scanning (data set collection unit). The scanning control unit 2111 is realized by cooperation between hardware including a processor and scanning control software that includes the scanning protocol 2121.

[0097] <Sampling control unit 2112> 4C , which is an exemplary embodiment of the scan control unit 2111, includes a sampling control unit 2112. The sampling control unit 2112 executes control related to the scan sampling described above. The scan sampling of this embodiment is, for example, a Lissajous scan that collects data from multiple portions of the fundus oculi Ef (for example, multiple regions each specified by multiple A-lines, in other words, multiple regions each specified by multiple scan points).

[0098] The sampling control unit 2112 is configured to control the number of samples in a Lissajous scan performed as scan sampling. Each sample is data (or a data set) acquired by the Lissajous scan from a region specified by a corresponding A-line (corresponding scan point).

[0099] The number of samples is the number of data (or data sets) collected in a Lissajous scan from multiple regions defined by multiple A-lines (multiple scan points), and is equal to the number of these A-lines, the number of these scan points, and the number of these regions.

[0100] The number of samples is related to the scan control parameters recorded in the scan protocol 2121. For example, the number of samples in a Lissajous scan is related to the number of cycles, the scan interval, the size of the scan area, etc. With regard to the number of cycles, for example, when the value of a certain parameter (e.g., scan interval, size of the scan area, etc.) is fixed, the number of samples increases as the number of cycles increases. With regard to the scan interval, for example, when the value of a certain parameter (e.g., number of cycles, size of the scan area, etc.) is fixed, the number of samples increases as the scan interval decreases. With regard to the size of the scan area (e.g., area defined by an x-y coordinate system, etc.), for example, when the value of a certain parameter (e.g., number of cycles, scan interval, etc.) is fixed, the number of samples increases as the size of the scan area increases. Similar considerations can be made for other scan control parameters.

[0101] The sampling control unit 2112 is configured to control predetermined elements (predetermined elements of the data set collection unit) for performing optical scanning (Lissajous scanning in this embodiment) to change the number of samples in sampling for constructing image data. This control may include, for example, any one or more of control of the light source unit 101, control of the optical scanner 44, control of the OCT focusing driver 43A, control of the retroreflector driver 41A, control of the retroreflector driver 114A, and control of the detector 125. The sampling control unit 2112 can change the number of scan points in optical scanning through such control, and as a result, can change the number of samples in sampling for constructing image data. The sampling control unit 2112 provides an exemplary embodiment of a first sampling control unit.

[0102] In some exemplary embodiments, the sampling control unit 2112 may be configured to control the dataset collection unit to change the spacing between scan points in the optical scan (distribution density of scan points). Also, in some exemplary embodiments, the sampling control unit 2112 may be configured to control the dataset collection unit to change the number of cycles included in a series of cycles in the optical scan. Also, in some exemplary embodiments, the sampling control unit 2112 may be configured to control the dataset collection unit to change the dimensions of the scan area to which the optical scan is applied. These exemplary controls may include, for example, changing the values ​​of corresponding scan control parameters.

[0103] The manner of control performed by the sampling control unit 2112 is not limited to the exemplary control described above, and may include any control for changing the number of scan points in optical scanning (and therefore for changing the number of samples in sampling for constructing image data).

[0104] The scanning control unit 2111A causes the data set acquisition unit to perform optical scanning in accordance with the control executed by the sampling control unit 2112 (for example, a change in the scanning control parameters, that is, a change in the scanning protocol 2121).

[0105] <Image data construction unit 220> The image data constructing unit 220 is configured to construct OCT image data based on the output (detection signal) from the detector 125 of the OCT unit 100. This OCT image data construction includes data sampling, noise removal (noise reduction), filtering, fast Fourier transform (FFT), and the like, similar to conventional Fourier domain OCT (swept-source OCT). When another type of OCT technique is adopted, the image data constructing unit 220 is configured to construct OCT image data by performing known processing corresponding to that OCT type.

[0106] The image data constructing unit 220 constructs image data (A-scan image data) corresponding to each scan point (each A-line) from the detection signal generated by the detector 125. The A-scan image data is obtained by visualizing (imaging) the signal profile (reflection intensity profile, scattering intensity profile) along the depth direction (z direction, optical axis direction, A-line direction).

[0107] In this embodiment, a Lissajous scan is applied to the fundus Ef. The image data constructing unit 220 can construct three-dimensional image data of the fundus Ef by applying, for example, the image construction method and motion artifact correction method disclosed in Chen to the data set collected by the Lissajous scan.

[0108] The image data constructing unit 220 (or the data processing unit 230) can apply rendering to the constructed 3D image data to form an image for display. Examples of applicable rendering methods include volume rendering, surface rendering, maximum intensity projection (MIP), minimum intensity projection (MIP), and multiplanar reconstruction (MPR).

[0109] The image data constructing unit 220 (or the data processing unit 230) can construct an en face OCT image based on the constructed 3D image data. For example, the image data constructing unit 220 (or the data processing unit 230) can construct projection data by projecting the 3D image data in the z direction (A-line direction, optical axis direction, depth direction). The image data constructing unit 220 (or the data processing unit 230) can also construct a shadowgram by projecting partial 3D image data, which is a part of the 3D image data, in the z direction. This partial 3D image data may be set using any segmentation method.

[0110] Segmentation is a process for identifying subregions in an image. For example, segmentation is performed to identify image regions corresponding to one or more tissues (regions) of the fundus oculi Ef. For example, segmentation is performed using thresholding, edge detection, filtering, machine learning (e.g., semantic segmentation), etc.

[0111] The ophthalmic examination apparatus 1 may be capable of performing OCT angiography. OCT angiography, also known as OCT motion contrast imaging, is an imaging technique that constructs an image in which blood vessels are emphasized (see, for example, JP 2015-515894 A). In OCT angiography, the ophthalmic examination apparatus 1 repeatedly scans the same region of the fundus Ef a predetermined number of times. For example, the ophthalmic examination apparatus 1 repeatedly executes the above-described scanning control (repeated control of Lissajous scanning) a predetermined number of times. This allows multiple pieces of three-dimensional data (time-series three-dimensional data sets) to be collected from the application region of the Lissajous scan. The image data constructing unit 220 constructs a motion contrast image from these three-dimensional data sets. This motion contrast image is an angiography image in which temporal changes in interference signals caused by blood flow in the fundus Ef are emphasized, and is three-dimensional angiography image data that represents the three-dimensional distribution of blood vessels in the fundus Ef. The image data constructing unit 220 can construct any two-dimensional angiographic image data and / or any pseudo three-dimensional angiographic image data from this three-dimensional angiographic image data. For example, the image data constructing unit 220 can construct two-dimensional angiographic image data representing any cross section of the fundus Ef by applying multiplanar reconstruction to the three-dimensional angiographic image data. Furthermore, the image data constructing unit 220 can construct frontal angiographic image data of the fundus Ef by applying projection imaging or shadowgramming to the three-dimensional angiographic image data.

[0112] The image data constructor 220 is realized by cooperation of hardware including a processor and image construction software. An exemplary embodiment of the image data constructor 220 is shown in FIG. 4B . The image data constructor 220 of this exemplary embodiment includes a data acquisition system (DAS) 2200. The image data constructor 220 of this exemplary embodiment further includes, as a group of elements for processing a data set acquired by Lissajous scanning, a strip constructor 2210, a mask image generator 2211, a range adjuster 2212, a composite image generator 2213, a cross-correlation function calculator 2214, a correlation coefficient calculator 2215, an xy shift amount calculator 2216, a registration unit 2217, a merge processor 2218, a z shift amount calculator 2220, and an image data corrector 2230.

[0113] The image data construction unit 220 is configured to construct multiple strips based on a data set collected from the fundus Ef in a Lissajous scan, and to construct an image corrected for motion artifacts by applying registration and merging processes to these strips.

[0114] A characteristic of Lissajous scanning is that any two strips have an overlapping area. Similar to the method described in Chen, the image data constructor 220 performs strip-to-strip registration using the overlapping area. The image data constructor 220 orders the multiple strips (first to Nth strips) according to size (e.g., area) and designates the first strip, which is the largest strip, as the initial reference strip. Next, the image data constructor 220 registers the second strip using the first strip as a reference and merges (combines) the first and second strips. The image data constructor 220 registers the third strip using the resulting merged strip as a reference strip and merges the merged strip with the third strip. By sequentially performing these registration and merging processes in the above order, the first to Nth strips are aligned and stitched together, and an image in which motion artifacts have been corrected is obtained.

[0115] In such registration, a cross-correlation function is used to determine the relative position of a reference strip relative to other strips. However, since the strips can have arbitrary shapes, the correlation between the strips is calculated using a mask that treats each strip as an image of a specific shape (e.g., a square) (see Appendix A of Chen).

[0116] The strip is an intensity image of a predetermined gradation, and the mask image is a binary image. Therefore, the difference between the absolute values ​​of the pixel values ​​of the strip and the mask becomes large, which may result in the effect of the mask being ignored in the correlation calculation using the strip and the mask, resulting in an inaccurate correlation coefficient. This problem becomes particularly pronounced when single-precision floating-point (float) calculations are used to calculate the correlation coefficient between strips due to cost considerations, etc., due to the influence of rounding errors caused by the limited number of significant digits. This rounding error problem is resolved by the processing executed by the image data construction unit 220, which will be described later.

[0117] <Data Collection System 2200> The data acquisition system 2200 digitizes (samples and quantizes) the detection signal input from the detector 125 .

[0118] A clock KC is supplied to the data collection system 2200 from the light source unit 101. The clock KC is generated in the light source unit 101 in synchronization with the output timing of each wavelength swept within a predetermined wavelength range by the wavelength-tunable light source. The light source unit 101, for example, branches the light L0 of each output wavelength to generate two branched lights, optically delays one of these branched lights, combines these branched lights, detects the obtained combined light, and generates the clock KC based on the detection result.

[0119] The data collection system 2200 measures the continuous signal (detection signal) input from the detector 125 at regular intervals based on this clock KC, thereby collecting it as a discrete signal. In other words, the data collection system 2200 performs sampling of the detection signal using this clock KC.

[0120] Furthermore, the data collection system 2200 generates a digital signal by applying quantization to the signal obtained by this sampling. The data collection system 2200 outputs this digital signal (or a digital signal obtained by applying predetermined signal processing to this digital signal). The output from the data collection system 2200 is input to the strip construction unit 2210.

[0121] <Strip Construction Unit 2210> The strip builder 2210 builds multiple strips based on the digital signals generated by the data acquisition system 2200. As described in Chen, the strip builder 2210 divides the volume (three-dimensional data) acquired by the Lissajous scan into multiple sub-volumes that do not involve relatively large motion, and builds a front projection image of each sub-volume. This front projection image is a strip.

[0122] Although details will be described later, an image in which motion artifacts have been corrected is obtained by applying registration and merging processes to the multiple strips obtained in this manner. In the example described below, one of any two strips is designated as a reference strip, and registration is performed so that the other strip (registering strip) is aligned with this reference strip, but the method of constructing image data is not limited to this.

[0123] <Mask image generation unit 2211> The mask image generator 2211 generates a reference mask image corresponding to the reference strip and a target mask image corresponding to the target strip. Some examples of the mask images are described below, but the present invention is not limited to these.

[0124] The contour shape of the mask image is, for example, rectangular, typically square. The shape of the reference mask image and the shape of the target mask image may be the same. Furthermore, the dimensions of the reference mask image and the dimensions of the target mask image may be the same.

[0125] The range of pixel values ​​of the mask image is set to be included in, for example, the closed interval [0, 1]. Typically, the mask image may be a binary image with pixel values ​​of 0 or 1. As a specific example, the mask image is a binary image in which pixels in an area corresponding to the domain of a strip have a value of 1 and other pixels have a value of 0. In other words, as shown in Chen's equation (20), pixel values ​​of an exemplary mask image have a value of 1 in the image area of ​​the corresponding strip and a value of 0 in other areas.

[0126] <Range Adjustment Unit 2212> The range adjuster 2212 is configured to adjust the pixel value range of the reference strip and the pixel value range of the target strip based on the pixel value range of the reference mask image and the pixel value range of the target mask image. Typically, the range adjuster 2212 adjusts the pixel value range of the reference strip and the pixel value range of the target strip so as to reduce the difference between the pixel value range of the strip and the pixel value range of the mask image.

[0127] In general, the range adjuster 2212 adjusts the pixel value range of the reference strip, the pixel value range of the target strip, and the pixel value range of the mask image relatively. In a typical example, the reference mask image applied to the reference strip and the target mask image applied to the target strip are different, and the range adjuster 2212 adjusts the pixel value range of the reference strip, the pixel value range of the target strip, the pixel value range of the reference mask image, and the pixel value range of the target strip relatively.

[0128] The range adjustment unit 2212 is configured to adjust the pixel value range of the reference strip and the pixel value range of the reference mask image so as to reduce the pixel value range of the reference strip and the pixel value range of the reference mask image, and to relatively adjust the pixel value range of the target strip and the pixel value range of the target strip so as to reduce the pixel value range of the target strip and the pixel value range of the target mask image.

[0129] The range adjustment unit 2212 may be configured to adjust the pixel value range of the strip and the pixel value range of the mask image so that the pixel value range of one of the strip and the mask image matches the pixel value range of the other. For example, the range adjustment unit 2212 may be configured to adjust the pixel value range of the reference strip and the pixel value range of the reference mask image so that the pixel value range of the reference strip and the pixel value range of the reference mask image match, and to relatively adjust the pixel value range of the target strip and the pixel value range of the target strip so that the pixel value range of the target strip and the pixel value range of the target mask image match.

[0130] For example, the range adjuster 2212 is configured to normalize the range of pixel values ​​of the strip according to the range of pixel values ​​of the mask image, some examples of this normalization (standardization) are described below, but are not limited to these.

[0131] A first example of normalization will be described. When the range of pixel values ​​of the mask image is included in the closed interval [0, 1], the range adjustment unit 2212 divides the value of each pixel in the strip by the maximum pixel value in the strip. In this example, the range adjustment unit 2212 first compares the values ​​of all pixels in the strip to identify the maximum value (maximum pixel value), and then divides the value of each pixel in the strip by the maximum pixel value. This causes the range of pixel values ​​of the strip to match the closed interval [0, 1], the same as the range of pixel values ​​of the mask image.

[0132] A second example of normalization will be described. When the range of pixel values ​​of the mask image is included in the closed interval [0, 1], the range adjustment unit 2212 divides the value of each pixel of the strip by the maximum value of the range of pixel values ​​of this strip. The range of pixel values ​​of the strip is set in advance, and the range adjustment unit 2212 divides the value of each pixel of the strip by the upper limit (maximum value) of this range. In this example, the range of pixel values ​​of the strip is also matched to the same closed interval [0, 1] as the range of pixel values ​​of the mask image.

[0133] The processing performed by the range adjustment unit 2212 can reduce the difference between the absolute values ​​of the pixel values ​​of the strip and the absolute values ​​of the pixel values ​​of the mask, so that the effect of the mask is not ignored in the correlation calculation using the strip and the mask, and it becomes possible to accurately calculate the correlation coefficient. In particular, even when single-precision floating-point (float) calculation is used, it is possible to eliminate (reduce) the influence of rounding errors caused by a small number of significant digits.

[0134] Although this specification mainly describes an example of changing only the range of pixel values ​​of the strip, it is also possible to change only the range of pixel values ​​of the mask image, or to change both the range of pixel values ​​of the strip and the range of pixel values ​​of the mask image.

[0135] <Synthetic Image Generation Unit 2213> For the strips and mask images to which the pixel value range adjustment by the range adjustment unit 2212 has been applied, the composite image generation unit 2213 generates two composite images by combining the mask image with the reference strip and the target strip, respectively. Typically, the composite image generation unit 2213 combines the reference mask image with the reference strip to generate a reference composite image, and combines the target mask image with the target strip to generate a target composite image.

[0136] The process of combining the strips and the mask image may be performed in the same manner as Chen, except that, unlike Chen's approach, the present embodiment adjusts to reduce the difference between the pixel value range of the strip and the pixel value range of the mask image. Typically, the pixel value ranges of the reference strip and the target strip are normalized to match the pixel value ranges of the reference mask image and the target mask image.

[0137] For example, in the same manner as Chen's equation (19), the composite image generator 2213 may be configured to embed the strip with the normalized pixel value range into an image of the same size and shape as the mask image.

[0138] Furthermore, the composite image generating unit 2213 generates a composite image of the embedded image of the strip and the mask image. This composite image is expressed as "f'(r)m f (r)" (page 1800, line 2, etc.), but as mentioned above, the value of the embedded image of the strip is different from that of equation (19).

[0139] <Cross-correlation function calculation unit 2214> The cross-correlation function calculation unit 2214 obtains a plurality of cross-correlation functions based on two synthesized images generated by the synthesized image generation unit 2213. The calculation of the cross-correlation function may be performed in the same manner as Chen. For example, the cross-correlation function calculation unit 2214 calculates six cross-correlation functions (image cross-correlation) included in Chen's equation (33) based on a reference synthesized image generated from a reference strip and a reference mask image and a target synthesized image generated from a target strip and a target mask image.

[0140] <Correlation coefficient calculation unit 2215> The correlation coefficient calculation unit 2215 calculates a correlation coefficient based on the plurality of cross-correlation functions calculated by the cross-correlation function calculation unit 2214. This calculation may be performed according to Chen's equation (33).

[0141] <XY shift amount calculation unit 2216> The XY shift amount calculation unit 2216 calculates the shift amount in the XY direction (lateral direction, horizontal direction) between the reference strip and the target strip based on the correlation coefficient calculated by the correlation coefficient calculation unit 2215.

[0142] For example, the calculation for calculating the XY direction shift amount may include a calculation corresponding to Chen's "rough lateral motion correction" (page 1787). In this case, the XY shift amount calculation unit 2216 is configured to estimate the XY direction shift amount by obtaining the maximum value of the cross-correlation function.

[0143] Furthermore, the XY shift amount calculation unit 2216 may be configured to execute a calculation corresponding to Chen's "fine lateral motion correction" (page 1789) in order to calculate a small shift amount in the lateral direction caused by eye movements such as slow drift and tremor.

[0144] <Registration unit 2217> The registration unit 2217 performs lateral registration based on the lateral shift amount calculated by the xy shift amount calculation unit 2216. For example, this registration may include processing equivalent to Chen's "rough lateral motion correction." The registration unit 2217 is configured to perform registration between the reference strip and the target strip so as to cancel out the lateral shift amount calculated by the xy shift amount calculation unit 2216.

[0145] If the xy shift amount calculation unit 2216 performs a calculation equivalent to Chen's "fine lateral motion correction," the registration unit 2217 can remove small lateral motion artifacts between the reference strip and the target strip by performing a registration equivalent to this "fine lateral motion correction."

[0146] <Merge processing unit 2218> The merge processing unit 2218 constructs a merged image of the reference strip and the target strip whose relative positions have been adjusted by the registration unit 2217. This processing may be performed in the same manner as the method described in Chen.

[0147] As described above, in this example, the above series of processes are sequentially performed on the multiple strips constructed by the image data construction unit 220 in order according to their sizes. As a result, a merged image in which lateral motion artifacts have been corrected is obtained from the multiple strips constructed by the image data construction unit 220. This merged image is typically an image that represents the entire range to which the Lissajous scan has been applied.

[0148] As described above, the plurality of strips are a plurality of front projection images based on a plurality of sub-volumes obtained by dividing the volume (3D data) collected in the resampling scan. Therefore, in this example, the merged image constructed from the plurality of strips provides a plurality of sub-volumes (and their merged images) with lateral position adjustment. In this example, the registration and merging processes in the axial direction (z-direction, A-line direction, optical axis direction, depth direction) orthogonal to the lateral direction are executed by the z-shift amount calculation unit 2220 and the image data correction unit 2230.

[0149] <z-shift amount calculation unit 2220> The z-shift amount calculation unit 2220 calculates the shift amount in the z-direction (A-line direction, optical axis direction, depth direction) between a plurality of sub-volumes obtained by dividing the volume collected in the resampling scan (that is, the plurality of sub-volumes that are the basis of the plurality of strips).

[0150] In this example, after performing the position adjustment in the xy-direction (lateral direction, horizontal direction), the z-shift amount calculation unit 2220 and the image data correction unit 2230 perform the position adjustment in the z-direction. The z-shift amount calculation unit 2220 in this example may be configured to calculate the shift amount in the z-direction using the data (for example, xy-direction shift amount data, merged image) obtained by the processes executed by the mask image generation unit 2211 to the merge processing unit 2218.

[0151] An example of the process executed by the z-shift amount calculation unit 2220 will be described. Similar to the pair of strips (reference strip and target strip) considered in the xy-direction shift amount calculation, a pair of sub-volumes is also considered in the z-direction shift amount calculation. The pair of sub-volumes may be two sub-volumes corresponding to the reference strip and the target strip considered in the xy-direction shift amount calculation, and these sub-volumes are respectively referred to as the reference sub-volume and the target sub-volume.

[0152] Based on the result of the xy-direction registration between the corresponding reference strips and target strips, the reference sub-volumes and target sub-volumes are aligned in the xy-direction. Also, as mentioned above, any two strips in a Lissajous scan overlap (intersect) at four points, and therefore any two sub-volumes also overlap (intersect) at four points.

[0153] The z-shift amount calculation unit 2220 first identifies an intersection area (common area) between the reference sub-volume and the target sub-volume whose positions have been adjusted in the x and y directions. Each intersection area is three-dimensional image data.

[0154] Next, the z-shift amount calculation unit 2220 sets a cross section in the identified intersection area. This cross section is, for example, a plane formed by an arbitrary axis (for example, the x-axis, the y-axis, or an axis obliquely intersecting both the x-axis and the y-axis) in the xy plane and the z-axis. Note that the cross section is not limited to a plane, and may be a curved surface, etc.

[0155] Next, the z-shift amount calculation unit 2220 constructs an image of the set cross section from the reference sub-volume, and also constructs an image of the same cross section from the target sub-volume. The cross-sectional image constructed from the reference sub-volume is called the reference cross-sectional image, and the cross-sectional image constructed from the target sub-volume is called the target cross-sectional image. The reference cross-sectional image and the target cross-sectional image are images that represent the same cross section in the intersection region between the reference sub-volume and the target sub-volume that have been registered in the x- and y-directions.

[0156] Next, the z-shift amount calculation unit 2220 analyzes the reference cross-sectional image to identify an image of a predetermined site of the subject's eye E, and analyzes the target cross-sectional image to identify an image of the same site. This site may be any site, and may be, for example, the surface of the fundus Ef (retinal surface, internal limiting membrane, boundary between the retina and vitreous body). Furthermore, if an artificial object has been implanted in the subject's eye E, an image of this artificial object may be identified. The analysis for identifying the image of the predetermined site may include, for example, segmentation.

[0157] Next, the z-shift amount calculation unit 2220 calculates the z-coordinate of an image (reference image) of a predetermined region identified from the reference cross-sectional image, and calculates the z-coordinate of an image (target image) of a predetermined region identified from the target cross-sectional image. Typically, the image of the predetermined region consists of multiple pixels, and the z-coordinates of these pixels are not constant. For example, the global shape of the retinal surface is generally a curved shape convex in the +z direction, and images of local areas (examples of the reference image and target image) are at least partially tilted with respect to the z-axis. The z-shift amount calculation unit 2220 can calculate the z-coordinate of the image of the predetermined region based on at least one pixel of a group of pixels constituting the image of the predetermined region. For example, a statistic of the z-coordinates can be calculated from the group of pixels, and this statistic can be used as the z-coordinate of the image. This statistic can be any representative value (summary statistic), such as a maximum value, minimum value, mean value, median, mode, or quantile. On the other hand, if the image of the predetermined region consists of a single pixel, the z-coordinate of this pixel can be used as the z-coordinate of the predetermined region.

[0158] Next, the z-shift amount calculation unit 2220 calculates the difference between the z-coordinate of the reference image and the z-coordinate of the target image (the shift amount in the z direction). In some exemplary aspects, processing control can be performed so that correction processing is performed by the image data correction unit 2230 when the z-direction shift amount exceeds a threshold. This threshold is, for example, zero or a positive value, and may be a preset fixed value or a variable value.

[0159] In the above example, the z-direction shift amount is calculated by constructing two-dimensional image data (cross-sectional images) from three-dimensional image data (sub-volumes), but in some exemplary aspects, the z-direction shift amount may be calculated from three-dimensional image data without constructing two-dimensional image data. In this case, the same processing as that performed on the pair of reference cross-sectional images and target cross-sectional images can be performed on the pair of reference sub-volumes and target sub-volumes.

[0160] In the above example, two-dimensional image data (cross-sectional image) is constructed from three-dimensional image data (subvolume), and an image of a specified area is identified from this two-dimensional image data to determine the amount of shift in the z direction. However, in some exemplary embodiments, an image of a specified area may be identified from the three-dimensional image data, and two-dimensional image data of the image of this specified area may be constructed to determine the amount of shift in the z direction.

[0161] The z-shift amount calculation unit 2220 may be configured to calculate the z-direction shift amount between the reference subvolume and the target subvolume based on a correlation coefficient calculated based on a pair of the reference subvolume and the target subvolume. The method for calculating the correlation coefficient between the subvolumes may be the same as the correlation coefficient calculation method executed by the correlation coefficient calculation unit 2215, for example.

[0162] The method for calculating the z-direction shift amount is not limited to the above-mentioned methods, and may be any method applicable to a pair of a reference subvolume and a target subvolume, or may be any method applicable to a pair of an object other than a subvolume. An example of an object other than a subvolume is a rendered image of the subvolume (an image having a dimension in the z direction, such as an image projected in the x direction or y direction).

[0163] <Image data correction unit 2230> The image data correction unit 2230 is configured to apply z-direction position adjustment based on the z-direction shift amount acquired by the z-shift amount calculation unit 2220 to the multiple sub-volumes whose positions have been adjusted in the x and y directions by the mask image generation unit 2211 to the merge processing unit 2218.

[0164] Similar to the registration unit 2217 that performs registration based on the xy direction shift amount, the image data correction unit 2230 performs registration between the reference subvolume and the target subvolume so as to cancel out the corresponding z direction shift amount obtained by the z shift amount calculation unit 2220.

[0165] As mentioned above, in some exemplary embodiments, the image data corrector 2230 may be controlled to perform registration between the reference sub-volume and the target sub-volume only if the corresponding z-direction shift exceeds a threshold.

[0166] The image data obtained as a result of the position adjustment by the image data corrector 2230 is a group of subvolumes that have been registered in all of the x-, y-, and z-directions, i.e., a group of subvolumes that have been three-dimensionally registered. The group of subvolumes before applying such registration is a volume acquired by Lissajous scanning. The data processor 230 recombines the group of subvolumes obtained by three-dimensional registration to obtain a volume to which three-dimensional registration has been applied.

[0167] The 3D registered dataset can then be used for any processing (image processing, post-processing, analysis, evaluation, visualization, rendering, etc.) This allows the desired processing to be performed using a 3D dataset that has been corrected for motion artifacts with higher accuracy and precision than ever before.

[0168] In addition, the z-shift amount calculation unit 2220 and the image data correction unit 2230 may be configured to perform registration equivalent to Chen's "axial motion correction (rough axial motion correction and / or fine axial motion correction)" (pages 1789 to 1790) in order to remove motion artifacts in the z direction.

[0169] <Data processing unit 230> The data processing unit 230 is configured to apply various types of data processing and is realized by cooperation between hardware including a processor and data processing software.

[0170] The data processing performed by the data processing unit 230 may be any data processing, such as image processing, image analysis, numerical analysis, calculation, control, machine learning, mathematical optimization, statistical calculation, exploratory data analysis (such as data mining), machine perception, natural language processing, syntactic pattern recognition, search, diagnostic support, bioinformatics processing, brain-machine interface processing, chemoinformatics processing, voice recognition, character recognition, object recognition, computer vision, software engineering processing, etc.

[0171] The image data processed by the data processing unit 230 may be any image data, such as image data generated by the image data construction unit 220, image data generated by the fundus camera unit 2, any OCT image data, any observation image data, any photographed image data, image data acquired by any modality, image data generated through any image processing, image data generated using computer graphics, image data generated using an artificial intelligence engine (e.g., a neural network) trained by machine learning, or image data recorded in electronic medical record data (e.g., schematic diagrams, illustrations).

[0172] <User Interface 240> The user interface 240 includes a display unit 241 and an operation unit 242. The display unit 241 includes the display device 3. The operation unit 242 includes various operation devices and input devices. The user interface 240 may include a device that combines a display function and an operation function, such as a touch panel. It is also possible to construct an embodiment that does not include at least a part of the user interface 240. For example, the display device may be an external device connected to the ophthalmic examination apparatus 1.

[0173] <Data Receiving Unit 250> The data receiving unit 250 acquires data from an external device. This external device may be, for example, a computer, a storage device, a recording medium, or an information system (for example, a hospital information system, an electronic medical record system, or an image archiving system). The external device may be, for example, a device directly connected to the ophthalmic examination apparatus 1, a device connected to the ophthalmic examination apparatus 1 via a local area network (LAN), or a device connected to the ophthalmic examination apparatus 1 via a wide area network (WAN).

[0174] The data receiving unit 250 may include, for example, a communication interface, a drive device, etc. The data receiving unit 250 may also include a scanner for reading data recorded on paper sheets, etc. The data receiving unit 250 may also include an input device for a user to input data. The input device may be a keyboard, a pen tablet, etc.

[0175] <Operation> The operation of the ophthalmic examination apparatus 1 will now be described. The operation described here is merely an example. For example, some exemplary embodiments may be configured to execute at least some of the steps in the operational example according to the present disclosure. In some exemplary embodiments, at least some of the steps in the operational example according to the present disclosure may be replaced with other steps. In some exemplary embodiments, any step may be combined with at least some of the steps in the operational example according to the present disclosure.

[0176] <First operation example> An example of the process of constructing image data from a data set acquired by Lissajous scanning will be described with reference to Figures 6A to 6E. The image data construction in this example includes motion artifact correction. Note that prior to step S1, preparatory operations similar to those in the conventional method are performed, such as entering a patient ID, setting the scanning mode (specifying Lissajous scanning), presenting a fixation target, alignment, focus adjustment, and OCT optical path length adjustment.

[0177] (S1: Lissajous Scan) Upon receiving a predetermined scan start trigger signal, the scan control unit 2111 starts applying an OCT scan (Lissajous scan) to the subject's eye E (fundus oculi Ef). This Lissajous scan is an example of the above-mentioned scan sampling. The number of samples in this Lissajous scan may be a value preset by the sampling control unit 2112 (or the user) or may be a default value.

[0178] The scanning start trigger signal is automatically generated, for example, in response to the completion of a predetermined preparatory operation (alignment, focus adjustment, OCT optical path length adjustment, etc.), or in response to a scanning start instruction operation being performed using the operation unit 242.

[0179] The scan control unit 2111 applies a Lissajous scan to the fundus Ef by controlling the optical scanner 44, the OCT unit 100, etc. in accordance with a scan protocol 2121 (a protocol corresponding to the Lissajous scan). The data set (analog data set) collected by this Lissajous scan is sent to the image data construction unit 220.

[0180] (S2: Building multiple strips) The data acquisition system 2200 of the image data constructor 220 converts the analog data set collected in step S1 into a digital data set, and the strip constructor 2210 constructs a plurality of strips based on this digital data set.

[0181] (S3: Set the reference strip and target strip) The image data constructing unit 220 orders the multiple strips constructed in step S2 according to their dimensions (area, etc.). In this example, the number of multiple strips constructed in step S2 is set to N (N is an integer equal to or greater than 2). Furthermore, according to the order specified by the ordering, these N strips are referred to as the first strip, second strip, ..., Nth strip. Furthermore, any strip from the first to Nth strips may be referred to as the nth strip (n = 1, 2, ..., N). In this way, the first strip is the largest strip, the second strip is the second largest strip, the nth strip is the nth largest strip, and the Nth strip is the smallest strip.

[0182] In this example, the image data constructor 220 sets the first strip as the initial reference strip and the second strip as the initial target strip.

[0183] The reference strip and the target strip correspond to the arbitrary shaped images f(r) and g(r), respectively, in Appendix A of Chen.

[0184] (S4: Set the reference mask image and the target mask image) The mask image generation unit 2211 generates a mask image (reference mask image) corresponding to the reference strip and a target mask image corresponding to the target strip.

[0185] At this stage, the mask image generation unit 2211 generates two mask images corresponding to the first strip and the second strip, respectively. The image data construction unit 220 sets the first mask image corresponding to the first strip as an initial reference mask image, and sets the second mask image corresponding to the second strip as an initial target mask image.

[0186] The reference mask image and the target mask image are rectangular shaped binary image masks m in Appendix A of Chen. f (r) and m g Equivalent to (r).

[0187] (S5: Normalize the reference strip and the target strip) The range adjustment unit 2212 normalizes the reference strip and target strip set in step S3 in the manner described above. The strips are normalized according to the range of pixel values ​​in the mask image. At this stage, the range adjustment unit 2212 applies normalization to the first strip (reference strip) and the second strip (target strip). Note that the process performed by the range adjustment unit 2212 is not limited to normalization, and may be any of the range adjustment processes described above or a process similar thereto.

[0188] In this example, the pixel value range of each mask image is assumed to be in the closed interval [0, 1]. In particular, each mask image in this example is assumed to be a binary image in which the pixel values ​​within the region corresponding to the domain of the corresponding strip are set to 1 and the other pixel values ​​are set to 0.

[0189] The range adjustment unit 2212 normalizes the strip, for example, by dividing the value of each pixel in the strip by the maximum pixel value in the strip, or by dividing the value of each pixel in the strip by the maximum value in the range of pixel values ​​(tone range) of the strip.

[0190] Furthermore, the composite image generator 2213 embeds the strip with the normalized pixel value range into an image with the same size and shape as the corresponding mask image. The embedded image of the normalized first strip f(r) is similar to the rectangular shaped image f'(r) in Appendix A of Chen, but the absolute value of the value range within the image area of ​​the first strip f(r) (|f(r)|) is normalized to 1 or less. This embedded image is also denoted as f'(r).

[0191] Similarly, the embedded image of the normalized second strip g(r) is an image similar to the rectangular image g'(r), but the absolute value of the range within the image area of ​​the second strip g(r) (|g(r)|) is normalized to be less than or equal to 1. This embedded image is also denoted as g'(r).

[0192] (S6: Generate a reference composite image and a target composite image) The composite image generator 2213 generates a composite image of the embedded image of the normalized strip and the corresponding mask image.

[0193] At this stage, the composite image generation unit 2213 generates a composite image of the embedded image of the normalized first strip (reference strip) and the first mask image (reference mask image), and also generates a composite image of the embedded image of the normalized second strip (target strip) and the second mask image (target mask image). The former composite image is called the reference composite image, and the latter is called the target composite image.

[0194] Here, the reference composite image and the target composite image are the combination of two rectangle-shaped images f´(r)m in Appendix A of Chen, respectively. f (r) and g´(r)m g(r), where, as mentioned above, the absolute value of the range of the first strip f(r) in the image area (|f(r)|) is less than or equal to 1, and the absolute value of the range of the second strip g(r) in the image area (|g(r)|) is less than or equal to 1.

[0195] Image 311 in Figure 7A is an example of an embedded image f'(r) of the normalized first strip f(r), and image 321 is an example of a first mask image. Combining these two images 311 and 321 produces a reference composite image f'(r)m f Similarly, image 312 in FIG. 7B is an example of an embedded image g'(r) of the normalized second strip g(r), and image 322 is an example of a second mask image. Combining these two images 312 and 322 results in a reference composite image g'(r)m g (r) is obtained.

[0196] (S7: Calculate multiple cross-correlation functions) The cross-correlation function calculation unit 2214 calculates a plurality of cross-correlation functions based on the reference composite image and the target composite image generated in step S6. In this example, the cross-correlation function calculation unit 2214 calculates six cross-correlation functions included in Chen's equation (33) based on the reference composite image and the target composite image generated in step S6.

[0197] (S8: Calculate the correlation coefficient) The correlation coefficient calculation unit 2215 calculates a correlation coefficient based on the multiple cross-correlation functions calculated in step S7. In this example, the correlation coefficient calculation unit 2215 calculates the correlation coefficient (ρ(r')) from the multiple cross-correlation functions calculated in step S7 according to Chen's equation (33).

[0198] (S9: Record the correlation coefficient) The image data constructing unit 220 (or the control unit 210) records the correlation coefficient (ρ(r')) calculated in step S8. For example, the image data constructing unit 220 records this correlation coefficient and a corresponding identifier (position information) in association with each other. This identifier may be, for example, any of the coordinates in the definition coordinate system of the image data, the cycle number, the scan number, and the strip number. By repeating steps S3 to S14, pairs of correlation coefficients and position information are accumulated.

[0199] (S10: Calculate the shift amount in the x and y directions between the reference strip and the target strip) The xy shift amount calculation unit 2216 calculates the amount of shift in the xy directions between the first strip (reference strip) f(r) and the second strip (target strip) g(r) based on the correlation coefficient calculated in step S8. In this example, the relative amount of shift in the xy directions (Δx, Δy) between the reference strip f(r) and the target strip g(r) is found by detecting the peak of the correlation coefficient ρ(r') calculated in step S8.

[0200] (S11: Save the shift amount in the x and y directions) The x and y direction shift amounts calculated for the strip pair in step S10 are stored in the storage unit 212 (and / or another storage device). The x and y direction shift amounts may be recorded together with time information corresponding to the strip pair. This time information may be time parameters corresponding to the Lissajous scan or information based thereon, or sequence information regarding the Lissajous scan or information based thereon. Examples of time information include cycle number, scan number, strip number, etc. By repeating steps S3 to S13, pairs of x and y direction shift amounts and time information are accumulated.

[0201] (S12: Perform registration between the reference strip and the target strip) The registration unit 2217 applies x- and y-direction registration (rough lateral motion correction) to the reference strip and the target strip based on the x- and y-direction shift amounts calculated in step S10. At this stage, registration between the first strip f(r) and the second strip g(r) is performed.

[0202] Furthermore, the registration unit 2217 may apply any xy-direction registration, such as the above-mentioned "fine lateral motion correction," to the reference strip and the target strip.

[0203] (S13: Construct a merged image of the reference strip and the target strip) The merge processing unit 2218 constructs a merged image of the reference strip and the target strip whose relative positions have been adjusted by the registration in step S12. Image 330 in Figure 7C shows an example of a merged image of the first strip f(r) and the second strip g(r).

[0204] Here, an example of implementing the processes in steps S7 to S13 will be described. First, f'(r)m f (r), g´(r)m g (r), m f (r), m g (r), (f´(r)m f (r)) 2 , and (g´(r)m g (r)) 2 Set the imaginary part of each of these to 0, leaving only the real part.

[0205] Next, six real-valued functions (real functions) f´(r)m f (r), g´(r)m g (r), m f (r), m g (r), (f´(r)m f (r)) 2 , and (g´(r)m g (r))2 A fast Fourier transform (FFT) is applied to each of the

[0206] Next, based on the six functions obtained by these fast Fourier transforms, the six cross-correlation functions shown in step S7 of FIG. 6A are derived.

[0207] An inverse fast Fourier transform (IFFT) is then applied to each of the six derived cross-correlation functions.

[0208] Next, the correlation coefficient ρ(r') of Chen's equation (33) is calculated.

[0209] Then, the relative shift amount (Δx, Δy) between the reference strip f(r) and the target strip g(r) is calculated by identifying the peak position of the correlation coefficient ρ(r'), and registration and merging processes between the reference strip f(r) and the target strip g(r) are performed based on this shift amount.

[0210] By applying this series of processes to the N strips in turn, merged images of all N strips can be obtained. In addition, the xy-direction shift amounts (Δx, Δy) calculated for each strip pair can be recorded in association with time information.

[0211] (S14: Have you processed all the strips?) A series of processes from steps S3 to S13 are executed for all of the N strips obtained in step S2, in the order described above.

[0212] When N is 3 or more, if a merged image of the first strip and the second strip is created in step S13 (S14: No), the process returns to step S3. In step S3, the merged image of the first strip and the second strip is set as a new reference strip, and the third strip is set as a new target strip. By performing the processes of steps S4 to S13 based on the new reference strip and the new target strip, a merged image of the new reference strip and the new target strip is obtained. This new merged image is a merged image of the first to third strips. By sequentially applying this series of processes to the N strips, merged images of all N strips are obtained (S14: Yes).

[0213] (S15: Save the image with the xy motion artifacts corrected) The merged image finally obtained by the above-described repetitive processing is an image in which motion artifacts in the x and y directions have been corrected, and is an image that represents the entire application range of the Lissajous scan in step S1. The main control unit 211 can store this final merged image in the storage unit 212 (and / or other storage device).

[0214] The image data constructing unit 220 (or the data processing unit 230) can use the result of the registration based on the N strips to register the data (three-dimensional data) collected in step S1 and / or three-dimensional image data constructed from this three-dimensional data. That is, the image data constructing unit 220 (or the data processing unit 230) can use the finally obtained merged image to register the three-dimensional data or three-dimensional image data. This registration includes a process of converting the coordinate system defining the Lissajous scan into a three-dimensional Cartesian coordinate system (x-y-z coordinate system). This coordinate conversion corresponds to "remapping" in Chen's term. In this way, three-dimensional image data (volume) in which x- and y-direction motion artifacts have been corrected is obtained. The main control unit 211 can store this x- and y-direction motion artifact-corrected volume in the storage unit 212 (and / or another storage device) together with or instead of the finally obtained merged image.

[0215] (S16: Select the reference strip) This operation example proceeds to processing for correcting z-direction motion artifacts. In z-direction motion artifact correction, first, the z-shift amount calculation unit 2220 selects one strip (reference strip) from multiple strips corresponding to the volume for which x- and y-direction motion artifact correction has been performed. The reference strip selected here may be the first strip selected in step S3 of the first iteration, or a strip different from this.

[0216] (S17: Select the target strip) Next, the z-shift amount calculation unit 2220 selects one strip (target strip) other than the reference strip selected in step S16 from the multiple strips corresponding to the volume in which the x- and y-direction motion artifacts have been corrected. The reference strip selected here may be the second strip selected in step S3 the first time, or may be a strip other than this.

[0217] (S18: Set a reference sub-volume corresponding to the reference strip) Next, the z-shift amount calculation unit 2220 sets the sub-volume corresponding to the reference strip selected in step S16 as the reference sub-volume. Here, the front projection image of the reference sub-volume is the reference strip.

[0218] (S19: Set the target subvolume corresponding to the target strip) Similarly, the z-shift amount calculation unit 2220 sets the sub-volume corresponding to the target strip selected in step S17 as the target sub-volume. Here, the front projection image of the target sub-volume is the target strip.

[0219] (S20: Identifying the intersection region between the reference subvolume and the target subvolume) Next, the z-shift amount calculation unit 2220 identifies the intersection area (common area) between the reference sub-volume set in step S18 and the target sub-volume set in step S19.

[0220] As described above, there are four intersection regions between the two sub-volumes. The z-shift amount calculation unit 2220 identifies one or more intersection regions. When two or more intersection regions are identified, the following step S21 is executed for each of the identified intersection regions.

[0221] (S21: Calculate the z-direction shift amount between the reference subvolume and the target subvolume) Next, the z-shift amount calculation unit 2220 calculates the amount of shift in the z direction between the reference subvolume and the target subvolume based on the intersecting region between the subvolumes identified in step S20.

[0222] For example, the z-shift amount calculation unit 2220 sets a cross section (cross section of interest) in the intersection region identified in step S20. The cross section of interest may be any cross section in the intersection region. Next, the z-shift amount calculation unit 2220 constructs an image of the cross section of interest (reference cross section image) from the reference sub-volume, and constructs an image of the cross section of interest (target cross section image) from the target sub-volume. Next, the z-shift amount calculation unit 2220 analyzes the reference cross section image to identify an image of a predetermined portion of the subject's eye E (reference image), and analyzes the target cross section image to identify an image of the same portion (target image). Next, the z-shift amount calculation unit 2220 obtains the z coordinate of the reference image and the z coordinate of the target image, and calculates the difference between these two z coordinates. In this example, the calculated difference is used as the z-direction shift amount between the reference sub-volume and the target sub-volume.

[0223] A specific example is shown in FIG. 8. Reference numeral 401 denotes the intersection state between a strip 402 corresponding to the reference subvolume and a strip 403 corresponding to the target subvolume. In this example, attention is focused on the intersection region surrounded by a white circle. The diameter of the white circle along the x direction (shown by a dotted line) is the cross section of interest. The two strips 402 and 403 also respectively show intersection regions and cross sections of interest. The z-shift amount calculation unit 2220 constructs an image of this cross section of interest (reference cross section image) 412 from the reference subvolume corresponding to the strip 402, and constructs an image of this cross section of interest (target cross section image) 413 from the target subvolume corresponding to the strip 403. Furthermore, the z-shift amount calculation unit 2220 analyzes the reference cross section image 412 to identify the z position (z coordinate) 422 of the image of the retinal surface, and analyzes the target cross section image 413 to identify the z position (z coordinate) 423 of the image of the retinal surface. In addition, the z-shift amount calculation unit 2220 calculates the difference Δz between two z positions (two z coordinates) 422 and 423 identified from the two cross-sectional images 412 and 413, respectively, as the z-direction shift amount between the reference subvolume and the target subvolume.

[0224] The method for calculating the z-direction shift amount between the reference subvolume and the target subvolume is not limited to this, and any method that utilizes their intersection area may be used. For example, as described above, the z-shift amount calculation unit 2220 may calculate a correlation coefficient between the reference subvolume and the target subvolume and determine the z-direction shift amount based on this correlation coefficient.

[0225] As in step S9 of FIG. 6B, the image data constructing unit 220 (or the control unit 210) records the correlation coefficient calculated for each subvolume pair. For example, the image data constructing unit 220 (or the control unit 210) associates the correlation coefficient obtained in the calculation of the z-direction shift amount with a corresponding identifier (position information) and records them. This identifier may be any of the coordinates in the definition coordinate system of the image data, the cycle number, the scan number, the strip number, the subvolume number, and the merge process number. By repeating steps S17 to S25, pairs of correlation coefficients and position information are accumulated. The image data constructing unit 220 (or the control unit 210) can associate the correlation coefficients in the x and y directions recorded in step S9 with the correlation coefficients in the z direction recorded in step S21 via the identifiers (position information). This makes it possible to obtain three-dimensional correlation coefficients.

[0226] (S22: Save the z-direction shift amount) The z-direction shift amount calculated for the subvolume pair in step S21 is stored, for example, in the storage unit 212. Similar to storing the xy-direction shift amount (step S11), the z-direction shift amount may be recorded, for example, together with time information corresponding to the subvolume pair.

[0227] (S23: Perform registration between the reference subvolume and the target subvolume) The image data correcting unit 2230 applies registration in the z direction to the reference sub-volume and the target sub-volume based on the z-direction shift amount calculated in step S21.

[0228] This registration is a process of adjusting the relative positions in the z direction between the reference sub-volume and the target sub-volume so as to cancel out the z-direction shift amount Δz in Figure 8, that is, so that the image of the retinal surface in the reference cross-sectional image 412 and the image of the retinal surface in the target cross-sectional image 413 are located at the same z position (equal z coordinate).

[0229] (S24: Construct a merged image of the reference subvolume and the target subvolume) The image data corrector 2230 constructs a merged image of the reference subvolume and the target subvolume whose relative positions have been adjusted in the z direction by the registration in step S23, thereby obtaining a merged image of the reference subvolume and the target subvolume whose relative positions have been adjusted in the xy and z directions.

[0230] (S25: Have all subvolumes been processed?) A series of processes from steps S17 to S25 are executed for all sub-volumes in a predetermined order (for example, the order assigned to the first to Nth strips) (S25: No). In this example, the merged image constructed in step S24 is set as the reference strip in the next routine. By applying this series of processes to all sub-volumes in turn, merged images of all sub-volumes are obtained (S25: Yes).

[0231] (S26: Save the volume with all subvolumes merged) The merged image finally obtained by repeating steps S17 to S25 is an image in which motion artifacts in the x, y, and z directions have been corrected, and is an image that represents the entire application range of the Lissajous scan in step S1. The main control unit 211 can store this final merged image in the storage unit 212 (and / or other storage device).

[0232] The following processing is for performing more precise motion artifact correction in the z direction. In steps S16 to S25, motion artifact correction in the z direction is performed in sub-volume units (strip units). In contrast, in steps S27 to S32 described below, motion artifact correction in the z direction is performed in cycle units. This cycle-unit correction is performed by the image data constructing unit 220 (for example, the image data correcting unit 2230).

[0233] Note that precise z-direction motion artifact correction does not need to be performed on a cycle-by-cycle basis, but may be performed on a cycle group that constitutes a part of a subvolume basis.Furthermore, precise z-direction motion artifact correction does not need to be performed for all cycles (all cycle groups), but may be performed for only some cycles (some cycle groups).

[0234] (S27: Select cycles from merged volumes) The image data corrector 2230 selects one cycle (partial data corresponding to one cycle) from the volume in which all sub-volumes are merged.

[0235] The cycle selected first may be any cycle. For example, the cycles may be selected sequentially according to the scan order (chronological order, scan number, cycle number) of the multiple cycles in the Lissajous scan in step S1. Alternatively, the cycle selection order may be set based on the order (strip number, subvolume number) assigned to multiple strips or multiple subvolumes.

[0236] (S28: Remove the cycle from the volume) Next, the image data corrector 2230 extracts the partial data corresponding to the cycle selected in step S27 from the volume.

[0237] (S29: Calculate the z-direction shift between the volume after cycle removal and the cycle) Next, the image data corrector 2230 calculates the amount of shift in the z direction between the partial data corresponding to the cycle extracted in step S28 and the volume from which the cycle was extracted.

[0238] The method for calculating the z-direction shift amount in this step may be the same as the method in step S21. For example, the image data correction unit 2230 analyzes the partial data (cross-sectional image of interest) of the cycle removed from the volume in step S28 to identify an image (first image) of a predetermined portion of the eye E, and analyzes the volume from which the cross-sectional image of interest was extracted to identify an image (second image) of the same portion. The analysis for identifying the second image does not need to be applied to the entire volume from which the cross-sectional image of interest was extracted; for example, it may be applied only to a portion adjacent to the cross-sectional image of interest (adjacent cycle). Furthermore, the image data correction unit 2230 calculates the z coordinate of the first image and the z coordinate of the second image and calculates the difference between these two z coordinates. In this example, the calculated difference is used as the z-direction shift amount between the cycle and the volume after the cycle has been removed.

[0239] (S30: Update the z-direction shift amount) Next, the main controller 211 replaces the z-direction shift amount found in step S21 with the z-direction shift amount calculated in step S29. Here, the z-direction shift amount of the subvolume including the partial data corresponding to the cycle extracted in step S28 is updated.

[0240] If a correlation coefficient is used in both the calculation of the z-direction shift amount in step S21 and the calculation of the z-direction shift amount in step S29, the information recorded in step S21 (correlation coefficient, identifier (position information), etc.) can be replaced with the information acquired in step S29 (correlation coefficient, identifier (position information), etc.), or both the information recorded in step S21 and the information acquired in step S29 can be recorded in association with each other. Here, the information recorded in step S21 and the information acquired in step S29 can be associated with each other via the identifier (position information). If a correlation coefficient is used in only one of the calculation of the z-direction shift amount in step S21 and the calculation of the z-direction shift amount in step S29, the information acquired in one of the processes can be recorded. The various processes described herein are executed by, for example, the image data constructing unit 220.

[0241] (S31: Perform registration and merging) Next, the image data corrector 2230 performs registration between the partial data corresponding to the cycle removed in step S28 and the volume after cycle removal so as to cancel the z-direction shift amount calculated in step S29. Furthermore, the image data corrector 2230 constructs a merged image of the partial data whose relative position in the z direction has been adjusted by this registration and the volume after cycle removal. This results in a volume whose relative position has been adjusted in the x and y directions and whose relative position has been precisely adjusted in the z direction.

[0242] (S32: Have all cycles been processed?) A series of processes from steps S27 to S31 are executed for all cycles in a predetermined order (S32: No). By applying this series of processes to all cycles in a sequential manner, a volume in which the relative positions in the z direction between all cycles have been adjusted is obtained (S32: Yes) (END). The main controller 211 can store this final volume in the memory unit 212 (and / or another memory device).

[0243] <Second operation example> An example of an operation combining Lissajous scanning (scanning sampling) and changing the number of samples will be described with reference to Fig. 9. The Lissajous scanning and image data construction of this example may be performed in the same manner as in the first operation example, and other matters may also be performed in the same manner as in the first operation example unless otherwise specified, but are not limited thereto.

[0244] (S41: Set the number of samples to the first number of samples) First, the number of samples for the Lissajous scan is specified by the user or the ophthalmic examination apparatus 1 (for example, the sampling control unit 2112). The sampling control unit 2112 sets the value of a scan control parameter related to the number of samples to a value corresponding to the specified number of samples. As described above, this scan control parameter may be, for example, any one of the number of cycles, the scan interval, and the size of the scan area.

[0245] In this step, at least one sample number is set. This sample number is called the first sample number. In this operation example, two (or more) Lissajous scans are applied to the subject's eye E. The first sample number is the number of samples applied to the first Lissajous scan.

[0246] In this step, two (or more) sample numbers corresponding to all or part of the two (or more) Lissajous scans executed in this operation example may be set. In this case, step S43 is executed to change the value of the sample number from the first sample number to another preset sample number.

[0247] (S42: Apply a first Lissajous scan to the subject's eye to obtain a first data set) Next, a Lissajous scan based on the first sample number set in step S41 is applied to the subject's eye E. This Lissajous scan is called the first Lissajous scan. A data set acquired from the subject's eye E by this first Lissajous scan is called the first data set.

[0248] (S43: Set the number of samples to the second number of samples) The sampling control unit 2112 changes the value of the scan control parameter related to the number of samples from the first number of samples in the first Lissajous scan in step S42 to another value (referred to as the second number of samples).

[0249] This step may include specifying a second number of samples, similar to the setting of the first number of samples in step S41, and setting the value of a scan control parameter to a value corresponding to the specified second number of samples. Alternatively, this step may include changing the value of a scan control parameter from the first number of samples specified in step S41 to the second number of samples also specified in step S41.

[0250] The first number of samples and the second number of samples are different values, but the magnitude relationship between them may be arbitrary. In some exemplary embodiments, the second number of samples is greater than the first number of samples. That is, in some exemplary embodiments, a first Lissajous scan using a relatively small number of first samples is performed, and then a second Lissajous scan using a relatively large number of second samples is performed. Various operational examples described below are performed in this manner. However, in some exemplary embodiments, a first Lissajous scan using a relatively large number of first samples may be performed, and then a second Lissajous scan using a relatively small number of second samples may be performed.

[0251] In the example shown in FIG. 9, two Lissajous scans (first Lissajous scan and second Lissajous scan) are performed, but the number of Lissajous scans performed may be three or more.

[0252] The manner of changing the number of samples performed in this step may be arbitrary, and may be, for example, switching the number of samples, changing the number of samples stepwise, or changing the number of samples continuously. The stepwise change and continuous change may be monotonic (monotonically increasing or decreasing) or non-monotonic. Parameters and conditions related to the change in the number of samples, such as the amount of change in the number of samples and the decision on whether to increase or decrease the number of samples, may be executed by, for example, the user or the ophthalmic examination apparatus 1 (e.g., the sampling control unit 2112).

[0253] (S44: Apply a second Lissajous scan to the subject's eye to obtain a second data set) Next, a Lissajous scan based on the second sample number set in step S43 is applied to the subject's eye E. This Lissajous scan is called a second Lissajous scan. A data set acquired from the subject's eye E by this second Lissajous scan is called a second data set.

[0254] (S45: Constructing first image data from the first data set) The image data constructing unit 220 constructs image data from the first data set acquired in step S42. This image data is referred to as first image data. This step may be executed in the same manner as steps S2 to S32 in the first operation example, for example.

[0255] (S46: Construct second image data from the second data set) The image data constructing unit 220 constructs image data from the second data set acquired in step S44 (end). This image data is called second image data. This step may be executed in the same manner as step S45.

[0256] According to this operation example, a plurality of image data corresponding to a plurality of different numbers of samples (in other words, a plurality of different image qualities (resolution, pixel density, etc.)) are obtained. The use of the processing according to this operation example and the use of the image data (e.g., the first image data and / or the second image data) obtained in this operation example are arbitrary. Some exemplary uses will be described in some operation examples described below.

[0257] <Third operation example> An example of an operation combining Lissajous scanning (scanning sampling) and changing the number of samples will be described with reference to Fig. 10. The Lissajous scanning and image data construction of this example may be performed in the same manner as in the first operation example, and other matters may also be performed in the same manner as in the first operation example unless otherwise specified, but are not limited thereto.

[0258] (S51: Set the number of samples to the initial number of samples) First, the user or the ophthalmic examination apparatus 1 (for example, the sampling control unit 2112) specifies the initial number of samples for the Lissajous scan. This initial number of samples is the number of samples that is initially applied in this operation example in which two or more Lissajous scans are performed. The sampling control unit 2112 sets the value of a scan control parameter related to the number of samples to a value (initial value) corresponding to the specified initial number of samples. This scan control parameter may be, for example, any one of the number of cycles, the scan interval, and the size of the scan area.

[0259] The initial sample number may be, for example, a value set by the user, a default value, a value according to the attributes of the subject, a value according to the attributes of the subject's eye, a value according to a previous examination (for example, a value recorded in the subject's electronic medical record), a value according to the examination conditions, or a value according to the examination environment. The initial sample number may be a relatively small value. For example, the initial sample number may be the minimum value within the settable range of the sample number or a value close to that minimum value.

[0260] (S52: Apply Lissajous scan to the subject's eye to obtain a data set) Next, a Lissajous scan based on the initial sample number set in step S51 is applied to the eye E to acquire a data set.

[0261] (S53: Construct image data from the dataset) The image data constructing section 220 constructs image data from the data set acquired in step S52. This step may be executed in the same manner as steps S2 to S32 in the first operation example, for example.

[0262] (S54: Evaluate the quality of the image data) The sampling control unit 2112 evaluates the quality of the image data constructed in step S53. This quality evaluation may be a process using any known image evaluation technique, for example, a process of evaluating a predetermined image quality parameter. This image quality parameter may be a quantitative or qualitative item that represents the quality of the image data.

[0263] The sampling control unit 2112 performs an evaluation of the quality of the image data constructed in step S53 with respect to one or more image quality parameters. In other words, the sampling control unit 2112 determines whether the quality of the image data constructed in step S53 is good with respect to one or more image quality parameters.

[0264] The sampling control unit 2112 may be configured to assess the quality of the image data using an evaluator trained by machine learning, which may include, for example, a convolutional neural network trained by deep learning.

[0265] The sampling control unit 2112 may be configured to evaluate the quality of the image data based on the correlation coefficients recorded in the first operation example. For example, the sampling control unit 2112 may be configured to compare the value of each correlation coefficient recorded for the image data to be evaluated with a predetermined threshold, calculate the proportion of correlation coefficients equal to or greater than the threshold among all correlation coefficients (a set of correlation coefficients), and determine the quality of the image data based on this proportion. As one example, the sampling control unit 2112 may be configured to determine that the quality of the image data is good when the proportion of correlation coefficients equal to or greater than the threshold among the entire set of correlation coefficients is 90 percent or more.

[0266] As such, the quality assessment method performed in this step may be any method that can be used to assess the quality of an image, and examples thereof include sharpness assessment (e.g., point spread function (PSF), modulation transfer function (MTF), etc.), noise assessment (e.g., root mean square (RMS) granularity, noise spectral density (NSDI, Wiener spectrum, etc.), gradation assessment (e.g., quantization bit rate, gamma characteristics, contrast, etc.), spatial characteristic assessment (e.g., brightness unevenness, distortion, etc.), assessment using machine learning, and assessment using values ​​calculated in constructing image data (e.g., correlation coefficient).

[0267] (S55: Is the image data quality good?) If the quality evaluation in step S54 determines that the quality of the image data constructed in step S53 is good (S55: Yes), the process proceeds to step S57. On the other hand, if the quality evaluation in step S54 determines that the quality of the image data constructed in step S53 is not good (S55: No), the process proceeds to step S56.

[0268] (S56: Change the number of samples) If it is determined that the quality of the image data constructed in step S53 is not good (S55: No), the sampling control unit 2112 changes the number of samples of the Lissajous scan. This change in the number of samples can also be expressed as, for example, a process of updating the number of samples, or a process of replacing the current number of samples with a new number of samples.

[0269] If the result of the first quality evaluation (S54) is "No", the sampling control unit 2112 changes the number of samples of the Lissajous scan from the initial number of samples (first set value of the number of samples) set in step S1 to a new number of samples (second set value of the number of samples). Generally, if the result of the Tth quality evaluation (S54) is "No", the sampling control unit 2112 changes the number of samples of the Lissajous scan from the Tth set value to a new T+1th set value (T is an integer greater than or equal to 1).

[0270] In some exemplary embodiments, the T+1th set value is greater than the Tth set value. In this case, if the quality of the image data is determined to be poor in the quality evaluation of step S54 (S55: No), the number of samples is increased, and a new Lissajous scan is performed with this increased number of samples (S52). The series of steps S52 to S56 is repeatedly performed until the quality evaluation of step S54 determines that the quality of the image data is good (S55: Yes). Such a series of steps S52 to S56 can be considered as a process of gradually increasing the number of samples until good-quality image data is obtained, a process of searching for the minimum number of samples (or a number of samples close to that number) that will provide good-quality image data, or a process of determining whether good-quality image data of the subject's eye E can be obtained by a Lissajous scan. Note that in some exemplary embodiments, the T+1th set value may be smaller than the Tth set value.

[0271] The amount of change in the number of samples in this step may be determined arbitrarily, and may be, for example, a value set by the user, a default value, a value according to the attributes of the subject, a value according to the attributes of the subject's eye, a value according to previous examinations, a value according to the examination conditions, a value according to the examination environment, a value according to the image data to be evaluated, or a value according to the results of the quality evaluation in step S54.

[0272] (S57: Change the number of samples to the maximum number) If it is determined that the quality of the image data constructed in step S53 is good (S55: Yes), the sampling control unit 2112 changes the number of samples of the Lissajous scan to a predetermined maximum number.

[0273] This maximum number may be determined arbitrarily, and may be, for example, the maximum value within the settable range of sample numbers or a value close to that value, a value according to the purpose of use of the image data (screening, detailed analysis of a specific disease, observation, interpretation, machine learning, etc.), a value set by the user, a value according to the attributes of the subject, a value according to the attributes of the subject's eye, a value according to past examinations, a value according to the examination conditions, a value according to the examination environment, a value according to the image data to be evaluated, or a value according to the results of the quality evaluation in step S54.

[0274] (S58: Apply Lissajous scan to the subject's eye to obtain a data set) The ophthalmic examination apparatus 1 applies Lissajous scans based on the maximum number set in step S57 to the subject's eye E to acquire a data set.

[0275] (S59: Construct image data from the dataset) The image data constructing unit 220 constructs image data from the data set acquired in step S58 (END). This step may be executed in the same manner as step S53, for example.

[0276] In addition, when the quality evaluation in step S54 determines that the quality of the image data is good (S55: Yes), if the number of samples is the maximum number mentioned above (or is greater than or equal to a predetermined allowable minimum value or satisfies predetermined conditions), steps S57 to S59 can be omitted.

[0277] According to this operation example, it is possible to automatically determine whether or not good quality image data of the subject's eye E can be acquired by Lissajous scanning.

[0278] Furthermore, by repeating the Lissajous scan while gradually increasing the number of samples from a small initial value, the time required to determine whether the Lissajous scan is successful (the time required to construct image data and the time required to evaluate the quality) also gradually increases. This has the advantage that it is possible to quickly obtain (possibly) a determination result as to whether good quality image data of the subject's eye E can be obtained by the Lissajous scan.

[0279] <Fourth operation example> An example of an operation combining Lissajous scanning (scan sampling) and changing the number of samples will be described with reference to Fig. 11. The Lissajous scanning and image data construction of this example may be performed in the same manner as in the first operation example, and other matters may also be performed in the same manner as in the first operation example unless otherwise specified, but are not limited thereto.

[0280] (S61~S63) Steps S61, S62, and S63 may be executed in the same manner as steps S51, S52, and S53 in the third operation example, respectively.

[0281] (S64: Display image) The control unit 210 (main control unit 211 as a display control unit) causes the display unit 241 to display an image based on the image data constructed in step S63. Furthermore, the main control unit 211 causes the display unit 241 to display a predetermined graphical user interface (GUI).

[0282] (S65: Is the displayed image quality good?) The user observes the image displayed in step S64 and determines whether its quality is good or not. The user inputs the result of this determination into the ophthalmic examination apparatus 1 using the operation unit 242 and the GUI.

[0283] If the input result indicates that the quality of the displayed image is good (S65: Yes), the process of this operation example ends (END). On the other hand, if the input result indicates that the quality of the displayed image is not good (S65: No), the process proceeds to step S66.

[0284] (S66: Change the number of samples) If the input result indicates that the quality of the displayed image is not good (S65: No), the sampling control unit 2112 changes the number of samples in the Lissajous scan. This change in the number of samples may be performed in the same manner as in step S56 of the third operation example.

[0285] The series of steps S62 to S66 are repeatedly executed until a determination result that the quality of the displayed image is good is input in step S65 (S65: Yes). When a determination result that the quality of the displayed image is good is input in step S65 (S65: Yes), the processing of this operation example ends (END).

[0286] In some exemplary aspects, if a determination result indicating that the quality of the displayed image is good is input in step S65 (S65: Yes), a series of processes similar to steps S57 to S59 in the third operation example may be executed.

[0287] According to this operation example, the user can determine whether or not good quality image data of the subject's eye E can be acquired by Lissajous scanning.

[0288] Furthermore, by repeating the Lissajous scan while gradually increasing the number of samples from a small initial value, the time required to determine whether the Lissajous scan is successful (the time required to construct image data and the time required to evaluate the quality) also gradually increases. This has the advantage that it is possible to quickly obtain (possibly) a determination result as to whether good quality image data of the subject's eye E can be obtained by the Lissajous scan.

[0289] <Fifth operation example> An example of an operation combining Lissajous scanning (scan sampling) and changing the number of samples will be described with reference to Fig. 12. The Lissajous scanning and image data construction of this example may be performed in the same manner as in the first operation example, and other matters may also be performed in the same manner as in the first operation example unless otherwise specified, but are not limited thereto.

[0290] As described above, the Lissajous function of the Lissajous scan of this embodiment is expressed by the following parametric equation system (x(t i ), y(t i )) is expressed as: x(t i )=A·cos(2π·(f A / n)·t i ), y(t i )=A·cos(2π·(f A (n-2) / n 2 )·t i ) The parameter n is the number of A lines (number of scan points) in each cycle in the x direction. Figure 13 shows three examples of the Lissajous function (i.e., the trajectory of the Lissajous scan) when the parameter n is changed. As is clear from these examples, the density of the Lissajous scan trajectory increases as the value of the parameter n increases, and the distribution density of the scan points also increases. In this operation example, the number of samples is changed by changing the parameter n.

[0291] (S71: Alignment) The ophthalmic examination apparatus 1 aligns the optical system with the eye E to be examined.

[0292] The alignment method may be any method, such as alignment using a front image of the subject eye E (fundus oculi Ef) (e.g., alignment using an observation image acquired by the fundus camera unit 2, alignment using an image acquired by SLO), stereo alignment, alignment using data acquired by Lissajous scanning, alignment using data acquired by other scan modes, and alignment using data acquired by other modalities, or a combination of any two or more of these methods.

[0293] In some exemplary aspects of this embodiment, the acquisition of an observation image by the fundus camera unit 2 and the Lissajous scan may be performed in parallel, and alignment may be performed by referring to this observation image, while the alignment state may be determined based on the data acquired by the Lissajous scan.

[0294] (S72:n=10) The sampling control unit 2112 sets the value of the parameter n to "10" as the initial value of the parameter n. The distribution density of the scan points corresponding to this parameter n=10 is "coarse".

[0295] 13, the initial value of the parameter n is "10," but is not limited to this. The initial value of the parameter n may be, for example, any of a value set by the user, a default value, a value according to the attributes of the subject, a value according to the attributes of the subject's eye, a value according to a previous examination, a value according to the examination conditions, a value according to the examination environment, and a value according to the image to be evaluated.

[0296] (S73: Lissajous Scan) The ophthalmic examination apparatus 1 applies a Lissajous scan based on the initial value "10" of the parameter n set in step S72 to the subject's eye E to acquire a data set.

[0297] (S74: Construction of image data) The image data constructing unit 220 constructs image data from the data set acquired in step S73. This step may be executed in the same manner as steps S2 to S32 in the first operation example, for example.

[0298] (S75: Display image) The control unit 210 (main control unit 211 as a display control unit) causes the display unit 241 to display an image based on the image data constructed in step S74. Furthermore, the main control unit 211 causes the display unit 241 to display a predetermined GUI.

[0299] (S76:Is the test complete?) The user observes the image displayed in step S75 and determines whether to end the examination of the subject's eye E (acquisition of an OCT image of the fundus oculi Ef). For example, if the user determines that the image displayed in step S75 is of sufficient quality, the user determines to end the examination of the subject's eye E. The user inputs the result of the determination as to whether to end the examination of the subject's eye E into the ophthalmic examination apparatus 1 using the operation unit 242 and the GUI.

[0300] If the user determines that the examination of the subject's eye E is to be ended (S76: Yes), the process of this operation example proceeds to step S79. On the other hand, if the user determines that the examination of the subject's eye E is not to be ended (S76: No), the process proceeds to step S77.

[0301] In some exemplary aspects, the determination in this step may be performed by the ophthalmic examination apparatus 1 (for example, the control unit 210 or the data processing unit 230). In this case, it is not necessary to display the image in step S75.

[0302] (S77:n>500?) If the user decides not to end the examination of the eye E (S76: No), the sampling control unit 2112 determines whether the current value of the parameter n exceeds a predetermined threshold value.

[0303] The threshold value of the parameter n defines the lower limit of the allowable range of the distribution density (number of samples) of scan points, and is set to "500" in the example shown in Fig. 13, but is not limited to this. This threshold value may be, for example, any of a value set by the user, a default value, a value according to the attributes of the subject, a value according to the attributes of the subject's eye, a value according to past examinations, a value according to the examination conditions, a value according to the examination environment, and a value according to the image to be evaluated.

[0304] If the current value of parameter n exceeds the threshold value (S77: Yes), the process proceeds to step S79. On the other hand, if the current value of parameter n does not exceed the threshold value (S77: No), the process proceeds to step S78.

[0305] (S78:n=n+10) If the current value of the parameter n does not exceed the threshold value (S77: No), the sampling control unit 2112 changes the value of the parameter n. In this example, the change in the value of the parameter n increases the distribution density of the scan points (the number of samples).

[0306] The amount of change in the value of parameter n specifies the amount of increase in the distribution density (number of samples) of scan points, and is set to "10" in the example shown in Fig. 13, but is not limited to this. The amount of change in parameter n may be, for example, any of a value set by the user, a default value, a value according to the attributes of the subject, a value according to the attributes of the subject's eye, a value according to past examinations, a value according to the examination conditions, a value according to the examination environment, and a value according to the image to be evaluated.

[0307] The series of steps S73 to S78 are repeatedly executed until it is determined in step S76 that the test has ended (S76: Yes) or until it is determined in step S77 that the current value of parameter n exceeds the threshold value (S77: Yes). If it is determined in step S76 that the test has ended (S76: Yes), the process proceeds to step S79. Similarly, if it is determined in step S77 that the current value of parameter n exceeds the threshold value (S77: Yes), the process proceeds to step S79.

[0308] (S79: Save image) If it is determined in step S76 that the examination has ended (S76: Yes), or if it is determined in step S77 that the current value of parameter n exceeds the threshold value (S77: Yes), the ophthalmic examination apparatus 1 saves image data of the image displayed in the last executed step S75. For example, the control unit 210 stores this image data in the memory unit 212 or another storage device. This completes the processing of this operation example (END).

[0309] According to this operation example, the user can determine whether or not good quality image data of the subject's eye E can be acquired while gradually increasing the number of samples of the Lissajous scan. Furthermore, the user can finish the examination of the subject's eye E at a desired timing.

[0310] <Sixth operation example> An example of an operation combining Lissajous scanning (scanning sampling) and changing the number of samples will be described with reference to Fig. 14. The Lissajous scanning and image data construction of this example may be performed in the same manner as in the first operation example, and other matters may also be performed in the same manner as in the first operation example unless otherwise specified, but are not limited thereto.

[0311] (S81~S85) Steps S81 to S85 may be executed in the same manner as steps S71 to S75 in the fifth operation example. In this operation example, alignment starts in step S81 and ends when the answer is "Yes" in step S86.

[0312] (S86: Is the alignment OK?) The user observes the image displayed in step S85 and determines the alignment state. The user inputs the result of the determination as to whether the alignment state is good or not into the ophthalmic examination apparatus 1 using the operation unit 242 and the GUI.

[0313] If the user determines that the alignment state is good (S86: Yes), the process in this operation example proceeds to step S88. On the other hand, if the user determines that the alignment state is not good (S86: No), the process proceeds to step S87.

[0314] In some exemplary aspects, the determination in this step may be performed by the ophthalmic examination apparatus 1 (for example, the control unit 210 or the data processing unit 230). In this case, it is not necessary to display the image in step S85.

[0315] (S87: Alignment correction) If the user determines that the alignment state is not good (S86: No), the ophthalmic examination apparatus 1 corrects the alignment state by, for example, performing the auto-alignment described above.

[0316] The series of steps S83 to S87 are repeatedly executed until it is determined in step S86 that the alignment state is good (S86: Yes). If it is determined in step S86 that the alignment state is good (S86: Yes), the process proceeds to step S88.

[0317] (S88:n=200) If it is determined in step S86 that the alignment state is good (S86: Yes), the sampling control unit 2112 changes the value of the parameter n to a predetermined value.

[0318] This predetermined value is a value set as the value of the parameter n for the image data to be saved (for diagnosis). This predetermined value is "200" in the example shown in Fig. 14, but is not limited to this. This predetermined value may be, for example, any of a value set by the user, a default value, a value according to the attributes of the subject, a value according to the attributes of the subject's eye, a value according to a previous examination, a value according to the examination conditions, a value according to the examination environment, and a value according to the image to be evaluated.

[0319] (S89: Lissajous Scan) The ophthalmic examination apparatus 1 applies a Lissajous scan based on the value "200" of the parameter n set in step S88 to the subject's eye E to acquire a data set.

[0320] (S90: Construction of image data) The image data constructing unit 220 constructs image data from the data set acquired in step S89. This step may be executed in the same manner as steps S2 to S32 in the first operation example, for example.

[0321] (S91: Display image) The control unit 210 (main control unit 211 as a display control unit) causes the display unit 241 to display an image based on the image data constructed in step S90.

[0322] (S92: Save image) The ophthalmic examination apparatus 1 saves the image data constructed in step S90. For example, the control unit 210 stores this image data in the storage unit 212 or another storage device. This completes the processing of this operation example (END).

[0323] According to this operation example, the alignment state can be confirmed using a Lissajous scan with a small number of samples (short scan time and processing time), and once the alignment state has been determined to be good, a Lissajous scan with a sufficient number of samples can be performed to obtain high-resolution image data.

[0324] <Seventh operation example> An example of an operation combining Lissajous scanning (scanning sampling) and changing the number of samples will be described with reference to Fig. 15. The Lissajous scanning and image data construction of this example may be performed in the same manner as in the first operation example, and other matters may also be performed in the same manner as in the first operation example unless otherwise specified, but are not limited thereto.

[0325] (S101~S106) Steps S101 to S106 may be executed in the same manner as steps S71 to S76 in the fifth operation example, respectively.

[0326] If the user determines that the examination of the subject's eye E is to be ended (S106: Yes), the process of this operation example proceeds to step S110. On the other hand, if the user determines that the examination of the subject's eye E is not to be ended (S106: No), the process proceeds to step S107.

[0327] In some exemplary aspects, the determination in this step may be performed by the ophthalmic examination apparatus 1 (for example, the control unit 210 or the data processing unit 230). In this case, it is not necessary to display the image in step S105.

[0328] (S107: Is the quality OK?) If the user decides not to end the examination of the subject's eye E (S106: No), the sampling control unit 2112 evaluates the quality of the image data constructed in step S104. This quality evaluation may be performed, for example, in the same manner as step S54 in the third operation example. In this manner, in this operation example, automatic determination (S107) is also performed in addition to the user's determination (S106).

[0329] If it is determined that the quality of the image data is good (S107: Yes), the process of this operation example proceeds to step S110. On the other hand, if it is determined that the quality of the image data is not good (S107: No), the process proceeds to step S108.

[0330] (S108~S109) Steps S108 and S109 may be executed in the same manner as steps S77 and S78 in the fifth operation example, respectively.

[0331] The series of steps S103 to S109 are repeatedly executed until it is determined in step S106 that the inspection has ended (S106: Yes), until it is determined in step S107 that the quality is OK (S107: Yes), or until it is determined in step S108 that the current value of parameter n exceeds the threshold (S108: Yes). If it is determined in step S106 that the inspection has ended (S106: Yes), the process proceeds to step S110. Similarly, if it is determined in step S107 that the quality is OK (S107: Yes), the process proceeds to step S110. Similarly, if it is determined in step S108 that the current value of parameter n exceeds the threshold (S108: Yes), the process proceeds to step S110.

[0332] (S110: Display and save images) If it is determined in step S106 that the examination has ended (S106: Yes), if the quality is determined to be OK in step S107 (S107: Yes), or if it is determined in step S108 that the current value of parameter n exceeds the threshold value (S108: Yes), the ophthalmic examination apparatus 1 saves image data of the image displayed in the last executed step S105. For example, the control unit 210 stores this image data in the memory unit 212 or another storage device. Furthermore, as necessary, the main control unit 211 can cause the display unit 241 to display an image based on this image data. This concludes the processing of this operational example (END).

[0333] According to this operation example, the user and the ophthalmic examination apparatus 1 can determine whether good quality image data of the subject's eye E can be acquired while gradually increasing the number of samples in the Lissajous scan. Furthermore, the user can finish the examination of the subject's eye E at a desired timing. Note that, in some exemplary embodiments, only one of the user and the ophthalmic examination apparatus may make this determination.

[0334] <8th operation example> An example of an operation combining Lissajous scanning (scan sampling) and changing the number of samples will be described with reference to Fig. 16. The Lissajous scanning and image data construction of this example may be performed in the same manner as in the first operation example, and other matters may also be performed in the same manner as in the first operation example unless otherwise specified, but are not limited thereto.

[0335] (S121~S123) Steps S121 to S123 may be executed in the same manner as steps S71 to S73 in the fifth operation example, respectively.

[0336] (S124: Strip Construction) The image data constructing unit 220 constructs image data from the data sets acquired in the Lissajous scan in step S103. In this step, the image data constructing unit 220 sequentially constructs strips corresponding to each cycle from a plurality of data sets acquired sequentially for a plurality of cycles in the Lissajous scan in step S103. This step may be executed in the same manner as at least step S2 in the first operation example, and may further include the same processing as steps S3 to S32.

[0337] (S125:Strip display) The control unit 210 (main control unit 211 as a display control unit) causes the display unit 241 to display an image based on the image data (strips) constructed in step S124. The image displayed in this step may be, for example, an image of one strip, or an image of a merged strip based on two or more strips. Furthermore, the main control unit 211 causes the display unit 241 to display a predetermined GUI.

[0338] (S126: Is refinement necessary?) The user observes the image displayed in step S125 and determines whether image refinement (refining the scan, increasing the distribution density of scan points, or increasing the number of samples) is necessary. In other words, the user determines whether a higher quality image is necessary. The user inputs the result of this determination into the ophthalmic examination apparatus 1 using the operation unit 242 and the GUI.

[0339] If the user determines that refinement is necessary (S126: Yes), the process of this operation example proceeds to step S127. On the other hand, if the user determines that refinement is not necessary (S126: No), the process proceeds to step S128.

[0340] In some exemplary aspects, the determination in this step may be performed by the ophthalmic examination apparatus 1 (for example, the control unit 210 or the data processing unit 230). In this case, it is not necessary to perform the strip display in step S125.

[0341] (S127:n=n+10) If the user determines that refinement is necessary (S126: Yes), the sampling control unit 2112 changes the value of the parameter n. This step may be executed in the same manner as step S78 in the fifth operation example. After the value of the parameter n is changed, steps S123 to S126 are executed again.

[0342] (S128: Processing complete?) Steps S123 to S128 are repeatedly executed until the processing for all cycles of the Lissajous scan (for example, steps S2 to S32 in the first operation example) is completed (S128: No). When the processing for all cycles of the Lissajous scan is completed (S128: Yes), the processing proceeds to step S129.

[0343] In this operation example, the ophthalmic examination apparatus 1 may be configured to execute processing (S124 to S128) of the data set acquired by the Lissajous scan while executing the Lissajous scan (S123).

[0344] For example, the ophthalmic examination apparatus 1 may be configured to execute the following series of processes: in response to the transition from step S122 to step S123, a Lissajous scan (which may be either one Lissajous scan or two or more Lissajous scans) is started (S123); strips for each cycle are constructed sequentially and in real time from multiple data sets acquired sequentially for multiple cycles in this Lissajous scan (S124); the sequentially constructed strips are displayed sequentially and in real time (S125); input of the user's judgment results for the sequentially displayed strips is accepted (S126); processing is performed in real time according to the input judgment results (S127, S128); and repeated processing (S123 to S128) is performed as necessary according to this judgment result.

[0345] (S129: Display image) The control unit 210 (main control unit 211 as a display control unit) causes the display unit 241 to display an image based on the image data constructed by the processing determined to be completed in step S128.

[0346] (S130: Save image) The control unit 210 stores the image data constructed by the process determined to be completed in step S128 in the storage unit 212 or another storage device. This completes the process of this operational example (END).

[0347] According to this operation example, the quality of the image can be determined based on the strips acquired sequentially while the Lissajous scan is being performed. This allows for quicker determination of the success or failure of the Lissajous scan. Furthermore, if a higher resolution image is desired, the number of Lissajous scan samples can be increased. Furthermore, the user can finish the examination of the subject's eye E at the desired timing.

[0348] <9th operation example> An example of an operation combining Lissajous scanning (scan sampling) and changing the number of samples will be described with reference to Fig. 17. The Lissajous scanning and image data construction of this example may be performed in the same manner as in the first operation example, and other matters may also be performed in the same manner as in the first operation example unless otherwise specified, but are not limited thereto.

[0349] (S141~S142) Steps S141 and S142 may be executed in the same manner as steps S71 and S72 in the fifth operation example, respectively.

[0350] (S143: Setting the scan center and interval) The user or the ophthalmic examination apparatus 1 sets the scan center and scan interval to be applied to the Lissajous scan. The scan center is set, for example, by referring to the observation image acquired by the fundus camera unit 2 and / or the OCT image acquired by the preliminary OCT scan. A non-limiting example of the processing performed in this step will be described below.

[0351] In some exemplary embodiments, the ophthalmic examination apparatus 1 may be configured so that the user can set a desired scan center position for the observation image and / or OCT image displayed on the display unit 241. Furthermore, the user may be able to set a desired scan range for the observation image and / or OCT image. Note that a wide scan range is set at this stage (wide-angle OCT scan). The user can also set the scan interval (the distance between adjacent scan points). At this time, the user may refer to the value of the parameter n (n=10 in this example) set in step S142.

[0352] In some exemplary aspects, the ophthalmic examination apparatus 1 (e.g., the sampling control unit 2112 and / or the data processing unit 230) may be configured to analyze the observation image and / or the OCT image to detect an image of a predetermined portion of the fundus oculi Ef, and to set the scan center position (and scan range) based on the position of this image. For example, the ophthalmic examination apparatus 1 may analyze the observation image and / or the OCT image to detect an image of the macula (or the optic disc, the center of the fundus, a lesion, a characteristic portion of blood vessels, etc.), detect the outer edge of this macular image, obtain an approximate circle or ellipse of this outer edge, identify the center of this approximate circle or ellipse, and set the position of this center as the scan center. Furthermore, the ophthalmic examination apparatus 1 may set the scan range to include this macular image. Note that at this stage, a wide scan range is set (wide-angle OCT scan). The ophthalmic examination apparatus 1 may also be configured to set a scan interval. In this process, the ophthalmic examination apparatus 1 may refer to the value of the parameter n (n=10 in this example) set in step S142.

[0353] (S144: Lissajous Scan (wide angle, low resolution)) The ophthalmic examination apparatus 1 acquires a data set by applying a Lissajous scan using the conditions (parameter n, scan center, scan interval, scan range, etc.) set in steps S142 and S143 to the subject's eye E. The Lissajous scan in this step is wider-angle and lower-resolution than the Lissajous scan in the subsequent stage (step S150).

[0354] (S145: Construction of image data) The image data constructing unit 220 constructs image data from the data set acquired in step S 144. This step may be executed in the same manner as steps S2 to S32 in the first operation example, for example.

[0355] (S146: Wide-angle image display) The control unit 210 (main control unit 211 as a display control unit) causes an image based on the image data constructed in step S145 to be displayed on the display unit 241. The image displayed in this step is a low-resolution wide-angle image (wide-area image).

[0356] (S147: Specify scan range) The user refers to the wide-angle image displayed in step S146 and specifies the range to which high-definition Lissajous scanning is to be applied.

[0357] In some exemplary aspects, the processing of this step may be executed by the ophthalmic examination apparatus 1 (for example, the control unit 210 or the data processing unit 230). In this case, it is not necessary to display a wide-angle image in step S145.

[0358] (S148: Scan center and interval settings) The user or the ophthalmic examination apparatus 1 sets the scan center and scan interval to be applied to the high-resolution Lissajous scan.

[0359] (S149:n=100) The sampling control unit 2112 changes the value of the parameter n to a predetermined value. This predetermined value is a value set as the value of the parameter n for image data to be saved (for diagnosis). This predetermined value is "100" in the example shown in FIG. 17, but is not limited to this. This predetermined value may be, for example, any of a value set by the user, a default value, a value according to the attributes of the subject, a value according to the attributes of the subject's eye, a value according to a previous examination, a value according to the examination conditions, a value according to the examination environment, and a value according to the image to be evaluated.

[0360] (S150: Lissajous Scan (High Definition)) The ophthalmic examination apparatus 1 acquires a data set by applying a Lissajous scan using the conditions set in steps S147 to S149 (scan range, scan center, scan interval, parameter n, etc.) to the subject's eye E. The Lissajous scan in this step is higher in resolution than the Lissajous scan in step S144.

[0361] (S151: Construction of image data) The image data constructing section 220 constructs image data from the data set acquired in step S 150. This step may be executed in the same manner as steps S2 to S32 in the first operation example, for example.

[0362] (S152: High-definition image display) The control unit 210 (main control unit 211 as a display control unit) causes the display unit 241 to display an image based on the image data constructed in step S151 (a high-definition image of the range designated in step S147).

[0363] (S153: High-definition image overlaid on wide-angle image) For example, in response to a user instruction, the control unit 210 (main control unit 211 as a display control unit) can display a high-definition image based on the image data constructed in step S151 overlapping with a wide-angle image based on the image data constructed in step S145.

[0364] The registration between the high-definition image and the wide-angle image may be performed based on the result of the scan range designation performed in step S147, for example, or may be performed by referring to feature points in the high-definition image and feature points in the wide-angle image.

[0365] (S154: Save image) The ophthalmic examination apparatus 1 saves the image data acquired in this operation example. For example, the control unit 210 stores the image data constructed in step S151 (and the image data constructed in step S145) in the storage unit 212 or another storage device. This completes the processing of this operation example (END).

[0366] According to this operation example, it is possible to set a range in which a sufficient number of samples of Lissajous scans are applied, using an image acquired with a small number of samples of Lissajous scans (shorter scan time and processing time).

[0367] <Effects> Some effects of the ophthalmic examination apparatus 1 according to the first embodiment will be described.

[0368] The ophthalmic examination apparatus 1 is a scanning imaging apparatus that constructs image data using optical scanning, and includes a data set collection unit, an image data construction unit, and a sampling control unit.

[0369] The data set collection unit is configured to collect a data set by applying an optical scan to the object according to a two-dimensional pattern including a series of intersecting cycles. In this embodiment, a group of elements for collecting OCT data corresponds to the data set collection unit, and for example, the fundus camera unit 2, the OCT unit 100, etc. correspond to the data set collection unit.

[0370] The image data constructing unit is configured to construct image data based on the data set collected by the data set collecting unit. In this embodiment, the image data constructing unit 220 corresponds to the image data constructing unit.

[0371] The sampling control unit is configured to change the number of samples in sampling for constructing image data. In this embodiment, the sampling control unit 2112 corresponds to the sampling control unit.

[0372] With conventional Lissajous scanning technology, data processing to create image data requires a significant amount of time and resources, and it is not possible to determine whether the scan was successful until this data processing is complete.

[0373] In contrast, according to the ophthalmic examination apparatus 1 of this embodiment, the number of samples in scan sampling can be changed, and therefore the time required for data processing (and further, the time required for Lissajous scanning) can be changed. In particular, it is possible to shorten the time required for data processing (and further, the time required for Lissajous scanning) and reduce resources. Therefore, it is possible to speed up the determination of the success or failure of the scan.

[0374] The effect of speeding up the determination of the success or failure of a scan is just one of the effects of this embodiment. This embodiment achieves the various effects described above depending on its aspect, and also achieves effects depending on its configuration and operation.

[0375] As described above, sampling for constructing image data in scanning imaging includes sampling in optical scanning (scanning sampling) and sampling in processing data collected by optical scanning (data sampling). This embodiment deals with several exemplary aspects of sampling control when scanning sampling is applied. Note that several exemplary aspects of sampling control when data sampling is applied will be described in the second embodiment.

[0376] The sampling control unit (2112) of this embodiment is configured to control the data set collection unit to change the number of scan points in optical scanning in order to change the number of samples in scanning sampling (the number of samples obtained from the test object by optical scanning) (first sampling control unit).

[0377] A first exemplary aspect of the sampling control unit (2112) of this embodiment, which functions as a first sampling control unit, is configured to change the number of samples in the scan sampling by controlling the dataset collection unit to change the spacing of the scan points (density of the scan points) in the optical scan.

[0378] A second exemplary aspect of the sampling control unit (2112) of this embodiment, functioning as the first sampling control unit, is configured to change the number of samples in the scan sampling by controlling the dataset collection unit to change the number of cycles included in the series of cycles in the optical scan.

[0379] A third exemplary aspect of the sampling control unit (2112) of this embodiment, which functions as the first sampling control unit, is configured to change the number of samples in the scan sampling by controlling the data set collection unit to change the dimensions of the application area of ​​the optical scan.

[0380] The sampling control unit (2112) of this embodiment, which functions as the first sampling control unit, is not limited to the first to third exemplary aspects, and may have any configuration that can directly or indirectly change the number of scan points in optical scanning.

[0381] In this embodiment, the sampling control unit 2112 may be configured to change the number of samples in the scan sampling between a first number of samples and a second number of samples greater than the first number of samples. In this case, the image data constructing unit 220 may construct first image data based on a first data set obtained by the first sampling using the (relatively small) first number of samples, and may construct second image data based on a second data set obtained by the second sampling using the (relatively large) second number of samples.

[0382] The number of samples in the scan sampling is not limited to two, and may be three or more. The first number of samples and the second number of samples may represent two of the three or more sample numbers.

[0383] The order of applying the first number of samples and the second number of samples may be arbitrary. That is, either the first sampling or the second sampling may be performed first. For example, as described in some operation examples of this embodiment, the sampling control unit (2112) may apply a relatively small number of first samples and then a relatively large number of second samples. Conversely, the sampling control unit (2112) may apply a relatively large number of second samples and then a relatively small number of first samples.

[0384] Such an ophthalmic examination device 1 can acquire two or more image data corresponding to two or more sample numbers, and therefore allows for applications such as the following: using image data corresponding to a certain number of samples to perform optical scanning corresponding to another number of samples; using image data corresponding to a certain number of samples to process image data corresponding to another number of samples; providing a user with two or more image data corresponding to two or more different numbers of samples; processing (analysis, synthesis, comparison, etc.) two or more image data corresponding to two or more different numbers of samples; and performing machine learning using two or more image data corresponding to two or more different numbers of samples.

[0385] As explained in some operation examples of this embodiment, the sampling control unit (2112) may be configured to increase the number of samples in the scanning sampling stepwise.

[0386] This configuration makes it possible to perform various processes while gradually increasing the number of samples. For example, when the number of samples is small, it is possible to take advantage of the short data processing time to determine the success or failure of the scan and to perform alignment, and when a sufficient number of samples is reached, it is possible to acquire image data of sufficient quality (resolution, definition).

[0387] In this embodiment, the sampling control unit 2112 may be configured to determine whether the quality of the image data constructed by the image data construction unit 220 is good. Furthermore, the sampling control unit 2112 may be configured to change the number of samples when it is determined that the quality of the image data is not good.

[0388] This configuration allows the quality of image data acquired using optical scanning to be automatically evaluated, enabling rapid and automatic determination of the success or failure of the scan. Furthermore, if the image data quality is not satisfactory, changing the number of samples allows further optical scanning to be performed under different conditions. For example, if the image data quality is not satisfactory, increasing the number of samples and performing further optical scanning can be used to attempt to acquire image data of higher quality.

[0389] The sampling control unit (2112) may be configured to change the number of samples to a predetermined maximum number when it is determined that the quality of the image data constructed by the image data construction unit (220) is good.

[0390] With this configuration, if the quality of the image data is good, further optical scanning can be performed with the maximum number of samples, making it possible to automatically transition to obtaining high-quality image data (maximum resolution, maximum definition).

[0391] The ophthalmic examination apparatus 1 of this embodiment includes a display control unit (control unit 210, main control unit 211) that displays an image on a display device (display unit 241) based on image data constructed by an image data construction unit (220), and also includes an operation unit (242) that allows a user to input instructions based on the image displayed on the display device. Furthermore, the sampling control unit (2112) may be configured to change the number of samples based on instructions input to the operation unit.

[0392] With this configuration, the user can set the desired number of samples by observing the displayed image.

[0393] <Second embodiment> A second embodiment will be described. In the first embodiment, several exemplary aspects relating to the control of sampling (scanning sampling) performed as optical scanning are described, but in this embodiment, several exemplary aspects relating to the control of sampling (data sampling) in processing data collected by optical scanning are described.

[0394] As described above, data sampling is, for example, an operation of extracting multiple partial data sets from data collected by optical scanning or data generated based on the collected data. Data sampling in this embodiment may be, for example, a process of extracting discrete data sets from continuous data (converting a continuous signal into a discrete signal, converting an analog signal into a digital signal, or A / D conversion), a process of extracting multiple continuous partial data sets from continuous data, a process of extracting one or more continuous partial data sets and one or more discrete partial data sets from continuous data, a process of extracting multiple discrete partial data sets from discrete data, or a combination of any of these processes. Furthermore, data sampling in this embodiment may be, for example, a process of extracting multiple partial image data sets from image data, a process of extracting multiple partial data sets from data generated based on image data, a process of extracting multiple partial data sets (subsets of a set consisting of multiple image data sets) from an image data set (a set consisting of multiple image data sets), or a combination of any of these processes.

[0395] In this embodiment, unless otherwise specified, the same matters as in the first embodiment (similar configurations, similar elements, similar functions, similar actions, similar effects, etc.) are applied, but the present embodiment is not limited to these.

[0396] The ophthalmic examination apparatus of this embodiment has the configuration shown in FIG. 18 in addition to the configuration of the first embodiment shown in FIGS. 1 to 4B.

[0397] Note that in some exemplary aspects, in addition to the configurations shown in Figures 1 to 4B of the first embodiment, both the configuration shown in Figure 4C and the configuration shown in Figure 18 may be provided. In such aspects, it is possible to execute both scan sampling control and data sampling control, and for example, it is possible to execute these controls in combination and / or to execute these controls selectively.

[0398] 18 is an example of the main control unit 211 in Fig. 3, and includes a sampling control unit 2113 in addition to the scanning control unit 2111 in Fig. 4A. The sampling control unit 2113 executes control related to data sampling, and is configured to control the data collection system 2200 of the image data creation unit 220.

[0399] For example, the sampling control unit 2113 is configured to control sampling in the digitization process executed by the data collection system 2200. More specifically, the sampling control unit 2113 is configured to control changing the number of samples extracted by sampling in the digitization process executed as data sampling.

[0400] In some exemplary embodiments, the sampling control unit 2113 may be configured to modulate the clock KC provided from the light source unit 101 to the data collection system 2200. This signal modulation may be, for example, frequency modulation, which allows the frequency of data sampling performed by the data collection system 2200 to be changed.

[0401] Furthermore, in some exemplary aspects, the sampling control unit 2113 may be configured to control the light source unit 101 that generates the clock KC. That is, the sampling control unit 2113 may be configured to execute control to change the frequency of the clock KC generated by the light source unit 101. This also makes it possible to change the frequency of data sampling performed by the data collection system 2200.

[0402] The control executed to change the number of samples in the data sampling executed by the data collection system 2200 (i.e., the configuration, function, and operation of the sampling control unit 2113) is not limited to the above example. For example, in some exemplary aspects, the image data constructor 220 may include a functional element (processor) configured to execute data thinning processing (data extraction processing) in the data collection system 2200 (or between the data collection system 2200 and the strip constructor 2210, or any other location), and the sampling control unit 2113 may be configured to change the number of data (number of samples) extracted by the data thinning processing by controlling this processor.

[0403] As described above, the image data constructing unit 220 of this embodiment is configured to perform data sampling, which extracts sub-data sets (plurality of samples) from a data set collected by a Lissajous scan applied to the subject's eye E, using the data collection system 2200. Furthermore, the image data constructing unit 220 of this embodiment is configured to perform image data construction based on the sub-data sets extracted from the data set by this data sampling, using the mask image generating unit 2211 to the image data correcting unit 2230. In addition, the sampling control unit 2113 of this embodiment is configured to change the number of data (samples) included in the sub-data sets extracted from the data set in this data sampling by controlling the image data constructing unit 220 to change the number of samples in the data sampling performed by the image data constructing unit 220. The sampling control unit 2113 provides an exemplary aspect of a second sampling control unit.

[0404] In some exemplary embodiments, the sampling control unit 2113 may be configured to control the image data construction unit 220 (data acquisition system 2200) to change the data extraction interval in data sampling. Also, in some exemplary embodiments, the sampling control unit 2113 may be configured to control the image data construction unit 220 (data acquisition system 2200) to change the number of cycles that are the subject of data extraction in data sampling among a series of cycles in optical scanning. Also, in some exemplary embodiments, the sampling control unit 2113 may be configured to control the image data construction unit 220 (data acquisition system 2200) to change the size of the area that is the subject of data extraction in data sampling among the application area of ​​optical scanning.

[0405] The data sampling that is the subject of control performed by the sampling control unit 2113 in this example (i.e., the data sampling that is performed by the data collection system 2200) corresponds to the "process of extracting discrete data from continuous data" among the various types of data sampling described above, but the data sampling that is the subject of control performed by the sampling control unit in this embodiment is not limited to this.

[0406] For example, the data sampling controlled by the sampling control unit of this embodiment may include, as non-limiting examples, any one of the processes shown below, or may include at least a partial combination of any two or more of them: a process for extracting multiple continuous partial data from continuous data; a process for extracting one or more continuous partial data and one or more discrete partial data from continuous data; a process for extracting multiple discrete partial data from discrete data; a process for extracting multiple partial image data from image data; a process for extracting multiple partial data from data generated based on image data; and a process for extracting multiple partial data sets from an image data set.

[0407] In some exemplary aspects, data sampling may be performed as a process of extracting image data groups from a plurality of image data (e.g., a plurality of strips, a plurality of sub-volumes, etc.) constructed by the image data construction unit 220, and the sampling control unit 2113 may be configured to control this data sampling. For example, the sampling control unit 2113 may be configured to be able to perform any of control for changing the image data extraction interval in this data sampling, control for changing the number of cycles from which image data is extracted in this data sampling, and control for changing the dimensions of the area from which image data is extracted in this data sampling, among the application areas of the optical scan.

[0408] The manner of control performed by the sampling control unit 2113 is not limited to the exemplary control described above, and may include any control for changing the number of data extracted by data sampling (and therefore for changing the number of samples in sampling to construct image data).

[0409] Furthermore, the sampling control unit 2113 may be configured to be able to execute any of the various processes that can be executed by the sampling control unit 2112 (or other functional elements) of the first embodiment.

[0410] With the ophthalmic examination apparatus of this embodiment configured as described above, the number of samples in data sampling can be changed, which allows the time required for data processing to be changed. In particular, it is possible to shorten the time and reduce the resources required for data processing. Therefore, it is possible to speed up the determination of the success or failure of a scan.

[0411] The effect of speeding up the determination of the success or failure of a scan is just one of the effects of this embodiment. This embodiment achieves the various effects described above depending on its aspect, and also achieves effects depending on its configuration and operation.

[0412] Furthermore, it will be understood by those skilled in the art that some of the various effects achieved by the first embodiment can be achieved by the ophthalmic examination apparatus of this embodiment.

[0413] <Other embodiments> The embodiments of the present disclosure are not limited to the first and second embodiments and their modified examples. For example, the first and second embodiments provide embodiments relating to various methods, embodiments relating to various programs, embodiments relating to various recording media, and the like.

[0414] The first or second embodiment provides an embodiment of a method for controlling a scanning imaging apparatus. The method according to this embodiment is a method for controlling a scanning imaging apparatus including a scanner that performs optical scanning and a processor that constructs image data from a data set collected by the optical scanning. The scanner may be the data set collection unit of the first embodiment, and the processor may be the image data construction unit 220 (and data processing unit 230) of the first embodiment.

[0415] The method according to this embodiment includes a step of changing the number of samples in the sampling for constructing the image data by controlling at least one of the scanner and the processor, i.e., the method according to this embodiment includes any of a step of controlling the scanner to change the number of samples in the sampling for constructing the image data, a step of controlling the processor to change the number of samples in the sampling for constructing the image data, and a step of controlling both the scanner and the processor to change the number of samples in the sampling for constructing the image data.

[0416] In some exemplary embodiments, controlling the scanner may include controlling the number of scan points in the optical scan, and in some exemplary embodiments, controlling the processor may include controlling the number of data points extracted from the data set by data sampling.

[0417] Any of the features described in the first or second embodiment can be combined with the method according to this embodiment, and the control method for a scanning imaging device will have functions and effects according to the combined features.

[0418] According to this method for controlling a scanning imaging device, it is possible to speed up the determination of whether a scan has been successful.

[0419] The first or second embodiment provides an embodiment of an imaging method using a scanning imaging apparatus. The method according to this embodiment is an imaging method using a scanning imaging apparatus including a scanner that performs optical scanning and a processor that constructs image data from a data set collected by the optical scanning. The scanner may be the data set collection unit of the first embodiment, and the processor may be the image data construction unit 220 (and the data processing unit 230) of the first embodiment.

[0420] The method according to this embodiment may include the following three steps: a first step is to collect a data set by applying an optical scan to a test object according to a two-dimensional pattern including a series of cycles that intersect with each other using a scanner; a second step is to construct image data based on the data set collected in the first step using a processor; and a third step is to change the number of samples in sampling for constructing the image data using the processor.

[0421] According to this imaging method, it is possible to speed up the determination of the success or failure of the scan.

[0422] The present disclosure provides a program that causes a computer to execute a method according to an embodiment. Some exemplary embodiments provide a program that causes a computer to execute a control method for a scanning imaging device. Some exemplary embodiments provide a program that causes a computer to execute an imaging method. Some exemplary embodiments provide a program that causes a computer to execute any method that can be realized by the technology according to the present disclosure.

[0423] The present disclosure provides a computer-readable non-transitory recording medium having a program recorded thereon according to an embodiment. Some exemplary embodiments provide a computer-readable non-transitory recording medium having a program recorded thereon that causes a computer to execute a control method for a scanning imaging device. Some exemplary embodiments provide a computer-readable non-transitory recording medium having a program recorded thereon that causes a computer to execute an imaging method. Some exemplary embodiments provide a computer-readable non-transitory recording medium having a program recorded thereon that causes a computer to execute any method that can be realized by the technology of the present disclosure. The non-transitory recording medium of the embodiments may be in any form, and examples thereof include a magnetic disk, an optical disk, a magneto-optical disk, and a semiconductor memory.

[0424] The present disclosure merely illustrates some exemplary embodiments and is not intended to limit the invention. 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. [Explanation of symbols]

[0425] 1. Ophthalmic examination equipment 211 Main control unit 2112, 2113 Sampling control section 220 Image Data Construction Department 2200 Data Acquisition System

Claims

1. a data set collection unit that collects a data set by applying an optical scan to the test object according to a two-dimensional pattern including a series of intersecting cycles; an image data constructing unit that constructs image data based on the data set; a sampling control unit that changes the number of samples in sampling for constructing the image data; Including, The sampling control unit controlling the data set collection unit to change the number of scan points in the optical scan to change the number of samples; and determining whether the quality of the image data constructed by the image data construction unit is good; If it is determined that the quality of the image data is not good, the sampling control unit increases the number of samples by a predetermined change amount to set a new number of samples; the data set collection unit performs a new optical scan according to the two-dimensional pattern based on the new number of samples to collect a new data set; the image data constructing unit constructs new image data based on the new data set; If the quality of the image data is determined to be good, the sampling control unit changes the number of samples to a predetermined maximum number; the data set collection unit collects data sets by performing optical scanning according to the two-dimensional pattern based on the predetermined maximum number; the image data constructing unit constructs image data based on the data set collected by the optical scanning based on the predetermined maximum number. Scanning imaging device.

2. the sampling control unit determines whether the quality of the new image data is good, and increases the number of samples stepwise until image data of good quality is obtained.

2. The scanning imaging device of claim 1.

3. the sampling control unit determines whether the quality of the new image data is good, and searches for the minimum number of samples that will result in good quality image data; 2. The scanning imaging device of claim 1.

4. the sampling control unit determines whether good quality image data can be acquired by optical scanning according to the two-dimensional pattern; 2. The scanning imaging device of claim 1.

5. The test object is an eye of a test subject, The predetermined change amount of the number of samples is any one of a value set by a user, a default value, a value according to the attributes of the subject, a value according to the attributes of the subject's eye, a value according to a past examination of the subject's eye, a value according to the examination conditions of the subject's eye, a value according to the examination environment of the subject's eye, a value according to the image data of which quality is to be determined, and a value according to the result of the quality determination. The scanning imaging device according to any one of claims 1 to 4.

6. The test object is an eye of a test subject, The maximum number of samples is any one of a maximum value within a settable range of the number of samples, a value according to the purpose of use of the image data, a value set by a user, a value according to the attributes of the subject, a value according to the attributes of the subject's eye, a value according to a past examination of the subject's eye, a value according to the examination conditions of the subject's eye, a value according to the examination environment of the subject's eye, a value according to the image data whose quality is to be determined, and a value according to the result of the quality determination. The scanning imaging device according to any one of claims 1 to 4.

7. A method of controlling a scanning imaging device including a scanner that performs an optical scan according to a two-dimensional pattern including a series of intersecting cycles, and a processor that constructs image data from a data set collected by the optical scan, comprising: Executing control of the scanner to vary the number of samples in sampling to construct the image data; The processor: controlling the scanner to change the number of scan points in the optical scan to change the number of samples; and Determine whether the constructed image data is of good quality; If it is determined that the quality of the image data is not good, the processor increases the number of samples by a predetermined change amount to set a new number of samples; the scanner performs a new optical scan along the two-dimensional pattern based on the new number of samples to collect a new data set; the processor constructs new image data based on the new data set; If the quality of the image data is determined to be good, the processor changes the number of samples to a predetermined maximum number; the scanner performs an optical scan according to the two-dimensional pattern based on the predetermined maximum number to collect a data set; the processor constructs image data based on the data sets collected in the optical scans based on the predetermined maximum number. method.

8. A program that causes a computer to execute the method of claim 7.

9. A computer-readable non-transitory recording medium on which the program of claim 8 is recorded.

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