Ophthalmological information processing device, ophthalmological device, ophthalmological information processing method, and program

Abstract

To provide a novel technology for analyzing spectral distribution data in more detail.SOLUTION: An ophthalmologic information processing device includes a feature region specification unit and a depth information specification unit. The feature region specification unit specifies a feature region in spectral distribution data acquired by receiving return light having a predetermined wavelength range from a subject eye illuminated with illumination light. The depth information specification unit specifies depth information of the feature region on the basis of measurement data of the subject eye having resolution in a depth direction higher than the spectral distribution data.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present invention relates to an ophthalmologic information processing device, an ophthalmologic apparatus, an ophthalmologic information processing method, and a program. [Background technology]

[0002] Fundus observation, which involves observing the retina, blood vessels, optic nerve, etc. through the pupil, is useful for diagnosing ocular diseases and estimating the state of sclerosis throughout the body (particularly cerebral blood vessels). Fundus observation uses fundus images acquired by ophthalmic devices (fundus photography devices) such as fundus cameras and scanning light ophthalmoscopes (SLO).

[0003] In fundus observation, it is known that acquiring multiple spectral fundus images over a wide analysis wavelength range may enable extraction of various fundus features that are difficult to grasp from general fundus images. For example, Patent Documents 1 and 2 disclose ophthalmologic devices that acquire spectral fundus images. For example, Non-Patent Documents 1 and 2 disclose a method of applying a hyperspectral image as a spectral fundus image to the retina. For example, Patent Document 3 discloses a method of accurately identifying a region from a spectral fundus image based on its spectral characteristics. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2006-158546 [Patent Document 2] Japanese Patent Application Laid-Open No. 2010-200916 [Patent Document 3] Japanese Patent Application Laid-Open No. 2007-330558 [Non-patent literature]

[0005] [Non-Patent Document 1] Sophie Lemments, et al., “Hyperspectral Imaging and the Retina: Worth the Wave?”, translational vision science & technology, August 5, 2020, Vol. 9, No. 9, Ariticle 9 [Non-patent document 2] Edith R. Reshef, et el., “Hyperspectral Imaging of the Retina: A Review”, INTERNATIONAL OPHTHALMOLOGY CLINICS, August 21, 2020, Vol. 60, No. 1, pp.85-96 Summary of the Invention [Problem to be solved by the invention]

[0006] Spectral distribution data such as spectral images are acquired based on the reflected light of illumination light from the measurement target region. The detected reflected light includes reflected light and scattered light from various tissues in the depth direction of the measurement target region, so it is unclear which tissue in the measurement target region the reflected light comes from. If it is possible to identify which tissue in the measurement target region the reflected light comes from, it becomes possible to perform a more detailed analysis of the spectral distribution data.

[0007] The present invention has been made in view of the above circumstances, and one of its objects is to provide a new technique for analyzing spectral distribution data in more detail. [Means for solving the problem]

[0008] A first aspect of the embodiment is an ophthalmologic information processing device that includes: a characteristic region identifying unit that identifies a characteristic region in spectral distribution data acquired by receiving return light in a predetermined wavelength range from a test eye illuminated with illumination light; and a depth information identifying unit that identifies depth information of the characteristic region based on measurement data of the test eye that has a higher resolution in the depth direction than the spectral distribution data.

[0009] In a second aspect of the embodiment, in the first aspect, the characteristic region identification unit identifies the characteristic region in any of a plurality of spectral distribution data obtained by illuminating the test eye with illumination light and receiving return light from the test eye having different wavelength ranges.

[0010] In a third aspect of the embodiment, in the first or second aspect, the measurement data is OCT data obtained by performing optical coherence tomography on the subject's eye.

[0011] In a fourth aspect of the embodiment, in the third aspect, the depth information identification unit includes a search unit that searches for a front image that has the highest correlation with the spectral distribution data from among a plurality of front images that are formed based on the OCT data and have different depth positions, and identifies the depth information based on the front image searched for by the search unit.

[0012] In a fifth aspect of the embodiment, in the third aspect, the depth information identification unit includes a search unit that searches for a front image including an image area that has the highest correlation with an image including the characteristic area from among a plurality of front images formed based on the OCT data and having different depth positions, and identifies the depth information based on the front image searched by the search unit.

[0013] A sixth aspect of the present invention is the fourth or fifth aspect, further comprising an estimation unit that estimates the presence or absence of a disease, the probability of a disease, or the type of disease based on the front image searched for by the search unit.

[0014] A seventh aspect of the embodiment is the sixth aspect, which includes a display control unit that causes a display means to display disease information including the presence or absence of the disease, the probability of the disease, or the type of disease estimated by the estimation unit.

[0015] An eighth aspect according to the present invention is the fourth or fifth aspect, further including a display control unit that causes a display unit to display the front image searched for by the search unit and the depth information.

[0016] A ninth aspect according to the present invention is the fourth or fifth aspect, further including a display control unit that causes a display unit to display the spectral distribution data superimposed on the front image searched for by the search unit.

[0017] In a tenth aspect of the present embodiment, in the eighth or ninth aspect, the display control unit causes the display means to identifiably display an area corresponding to a characteristic part in the front image that corresponds to the characteristic area.

[0018] An eleventh aspect according to the present invention is any of the first to seventh aspects, further including a display control unit that causes a display unit to display the spectral distribution data and the depth information.

[0019] In a twelfth aspect of the embodiment, in any of the first to eleventh aspects, the depth information includes at least one of information representing a depth position, a depth range, and a layer region relative to a reference portion of the test eye.

[0020] A thirteenth aspect of the embodiment is an ophthalmic device including an illumination optical system that illuminates the test eye with illumination light, a light receiving optical system that receives return light of the illumination light from the test eye, the return light having different wavelength ranges, an OCT optical system that performs optical coherence tomography on the test eye, and an ophthalmic information processing device of any of the first to twelfth aspects.

[0021] A fourteenth aspect of the embodiment is an ophthalmologic information processing method including: a characteristic region identifying step of identifying a characteristic region in spectral distribution data acquired by receiving return light in a predetermined wavelength range from a test eye illuminated with illumination light; and a depth information identifying step of identifying depth information of the characteristic region based on measurement data of the test eye having a higher resolution in the depth direction than the spectral distribution data.

[0022] In a 15th aspect of the embodiment, in the 14th aspect, the characteristic region identifying step identifies the characteristic region in any one of a plurality of spectral distribution data obtained by illuminating the test eye with illumination light and receiving return light from the test eye having different wavelength ranges.

[0023] In a sixteenth aspect according to the present invention, in the fourteenth or fifteenth aspect, the measurement data is OCT data obtained by performing optical coherence tomography on the subject's eye.

[0024] In a seventeenth aspect of the embodiment, in the sixteenth aspect, the depth information identifying step includes a search step of searching for a front image having the highest correlation with the spectral distribution data from among a plurality of front images formed based on the OCT data and having different depth positions, and the depth information is identified based on the front image searched for in the search step.

[0025] In an 18th aspect of the embodiment, in the 16th aspect, the depth information identification step includes a search step of searching for a front image including an image area that has the highest correlation with an image including the characteristic area from among a plurality of front images formed based on the OCT data and having different depth positions, and the depth information is identified based on the front image searched in the search step.

[0026] A 19th aspect of the present invention is the 17th or 18th aspect, which includes an estimation step of estimating the presence or absence of a disease, the probability of a disease, or the type of disease based on the front image searched in the search step.

[0027] A twentieth aspect of the present invention is the 19th aspect, which includes a display control step of displaying disease information including the presence or absence of the disease, the probability of the disease, or the type of disease estimated in the estimation step on a display means.

[0028] A 21st aspect of the present invention is the 17th or 18th aspect, further including a display control step of causing a display unit to display the front image searched for in the searching step and the depth information.

[0029] A 22nd aspect of the present invention is the 17th or 18th aspect, further including a display control step of causing a display unit to display the spectral distribution data in a manner superimposed on the front image searched for in the search step.

[0030] In a 23rd aspect of the present invention, in the 21st or 22nd aspect, the display control step causes the display means to identifiably display an area corresponding to a characteristic part in the front image that corresponds to the characteristic area.

[0031] A 24th aspect of the embodiment is based on any of the 14th to 19th aspects and includes a display control step of causing a display unit to display the spectral distribution data and the depth information.

[0032] In a 25th aspect of the embodiment, in any of the 14th to 24th aspects, the depth information includes at least one of information representing a depth position, a depth range, and a layer region relative to a reference portion of the test eye.

[0033] A 26th aspect of the embodiment is a program that causes a computer to execute each step of the ophthalmologic information processing method according to any one of the 14th to 25th aspects.

[0034] The configurations according to the above-described multiple aspects can be combined in any manner. [Effects of the Invention]

[0035] According to the present invention, a new technique for analyzing spectral distribution data in more detail can be provided. [Brief explanation of the drawings]

[0036] [Figure 1]1 is a schematic diagram illustrating an example of the configuration of an optical system of an ophthalmologic apparatus according to an embodiment. [Figure 2] 1 is a schematic diagram illustrating an example of the configuration of an optical system of an ophthalmologic apparatus according to an embodiment. [Figure 3] FIG. 2 is a schematic diagram illustrating an example of the configuration of a control system of an ophthalmologic apparatus according to an embodiment. [Figure 4] FIG. 2 is a schematic diagram illustrating an example of the configuration of a control system of an ophthalmologic apparatus according to an embodiment. [Figure 5] FIG. 2 is a schematic diagram illustrating an example of the configuration of a control system of an ophthalmologic apparatus according to an embodiment. [Figure 6] 3A and 3B are schematic diagrams for explaining the operation of the ophthalmologic apparatus according to the embodiment. [Figure 7] 3A and 3B are schematic diagrams for explaining the operation of the ophthalmologic apparatus according to the embodiment. [Figure 8] 3A and 3B are schematic diagrams for explaining the operation of the ophthalmologic apparatus according to the embodiment. [Figure 9] 10 is a flowchart illustrating an example of an operation of the ophthalmologic apparatus according to the embodiment. [Figure 10] 10 is a flowchart illustrating an example of an operation of the ophthalmologic apparatus according to the embodiment. [Figure 11] 10 is a flowchart illustrating an example of an operation of the ophthalmologic apparatus according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0037] An ophthalmological information processing apparatus, an ophthalmological apparatus, an ophthalmological information processing method, and a program according to an embodiment of the present invention will be described in detail with reference to the drawings. Note that the embodiments may incorporate any of the techniques described in the documents cited in this specification.

[0038] An ophthalmologic information processing apparatus according to an embodiment acquires spectral distribution data of a subject's eye, and identifies information (depth information) representing the depth of the spectral distribution data based on measurement data of the subject's eye having a higher resolution in the depth direction than the spectral distribution data. In particular, the ophthalmologic information processing apparatus identifies a characteristic region in the spectral distribution data of the subject's eye, and can identify information (depth information) representing the depth of the identified characteristic region based on the measurement data of the subject's eye having a higher resolution in the depth direction than the spectral distribution data.

[0039] Spectral distribution data is acquired by receiving return light within a predetermined wavelength range from the subject's eye (e.g., fundus or anterior segment) illuminated with illumination light. Examples of spectral distribution data include spectral images (spectral fundus images, spectral anterior segment images) as two-dimensional spectral distributions. Examples of spectral images include hyperspectral images, multispectral images, and RGB color images. Examples of characteristic regions include blood vessels, optic discs, diseased areas, and abnormal areas.

[0040] In some embodiments, the plurality of spectral distribution data are acquired by illuminating the subject's eye with illumination light having two or more wavelength components in different wavelength ranges and selecting, from light returned from the subject's eye, light having wavelength components in a predetermined wavelength range. In some embodiments, the plurality of spectral distribution data are acquired by sequentially illuminating the subject's eye with illumination light having two or more wavelength components in different wavelength ranges and sequentially selecting, from light returned from the subject's eye, light having wavelength components in a predetermined wavelength range.

[0041] In some embodiments, illumination light having wavelength components in a predetermined wavelength range is sequentially selected from illumination light having two or more wavelength components with different wavelength ranges, the selected illumination light is sequentially used to illuminate the subject's eye, and the return light from the subject's eye is sequentially received, thereby acquiring multiple spectral distribution data.

[0042] In some embodiments, a light source capable of arbitrarily changing the wavelength range is used to sequentially emit illumination light having two or more wavelength components with different wavelength ranges, the emitted illumination light is sequentially used to illuminate the subject's eye, and the return light from the subject's eye is sequentially received, thereby obtaining multiple spectral distribution data.

[0043] In some embodiments, a plurality of spectral distribution data are obtained by illuminating the subject's eye with illumination light, sequentially changing the wavelength range in which the light-receiving device has high light-receiving sensitivity, and sequentially selecting the return light from the subject's eye.

[0044] The depth direction may be the traveling direction of illumination light that illuminates the eye, the depth direction of the eye, the direction from the superficial layer to the deep layer of the fundus, or the direction of the measurement optical axis (photography optical axis) for the eye. Examples of measurement data of the eye that has a higher resolution in the depth direction than spectral distribution data include OCT data obtained by performing OCT on the eye, and measurement data of the eye obtained using AO (Adaptive Optics)-SLO.

[0045] The OCT data is acquired, for example, by splitting light from an OCT light source into measurement light and reference light, projecting the measurement light onto the subject's eye, and detecting interference light between return light of the measurement light from the subject's eye and the reference light passing through the reference light path. In some embodiments, the ophthalmologic information processing device is configured to acquire OCT data acquired by an external OCT device. In some embodiments, the functions of the ophthalmologic information processing device are realized by an ophthalmologic device capable of acquiring OCT data.

[0046] In some embodiments, the ophthalmologic information processing device is configured to acquire measurement data obtained by an external AO-SLO device, and in some embodiments, the functionality of the ophthalmologic information processing device is realized by an ophthalmologic device having the AO-SLO functionality.

[0047] In some embodiments, multiple spectral distribution data are acquired by sequentially receiving return light of illumination light having different wavelength ranges in a predetermined analysis wavelength region. For first and second return light beams having adjacent wavelength ranges among the sequentially received return light beams, a portion of the wavelength range of the first return light beam may overlap with the wavelength range of the second return light beam. In this case, a process for identifying a characteristic region is performed for each of the multiple spectral distribution data. For example, depth information of the characteristic region is obtained in the spectral distribution data that can identify the characteristic region most accurately among the multiple spectral distribution data. For example, depth information of the characteristic region is obtained in desired spectral distribution data selected by a user or the like from the multiple spectral distribution data.

[0048] In some embodiments, the ophthalmologic information processing device searches for a front image having the highest correlation with the spectral distribution data from a plurality of front images (en-face image, C-scan image, projection image, OCT angiography) formed based on OCT data of the subject's eye and projected or integrated at different depth ranges. The ophthalmologic information processing device identifies depth information of the searched front image as depth information of the spectral distribution data.

[0049] This makes it possible to accurately identify which tissue in the depth direction of the measurement site a characteristic region identified from the spectral distribution data of the measurement site belongs to. It also makes it possible to correct positional deviations (e.g., in the x- and z-directions) of the spectral distribution data caused by eye movement. This makes it possible to perform more detailed analyses of the spectral distribution data (e.g., more detailed observation of characteristic regions, disease estimation).

[0050] An ophthalmologic information processing method according to an embodiment includes one or more steps executed by the ophthalmologic information processing device. A program according to an embodiment causes a computer (processor) to execute each step of the ophthalmologic information processing method according to an embodiment. A recording medium according to an embodiment is a non-transitory recording medium (storage medium) on which the program according to an embodiment is recorded.

[0051] In this specification, a processor includes circuits such as 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), or a field programmable gate array (FPGA)). The processor realizes the functions of the embodiments by, for example, reading and executing a program stored in a memory circuit or a storage device. The memory circuit or storage device may be included in the processor. Alternatively, the memory circuit or storage device may be provided external to the processor.

[0052] Hereinafter, a case where depth information is determined for a spectral fundus image as spectral distribution data of the fundus of the subject's eye will be described, but the configuration of the embodiment is not limited to this. For example, the following embodiment can also be applied to a case where depth information is determined for a spectral anterior segment image as spectral distribution data of an anterior segment other than the fundus.

[0053] In some embodiments, the ophthalmologic information-processing device is configured to acquire spectral power distribution data of the subject's eye acquired externally through a communication function. In some embodiments, an ophthalmologic device capable of acquiring the spectral power distribution data of the subject's eye has the functionality of the ophthalmologic information-processing device.

[0054] In the following embodiments, an ophthalmic apparatus including the functions of an ophthalmic information processing apparatus according to an embodiment will be described as an example. The ophthalmic apparatus according to the embodiment includes an ophthalmic imaging apparatus. The ophthalmic imaging apparatus included in the ophthalmic apparatus according to some embodiments is, for example, one or more of a fundus camera, a scanning optical ophthalmoscope, a slit lamp ophthalmoscope, a surgical microscope, etc. The ophthalmic apparatus according to some embodiments includes, in addition to the ophthalmic imaging apparatus, one or more of an ophthalmic measurement apparatus and an ophthalmic treatment apparatus. The ophthalmic measurement apparatus included in the ophthalmic apparatus according to some embodiments is, for example, one or more of an eye refraction examination apparatus, a tonometer, a specular microscope, a wavefront analyzer, a perimeter, a microperimeter, etc. The ophthalmic treatment apparatus included in the ophthalmic apparatus according to some embodiments is, for example, one or more of a laser treatment apparatus, a surgical apparatus, a surgical microscope, etc.

[0055] In the following embodiments, the ophthalmologic apparatus includes an optical coherence tomography (OCT) scanner and a fundus camera. While the swept-source OCT scanner is used, the type of OCT is not limited thereto, and other types of OCT (such as spectral domain OCT, time domain OCT, and amphas OCT) may also be used.

[0056] Hereinafter, the x direction is defined as the direction perpendicular to the optical axis direction of the objective lens (left-right direction), the y direction is defined as the direction perpendicular to the optical axis direction of the objective lens (up-down direction), and the z direction is defined as the direction of the optical axis of the objective lens.

[0057] <Configuration> [Optical system] As shown in FIG. 1, the ophthalmic apparatus 1 includes a fundus camera unit 2, an OCT unit 100, and an arithmetic and control unit 200. The fundus camera unit 2 is provided with an optical system and mechanisms for acquiring a front image of the subject's eye E. The OCT unit 100 is provided with a portion of the optical system and mechanisms for performing OCT. Other portions of the optical system and mechanisms for performing OCT are provided in the fundus camera unit 2. The arithmetic and control unit 200 includes one or more processors that perform various calculations and controls. In addition to these, the ophthalmic apparatus 1 may be provided with any other elements or units, such as members for supporting the subject's face (such as a chin rest or forehead rest) and a lens unit for switching the target region for OCT (for example, an attachment for anterior segment OCT). Furthermore, the ophthalmic apparatus 1 includes a pair of anterior segment cameras 5A and 5B.

[0058] [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 video shooting using near-infrared light. The photographed image is a still image using flash light or a spectral image (spectral fundus image, spectral anterior segment image). Furthermore, the fundus camera unit 2 can photograph the anterior segment Ea of the subject's eye E to acquire a front image (anterior segment image).

[0059] 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.

[0060] Light (observation illumination light) output from an observation light source 11 of an illumination optical system 10 is reflected by a reflecting mirror 12 having a curved reflecting surface, passes through a condenser lens 13, and passes 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 relay lenses 17 and 18, an aperture 19, and a relay lens 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 Ef or anterior segment Ea). 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 photographing 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 condenser lens 34. The image sensor 35 detects the returned light at a predetermined frame rate. The focus of the photographing optical system 30 is adjusted to match the fundus Ef or the anterior segment Ea.

[0061] The light (imaging illumination light) output from the imaging light source 15 is irradiated onto the fundus Ef through the same path as the observation illumination light. The return light of the imaging illumination light from the subject's eye E is guided to the dichroic mirror 33 through the same path as the return light of the observation illumination light, transmitted through the dichroic mirror 33, reflected by the mirror 36, and guided to the tunable filter 80.

[0062] The tunable filter 80 is a filter that can select the wavelength range of transmitted light in a predetermined analysis wavelength region. The wavelength range of light that passes through the tunable filter 80 can be selected arbitrarily.

[0063] In some embodiments, the tunable filter 80 is similar to the liquid crystal tunable filter disclosed in, for example, Japanese Patent Application Laid-Open No. 2006-158546. In this case, the tunable filter 80 can arbitrarily select the wavelength selection range of transmitted light by changing the voltage applied to the liquid crystal.

[0064] In some embodiments, the wavelength-tunable filter 80 may include two or more wavelength-selective filters having different wavelength selection ranges for transmitted light, and may be configured so that the two or more wavelength-selective filters can be selectively positioned in the optical path of the return light of the illumination light.

[0065] In some embodiments, the tunable filter 80 is a filter that can select a wavelength range of reflected light in a predetermined analysis wavelength region.

[0066] The light returning from the mirror 36 and transmitted through the wavelength tunable filter 80 is focused by the condenser lens 37 onto the light receiving surface of the image sensor 38 .

[0067] In some embodiments, the tunable filter 80 is disposed between the dichroic mirror 33 and the collecting lens 34 .

[0068] In some embodiments, the tunable filter 80 is configured to be insertable into and removable from the optical path between the dichroic mirror 33 or mirror 36 and the condenser lens 37. For example, when the tunable filter 80 is disposed in the optical path between the dichroic mirror 33 and the condenser lens 37, the ophthalmic apparatus 1 can acquire a plurality of spectral fundus images by sequentially acquiring the reception results of the returned light obtained by the image sensor 38. For example, when the tunable filter 80 is retracted from the optical path between the dichroic mirror 33 and the condenser lens 37, the ophthalmic apparatus 1 can acquire a normal still image (fundus image, anterior eye image) by acquiring the reception results of the returned light obtained by the image sensor 38.

[0069] The display device 3 displays an image (observation image) based on the fundus reflected light detected by the image sensor 35. When the focus of the photographing optical system 30 is adjusted to the anterior segment, an observation image of the anterior segment of the subject's eye E is displayed. The display device 3 also displays an image (photographed image, spectral fundus image) based on the fundus reflected light detected by the image sensor 38. The display device 3 that displays the observation image and the display device 3 that displays the photographed image may be the same or different. When the subject's eye E is illuminated with infrared light and similar photographing is performed, an infrared photographed image is displayed.

[0070] A fixation target and a visual target for visual acuity testing are displayed on an LCD (Liquid Crystal Display) 39. A portion of the light beam output from the LCD 39 is reflected by a half mirror 33A, reflected by a mirror 32, passes through a photographing focusing lens 31, and passes through a hole in the aperture mirror 21. The light beam that has passed through the hole in the aperture mirror 21 passes through a dichroic mirror 46, is refracted by the objective lens 22, and is projected onto the fundus Ef.

[0071] The fixation position of the subject's eye E can be changed by changing the display position of the fixation target on the screen of the LCD 39. Examples of fixation positions include a fixation position for acquiring an image centered on the macula, a fixation position for acquiring an image centered on the optic disc, a fixation position for acquiring an image centered on the fundus between the macula and the optic disc, and a fixation position for acquiring an image of a region far removed from the macula (periphery of the fundus). The ophthalmologic apparatus 1 according to some embodiments includes a GUI (Graphical User Interface) or the like for specifying at least one of such fixation positions. The ophthalmologic apparatus 1 according to some embodiments includes a GUI or the like for manually moving the fixation position (display position of the fixation target).

[0072] The configuration for presenting a movable fixation target to the subject's eye E is not limited to a display device such as an LCD. For example, a movable fixation target can be generated by selectively illuminating a plurality of light sources in a light source array (such as a light-emitting diode (LED) array). Also, a movable fixation target can be generated by one or more movable light sources.

[0073] 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 insertable into and removable from the illumination optical path. When performing focus adjustment, the reflective surface of the reflecting rod 67 is tilted and positioned in the illumination optical path. The focusing light output from the LED 61 passes through the relay lens 62, is split into two beams by the split index plate 63, passes through the two-hole diaphragm 64, is reflected by the mirror 65, and is once imaged and reflected on the reflective surface of the reflecting rod 67 by the condenser lens 66. The focusing light further passes through the relay lens 20, is reflected by the aperture mirror 21, passes through the dichroic mirror 46, is refracted by the objective lens 22, and is projected onto the fundus Ef. The fundus reflection light of the focusing light is guided to the image sensor 35 via the same path as the return light of the observation illumination light. Manual focusing and autofocusing can be performed based on the received light image (split target image).

[0074] The dichroic mirror 46 combines the optical path for fundus imaging and the optical path for OCT. The dichroic mirror 46 reflects light in the wavelength band used for OCT and transmits light for fundus imaging. The OCT optical path (optical path of measurement light) is provided with a collimator lens unit 40, an optical path length changing unit 41, an optical scanner 42, an OCT focusing lens 43, a mirror 44, and a relay lens 45 in this order from the OCT unit 100 side to the dichroic mirror 46 side.

[0075] The optical path length changing unit 41 is movable in the direction of the arrow shown in Figure 1 to change the length of the OCT optical path. This change in optical path length is used for correcting the optical path length according to the axial length of the eye, adjusting the interference state, etc. The optical path length changing unit 41 includes a corner cube and a mechanism for moving it.

[0076] The optical scanner 42 is disposed at a position optically conjugate with the pupil of the subject's eye E. The optical scanner 42 deflects the measurement light LS passing through the OCT optical path. The optical scanner 42 is, for example, a galvano scanner capable of two-dimensional scanning.

[0077] The OCT focusing lens 43 is moved along the optical path of the measurement light LS to adjust the focus of the OCT optical system. 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.

[0078] [Anterior Eye Cameras 5A and 5B] The anterior eye cameras 5A and 5B are used to determine the relative position between the optical system of the ophthalmic apparatus 1 and the subject's eye E, similar to the invention disclosed in Japanese Patent Application Laid-Open No. 2013-248376. The anterior eye cameras 5A and 5B are provided on the surface of a housing (such as the fundus camera unit 2) that houses the optical system, facing the subject's eye E. The ophthalmic apparatus 1 determines the three-dimensional relative position between the optical system and the subject's eye E by analyzing two anterior eye images acquired substantially simultaneously from different directions by the anterior eye cameras 5A and 5B. The analysis of the two anterior eye images may be similar to the analysis disclosed in Japanese Patent Application Laid-Open No. 2013-248376. The number of anterior eye cameras may be any number equal to or greater than two.

[0079] In this example, the position of the subject's eye E (i.e., the relative position between the subject's eye E and the optical system) is determined using two or more anterior segment cameras, but the method for determining the position of the subject's eye E is not limited to this. For example, the position of the subject's eye E can be determined by analyzing a front image of the subject's eye E (e.g., an observation image of the anterior segment Ea). Alternatively, a means for projecting an index onto the cornea of ​​the subject's eye E can be provided, and the position of the subject's eye E can be determined based on the projection position of this index (i.e., the detection state of the corneal reflected light beam of this index).

[0080] [OCT Unit 100] As illustrated in Fig. 2, the OCT unit 100 is provided with an optical system for performing swept-source OCT. This optical system includes an interference optical system. This interference optical system has the following functions: splitting light from a wavelength-tunable light source (swept-wavelength light source) into measurement light and reference light; generating interference light by superimposing return light of the measurement light from the subject's eye E on the reference light that has passed through the reference light path; and detecting this interference light. The detection result (detection signal) of the interference light obtained by the interference optical system is a signal indicating the spectrum of the interference light, and is sent to the arithmetic and control unit 200.

[0081] The light source unit 101 includes, for example, a near-infrared wavelength-tunable laser that changes the wavelength of the emitted light at high speed. The 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, whose polarization state has been adjusted, is guided by an optical fiber 104 to a fiber coupler 105, where it is split into a measurement light LS and a reference light LR.

[0082] 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 corner cube 114 via an optical path length correction member 112 and a dispersion compensation member 113. The optical path length correction member 112 acts to match the optical path length of the reference light LR with the optical path length of the measurement light LS. The dispersion compensation member 113 acts to match the dispersion characteristics between the reference light LR and the measurement light LS. The corner cube 114 is movable in the incident direction of the reference light LR, thereby changing the optical path length of the reference light LR.

[0083] The reference light LR that has passed through the corner cube 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 the optical fiber 117. The reference light LR that has entered the optical fiber 117 is guided to the polarization controller 118 where its polarization state is adjusted, is guided by the optical fiber 119 to the attenuator 120 where the light amount is adjusted, and is guided by the optical fiber 121 to the fiber coupler 122.

[0084] Meanwhile, 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, and passes through the optical path length changing unit 41, the optical scanner 42, the OCT focusing lens 43, the mirror 44, and the relay lens 45. After passing through the relay lens 45, the measurement light LS is reflected by the dichroic mirror 46, refracted by the objective lens 22, and enters the subject's eye E. The measurement light LS is scattered and reflected at various depth positions in the subject's eye E. The return light of the measurement light LS from the subject's eye E travels the same path as the outward path in the reverse direction, guided to the fiber coupler 105, and reaches the fiber coupler 122 via the optical fiber 128. The incident end of the optical fiber 127 into which the measurement light LS is incident is positioned approximately conjugate with the fundus Ef of the subject's eye E.

[0085] The fiber coupler 122 generates interference light by combining (causing interference between) 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 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 a detector 125 via optical fibers 123 and 124, respectively.

[0086] The detector 125 is, for example, a balanced photodiode. The balanced photodiode includes a pair of photodetectors that respectively detect a pair of interference lights LC, and outputs the difference between the pair of detection results obtained by these photodetectors. The detector 125 sends this output (detection signal) to a DAQ (Data Acquisition System) 130.

[0087] The DAQ 130 is supplied with a clock KC 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. For example, the light source unit 101 optically delays one of two branched lights obtained by branching light L0 of each output wavelength, and then generates the clock KC based on the result of detecting the combined light. The DAQ 130 samples the detection signal input from the detector 125 based on the clock KC. The DAQ 130 sends the sampling result of the detection signal from the detector 125 to the arithmetic and control unit 200.

[0088] In this example, both an optical path length changer 41 for changing the length of the optical path (measurement optical path, measurement arm) of the measurement light LS and a corner cube 114 for changing the length of the optical path (reference optical path, reference arm) of the reference light LR are provided. However, only one of the optical path length changer 41 and the corner cube 114 may be provided. It is also possible to change the difference between the measurement optical path length and the reference optical path length using optical members other than these.

[0089] [Control system] 3 to 5 show an example of the configuration of the control system of the ophthalmic apparatus 1. Some of the components included in the ophthalmic apparatus 1 are omitted in FIGS. 3 to 5. In FIG. 3, the same components as those in FIGS. 1 and 2 are denoted by the same reference numerals, and descriptions thereof will be omitted where appropriate. The control unit 210, image forming unit 220, and data processing unit 230 are provided in, for example, an arithmetic control unit 200.

[0090] <Control unit 210> The control unit 210 executes various controls and includes a main control unit 211 and a storage unit 212.

[0091] <Main control unit 211> The main controller 211 includes a processor (for example, a control processor) and controls each part (including each element shown in FIGS. 1 to 5) of the ophthalmologic apparatus 1. For example, the main controller 211 controls each part of the optical system of the fundus camera unit 2 shown in FIGS. 1 and 2, each part of the optical system of the OCT unit 100, the anterior eye cameras 5A and 5B, the moving mechanism 150 that moves the above-mentioned optical systems, the image forming unit 220, the data processing unit 230, and the user interface (UI) 240.

[0092] The control of the fundus camera unit 2 includes control of the focusing drivers 31A and 43A, control of the wavelength tunable filter 80, control of the image sensors 35 and 38, control of the optical path length changer 41, and control of the optical scanner 42.

[0093] Control over the focus driver 31A includes control to move the photographing focus lens 31 in the optical axis direction. Control over the focus driver 43A includes control to move the OCT focus lens 43 in the optical axis direction.

[0094] The control of the wavelength tunable filter 80 includes the selection control of the wavelength range of transmitted light (for example, the control of the voltage applied to the liquid crystal).

[0095] Control of the image sensors 35, 38 includes control of the light receiving sensitivity of the image sensor, control of the frame rate (light receiving timing, exposure time), control of the light receiving area (position, size, etc.), and control of readout of the light receiving results from the image sensor. In some embodiments, the image sensors 35, 38 are controlled by changing the exposure time according to the wavelength range of the returned light so that the received light intensity is uniform across each wavelength range of the analysis wavelength range in which multiple spectral fundus images are acquired. In some embodiments, the main controller 211 controls the light intensity of the wavelength components of each wavelength range of the illumination light so that the received light intensity is uniform across each wavelength range of the analysis wavelength range in which multiple spectral fundus images are acquired.

[0096] Control of the LCD 39 includes control of the fixation position. For example, the main control unit 211 displays a fixation target at a position on the screen of the LCD 39 that corresponds to a manually or automatically set fixation position. The main control unit 211 can also change (continuously or stepwise) the display position of the fixation target displayed on the LCD 39. This makes it possible to move the fixation target (i.e., change the fixation position). The display position and movement manner of the fixation target are set manually or automatically. Manual setting is performed using, for example, a GUI. Automatic setting is performed by, for example, the data processing unit 230.

[0097] The control over the optical path length changing unit 41 includes control to change the optical path length of the measurement light LS. The main control unit 211 controls a drive unit that drives the corner cube of the optical path length changing unit 41 to move the optical path length changing unit 41 along the optical path of the measurement light LS and change the optical path length of the measurement light LS.

[0098] The control of the optical scanner 42 includes control of the scan mode, scan range (scan start position, scan end position), scan speed, etc. The main controller 211 controls the optical scanner 42, thereby enabling an OCT scan to be performed with the measurement light LS on a desired region in the measurement region (image capture region).

[0099] The main control unit 211 also controls the observation light source 11, the imaging light source 15, the focus optical system 60, and the like.

[0100] The control over the OCT unit 100 includes control over the light source unit 101, control over the reference driver 114A, control over the detector 125, and control over the DAQ .

[0101] Control of the light source unit 101 includes control of turning the light source on and off, control of the amount of light emitted from the light source, control of the wavelength sweep range, control of the wavelength sweep speed, and control of the emission timing of light of each wavelength component.

[0102] The control over the reference driver 114A includes control to change the optical path length of the reference light LR. The main controller 211 controls the reference driver 114A to move the corner cube 114 along the optical path of the reference light LR, thereby changing the optical path length of the reference light LR.

[0103] Control of the detector 125 includes control of the light receiving sensitivity of the detection elements, control of the frame rate (light receiving timing), control of the light receiving area (position, size, dimension), and control of reading out the light receiving results of the detection elements.

[0104] The control over the DAQ 130 includes control of capturing the detection results of the interference light obtained by the detector 125 (capture timing, sampling timing), and control of reading out the interference signal corresponding to the detection results of the captured interference light.

[0105] Control of the anterior eye cameras 5A and 5B includes control of the light receiving sensitivity of each camera, control of the frame rate (light receiving timing), and synchronization control of the anterior eye cameras 5A and 5B.

[0106] The movement mechanism 150 moves at least the fundus camera unit 2 (optical system) three-dimensionally, for example. In a typical example, the movement mechanism 150 includes at least a mechanism for moving the fundus camera unit 2 in the x direction (left-right direction), a mechanism for moving it in the y direction (up-down direction), and a mechanism for moving it in the z direction (depth direction, front-back direction). The mechanism for movement in the x direction includes, for example, an x-stage movable in the x direction and an x-movement mechanism for moving the x-stage. The mechanism for movement in the y direction includes, for example, a y-stage movable in the y direction and a y-movement mechanism for moving the y-stage. The mechanism for movement in the z direction includes, for example, a z-stage movable in the z direction and a z-movement mechanism for moving the z-stage. Each movement mechanism includes a pulse motor as an actuator and operates under the control of the main controller 211.

[0107] Control of the moving mechanism 150 is used for alignment and tracking. Tracking is the act of moving the device optical system in accordance with the eye movement of the subject's eye E. When tracking is performed, alignment and focus adjustment are performed beforehand. Tracking is a function of maintaining a suitable positional relationship where alignment and focus are achieved by making the position of the device optical system follow the eye movement. In some embodiments, the moving mechanism 150 is configured to be controlled to change the optical path length of the reference light (and therefore the optical path length difference between the optical path of the measurement light and the optical path of the reference light).

[0108] In the case of manual alignment, the user operates the user interface 240 to move the optical system relative to the eye E so that the displacement of the eye E relative to the optical system is canceled. For example, the main control unit 211 controls the movement mechanism 150 by outputting a control signal corresponding to the operation content on the user interface 240 to the movement mechanism 150, thereby moving the optical system relative to the eye E.

[0109] In the case of auto-alignment, the main controller 211 controls the moving mechanism 150 to move the optical system relative to the subject's eye E so that displacement of the subject's eye E relative to the optical system is canceled. Specifically, as described in Japanese Patent Application Laid-Open No. 2013-248376, calculation processing is performed using trigonometry based on the positional relationship between the pair of anterior eye cameras 5A and 5B and the subject's eye E, and the main controller 211 controls the moving mechanism 150 so that the positional relationship of the subject's eye E with respect to the optical system becomes a predetermined positional relationship. In some embodiments, the main controller 211 controls the moving mechanism 150 by outputting a control signal to the moving mechanism 150 so that the optical axis of the optical system substantially coincides with the axis of the subject's eye E and the distance of the optical system from the subject's eye E is a predetermined working distance, thereby moving the optical system relative to the subject's eye E. Here, the working distance is a predetermined value also called the working distance of the objective lens 22, and corresponds to the distance between the subject's eye E and the optical system during measurement (photography) using the optical system.

[0110] The main controller 211, as a display controller, can display various types of information on the display unit 240A. For example, the main controller 211 associates a plurality of spectral fundus images with wavelength ranges and displays them on the display unit 240A. For example, the main controller 211 displays the analysis processing results obtained by the analysis unit 231 (described later) on the display unit 240A.

[0111] <Storage section 212> The storage unit 212 stores various data. The functions of the storage unit 212 are realized by a storage device such as a memory or a storage device. Examples of data stored in the storage unit 212 include control parameters, image data of fundus images, image data of anterior segment images, OCT data (including OCT images), spectral image data of fundus images, spectral image data of anterior segment images, and information about the subject's eye. Examples of control parameters include hyperspectral imaging control data. The hyperspectral imaging control data is control data for acquiring multiple fundus images based on returned light having different center wavelengths within a predetermined analysis wavelength range. Examples of hyperspectral imaging control data include the analysis wavelength range in which multiple spectral fundus images are acquired, the wavelength range in which each spectral fundus image is acquired, the center wavelength, the center wavelength step, and control data for the wavelength-tunable filter 80 corresponding to the center wavelength. The information about the subject's eye includes information about the subject, such as a patient ID and name, identification information for the left eye / right eye, and information about the subject's eye, such as electronic medical record information. The storage unit 212 stores programs for executing various processors (control processor, image forming processor, data processing processor).

[0112] <Image forming unit 220> The image forming unit 220 includes a processor (e.g., an image forming processor) and forms an OCT image (image data) of the subject's eye E based on the output (sampling results of the detection signals) from the DAQ 130. For example, similar to conventional swept-source OCT, the image forming unit 220 performs signal processing on the spectral distribution based on the sampling results for each A-line to form a reflection intensity profile for each A-line, and then images these A-line profiles and arranges them along the scan line. The signal processing includes noise removal (noise reduction), filtering, FFT (Fast Fourier Transform), etc. When performing other types of OCT, the image forming unit 220 performs known processing appropriate for the type.

[0113] Data Processing Unit 230 Data processing unit 230 includes a processor (for example, a data processor) and performs image processing and analysis processing on the image formed by image forming unit 220. At least two of the processor included in main control unit 211, the processor included in data processing unit 230, and the processor included in image forming unit 220 may be configured by a single processor.

[0114] The data processing unit 230 performs known image processing, such as interpolation processing that interpolates pixels between tomographic images, to form image data of a three-dimensional image of the fundus oculi Ef or the anterior segment Ea. Note that image data of a three-dimensional image refers to image data in which pixel positions are defined by a three-dimensional coordinate system. Image data of a three-dimensional image includes image data consisting of three-dimensionally arranged voxels. This image data is called volume data or voxel data. When displaying an image based on the volume data, the data processing unit 230 performs rendering processing (volume rendering, MIP (Maximum Intensity Projection), etc.) on the volume data to form image data of a pseudo three-dimensional image as viewed from a specific line of sight. This pseudo three-dimensional image is displayed on a display device, such as the display unit 240A.

[0115] It is also possible to form stack data of multiple tomographic images as image data of a three-dimensional image. Stack data is image data obtained by arranging multiple tomographic images obtained along multiple scan lines in a three-dimensional manner based on the positional relationship of the scan lines. In other words, stack data is image data obtained by expressing multiple tomographic images that were originally defined using separate two-dimensional coordinate systems using a single three-dimensional coordinate system (i.e., embedding them in a single three-dimensional space).

[0116] In some embodiments, the data processing unit 230 generates a B-scan image by arranging A-scan images in the B-scan direction. In some embodiments, the data processing unit 230 can generate a B-mode image (B-scan image) (longitudinal or axial image) of an arbitrary cross section, a C-mode image (C-scan image) (transverse or horizontal image) of an arbitrary cross section, a projection image, a shadowgram, or the like, by performing various rendering operations on the acquired three-dimensional data set (volume data, stack data, etc.). An image of an arbitrary cross section, such as a B-scan image or a C-scan image, is generated by selecting pixels (voxels) on a specified cross section from the three-dimensional data set. A projection image is generated by projecting the three-dimensional data set in a predetermined direction (z direction, depth direction, axial direction). A shadowgram is generated by projecting a portion of the three-dimensional data set (e.g., partial data corresponding to a specific layer) in a predetermined direction. By changing the depth range in the layer direction to be integrated, two or more different shadowgrams can be generated. Images viewed from the front side of the subject's eye, such as C-scan images, projection images, and shadowgrams, are called en-face images.

[0117] The data processing unit 230 can construct B-scan images and front images (vessel-enhanced images, angiograms) in which retinal blood vessels and choroidal blood vessels are emphasized based on data collected in time series by OCT (for example, B-scan image data). For example, time-series OCT data can be collected by repeatedly scanning approximately the same region of the subject's eye E.

[0118] In some embodiments, the data processor 230 compares time-series B-scan images obtained by B-scanning approximately the same region, and constructs an enhanced image in which the changed region is emphasized by converting pixel values ​​of the changed region in signal intensity into pixel values ​​corresponding to the changed region. Furthermore, the data processor 230 extracts information of a predetermined thickness of a desired region from the constructed multiple enhanced images, and constructs the information as an en-face image to form an OCTA (angiography) image.

[0119] Such a data processing unit 230 includes an analysis unit 231 .

[0120] <Analysis Department 231> As shown in FIG. 4, the analysis section 231 includes a characteristic portion identification section 231A, a three-dimensional position calculation section 231B, and a spectral distribution data processing section 231C.

[0121] The analysis unit 231 can analyze an image (including a spectral fundus image) of the subject's eye E and identify characteristic parts depicted in the image. For example, the analysis unit 231 determines the three-dimensional position of the subject's eye E based on the positions of the anterior eye cameras 5A and 5B and the positions of the identified characteristic parts. The main control unit 211 aligns the optical system with the subject's eye E by moving the optical system relative to the subject's eye E based on the determined three-dimensional position.

[0122] The analysis unit 231 can also perform predetermined analysis processing on the plurality of spectral fundus images. Examples of the predetermined analysis processing include a comparison processing of any two of the plurality of spectral fundus images, an extraction processing of a common region or a difference region identified by the comparison processing, a processing of identifying a region of interest or a characteristic region in at least one of the plurality of spectral fundus images, a processing of identifying and displaying the common region, the difference region, the region of interest, or the characteristic region in the spectral fundus images, and a processing of combining at least two of the plurality of spectral fundus images.

[0123] Furthermore, the analysis unit 231 identifies depth information of a characteristic region in any of the plurality of spectral fundus images, and identifies the depth information of the identified characteristic region based on the OCT data as measurement data. In some embodiments, the analysis unit 231 aligns the plurality of spectral fundus images based on the OCT data so that each portion in each spectral fundus image coincides in the z direction, and can identify a characteristic region in any of the aligned spectral fundus images.

[0124] <Characteristic part identification unit 231A> The characteristic portion identifying unit 231A analyzes each captured image obtained by the anterior eye cameras 5A and 5B to identify a position in the captured image corresponding to a characteristic portion of the anterior eye Ea (referred to as a characteristic portion). As the characteristic portion, for example, the pupil region of the subject's eye E, the pupil center position of the subject's eye E, the pupil centroid position, the corneal center position, the corneal apex position, the subject's eye center position, or the iris is used. Below, a specific example of processing for identifying the pupil center position of the subject's eye E will be described.

[0125] First, the characteristic part identification unit 231A identifies an image region (pupil region) corresponding to the pupil of the subject's eye E based on the distribution of pixel values ​​(such as brightness values) of the captured image. Since the pupil is generally depicted with lower brightness than other parts, the pupil region can be identified by searching for an image region with low brightness. At this time, the pupil region may be identified taking into consideration the shape of the pupil. In other words, the characteristic part identification unit 231A can be configured to identify the pupil region by searching for an image region with a substantially circular shape and low brightness.

[0126] Next, characteristic portion identification unit 231A identifies the center position of the identified pupil region. Because the pupil is approximately circular as described above, the outline of the pupil region is identified, and the center position of this outline (an approximate circle or ellipse) is identified and can be used as the pupil center position. Alternatively, the center of gravity of the pupil region may be found, and this center position may be identified as the pupil center position.

[0127] Note that even when identifying a feature position corresponding to another feature portion, it is possible to identify the feature position based on the distribution of pixel values ​​of the captured image in the same manner as described above.

[0128] The characteristic part specifying unit 231A can sequentially specify characteristic positions corresponding to characteristic parts in the photographed images sequentially obtained by the anterior eye cameras 5A and 5B. Furthermore, the characteristic part specifying unit 231A may specify characteristic positions every arbitrary number of frames greater than or equal to one in the photographed images sequentially obtained by the anterior eye cameras 5A and 5B.

[0129] <3D position calculation unit 231B> The three-dimensional position calculation unit 231B identifies the three-dimensional position of the characteristic site as the three-dimensional position of the subject's eye E based on the positions of the anterior-segment cameras 5A and 5B and the characteristic position corresponding to the characteristic site identified by the characteristic site identification unit 231A. As disclosed in Japanese Patent Application Laid-Open No. 2013-248376, the three-dimensional position calculation unit 231B calculates the three-dimensional position of the subject's eye E by applying known trigonometry to the positions (known) of the two anterior-segment cameras 5A and 5B and the positions corresponding to the characteristic sites in the two captured images. The three-dimensional position calculated by the three-dimensional position calculation unit 231B is sent to the main controller 211. Based on the three-dimensional position, the main controller 211 controls the movement mechanism 150 so that the positions in the x and y directions of the optical axis of the optical system coincide with the positions in the x and y directions of the three-dimensional position and so that the distance in the z direction is a predetermined working distance.

[0130] <Spectral distribution data processing unit 231C> The spectral distribution data processing unit 231C executes a process of identifying depth information of the spectral distribution data based on the OCT data. In particular, the spectral distribution data processing unit 231C executes a process of identifying a characteristic region in a spectral fundus image as spectral distribution data and identifying depth information of the identified characteristic region. Furthermore, the spectral distribution data processing unit 231C can estimate the presence or absence of a disease, the probability of a disease, or the type of disease based on the characteristic region identified by the above process. In particular, the spectral distribution data processing unit 231C can estimate the presence or absence of a disease with high accuracy based on the characteristic region whose depth information is identified by the above process.

[0131] 5, the spectral distribution data processing unit 231C includes a characteristic region specifying unit 2311C, a depth information specifying unit 2312C, and a disease estimation unit 2314C. The depth information specifying unit 2312C includes a search unit 2313C.

[0132] <Feature region identification unit 2311C> The characteristic region identifying unit 2311C identifies a characteristic region in the spectral fundus image. In this case, the characteristic region may be a blood vessel, a diseased region, an optic disc, an abnormal region, a region characterized by a change in pixel brightness, etc. The characteristic region identifying unit 2311C may identify a characteristic region designated using the operation unit 240B of the user interface 240 as a characteristic region in the spectral distribution data.

[0133] In some embodiments, the characteristic region identifying unit 2311C identifies a characteristic region for each of the plurality of spectral fundus images. The characteristic region may be two or more regions. In some embodiments, the characteristic region identifying unit 2311C identifies a characteristic region for one or more spectral fundus images selected from the plurality of spectral fundus images.

[0134] In some embodiments, the characteristic region identifying unit 2311C performs principal component analysis on the spectral fundus image and identifies the characteristic region using the results of the principal component analysis. For example, in the principal component analysis of the spectral fundus image, one or more principal components are sequentially identified so as to maximize the variance (variation). Each principal component reflects a characteristic region (characteristic part).

[0135] Specifically, the characteristic region identifying unit 2311C first calculates the center of gravity (average value) of all data of the spectral fundus image, identifies the direction from the calculated center of gravity in which the variance of the data is maximum as the first principal component, and identifies the second principal component in which the variance is maximum in a direction perpendicular to the identified first principal component. Next, the characteristic region identifying unit 2311C identifies the (n+1)th principal component in which the variance is maximum in a direction perpendicular to the most recently identified nth (n is an integer of 2 or more) principal component, and identifies principal components sequentially up to a predetermined dimension.

[0136] A method for identifying a characteristic region by applying principal component analysis to such a spectral fundus image is exemplified in, for example, Japanese Patent Application Laid-Open No. 2007-330558. In this method, the first principal component reflects the basic shape of the retina, the second principal component reflects the interchoroidal vessels, the third principal component reflects the retinal veins, and the fifth principal component reflects the entire retinal vessels. For example, by removing the third principal component representing the retinal veins from the fifth principal component representing the entire retinal vessels, it is possible to extract a component representing the retinal arteries. In other words, each principal component obtained by principal component analysis reflects a characteristic region (characteristic site) in the spectral distribution data, and it is possible to identify a characteristic region in the spectral distribution data using the results of the principal component analysis.

[0137] In some embodiments, the characteristic region identifying unit 2311C identifies a characteristic region in the spectral fundus image using at least one of an eigenvalue, a contribution rate, and a cumulative contribution rate corresponding to each principal component obtained by principal component analysis of the spectral fundus image.

[0138] In some embodiments, the characteristic region identifying unit 2311C identifies a characteristic region based on a comparison result obtained by comparing a plurality of spectral fundus images. For example, the characteristic region identifying unit 2311C identifies a characteristic region by comparing two spectral fundus images having adjacent wavelength ranges. For example, the characteristic region identifying unit 2311C identifies a characteristic region by comparing spectral fundus images of two predetermined wavelength ranges.

[0139] <Depth information determination unit 2312C> The depth information identifying section 2312C identifies depth information of the characteristic region identified by the characteristic region identifying section 2311C.

[0140] Examples of depth information include information representing a position in the depth direction, which is the direction of the measurement optical axis, based on a predetermined reference site, information representing a range of positions in the depth direction, information representing a layer region, information representing a tissue, etc. Examples of the predetermined reference site include the surface of the fundus of the subject's eye, a predetermined layer region constituting the retina of the subject's eye, the corneal apex of the subject's eye, a site where the intensity of reflected light from the subject's eye is maximum, a predetermined site constituting the anterior segment of the subject's eye, etc.

[0141] The depth information identifying unit 2312C identifies depth information of the feature region identified by the feature region identifying unit 2311C using OCT data, which has a higher resolution in the depth direction than the spectral distribution data. Specifically, the depth information identifying unit 2312C searches the OCT data for a region that has the highest correlation with the feature region identified by the feature region identifying unit 2311C. The depth information identifying unit 2312C identifies the depth information of the searched region of the OCT data as the depth information of the feature region identified by the feature region identifying unit 2311C.

[0142] In some embodiments, the main controller 211, as a display controller, causes the display unit 240A to display the spectral fundus image (spectral distribution data) and the depth information identified by the depth information identifying unit 2312C. At this time, the main controller 211 causes the display unit 240A to display the OCT data corresponding to the depth information together with the spectral fundus image and the depth information.

[0143] <Exploration Department 2313C> The search unit 2313C searches for a region in the OCT data (e.g., three-dimensional OCT data) that has the highest correlation with the spectral fundus image in a predetermined wavelength range. In some embodiments, the search unit 2313C calculates multiple correlations between each of multiple regions of the OCT data and the spectral fundus image, and identifies the region of the OCT data that has the highest correlation from the calculated multiple correlations.

[0144] For example, multiple front images (en-face image, C-scan image, projection image, OCT angiography) at different depth positions are formed in advance based on OCT data of the subject's eye E. In this case, the search unit 2313C calculates multiple correlations between each of the multiple front images and a spectral distribution image of a predetermined wavelength range. The search unit 2313C identifies the front image with the highest correlation, and specifies the depth information of the identified front image as the depth information of the spectral fundus image.

[0145] In some embodiments, the search unit 2313C obtains the above-mentioned multiple correlation degrees for a three-dimensional OCT image of the subject's eye E formed based on OCT data of the subject's eye E, and identifies an area of ​​the three-dimensional image with the highest correlation degree from the obtained multiple correlation degrees. The depth information identification unit 2312C identifies depth information in the identified area of ​​the three-dimensional image as depth information of the spectral fundus image.

[0146] Furthermore, the search unit 2313C can search for a region in the OCT data that has the highest degree of correlation with the feature region (in a broader sense, the spectral distribution data) identified by the feature region identification unit 2311C. In some embodiments, the search unit 2313C finds multiple degrees of correlation between each of multiple regions of the OCT data and the feature region identified by the feature region identification unit 2311C, and identifies the region of the OCT data that has the highest degree of correlation from the multiple degrees of correlation found.

[0147] For example, multiple front images having different depth positions are formed in advance based on OCT data of the subject's eye E. In this case, the search unit 2313C calculates multiple correlations between each of multiple regions of the front image and the characteristic region identified by the characteristic region identification unit 2311C for each of the multiple front images. The search unit 2313C identifies the region in each front image that has the highest correlation with the characteristic region, and identifies the front image including the region with the highest correlation from among the multiple front images in which the region with the highest correlation has been identified. The search unit 2313C identifies depth information of the identified front image as depth information of the characteristic region identified by the characteristic region identification unit 2311C.

[0148] In some embodiments, the search unit 2313C obtains the above-mentioned multiple correlation degrees for a three-dimensional OCT image of the subject's eye E formed based on OCT data of the subject's eye E, and identifies a region of the three-dimensional image with the highest correlation degree from the obtained multiple correlation degrees. The depth information identification unit 2312C identifies depth information of the identified region of the three-dimensional image as depth information of the feature region identified by the feature region identification unit 2311C.

[0149] <Disease Estimation Department 2314C> The disease estimation unit 2314C estimates the presence or absence of a disease, the probability of a disease, or the type of disease based on the front image searched by the search unit 2313C (or a region in the front image corresponding to the feature region identified by the feature region identification unit 2311C). In some embodiments, the disease estimation unit 2314C estimates the presence or absence of a disease, the probability of a disease, or the type of disease based on two or more front images in a predetermined depth range that includes the searched front image.

[0150] For example, the disease estimation unit 2314C has pre-registered multiple image patterns corresponding to different types of disease. The disease estimation unit 2314C calculates the correlation between the searched front image (or the above-mentioned region in the front image) and each of the multiple image patterns, and generates disease information indicating that the subject's eye E is estimated to have a disease when the correlation is equal to or greater than a predetermined threshold. The disease estimation unit 2314C can generate disease information indicating that the subject's eye E is estimated to have a disease and the type of disease corresponding to the image pattern having a correlation equal to or greater than the threshold. Furthermore, when the correlation is less than a predetermined threshold, the disease estimation unit 2314C generates disease information indicating that the subject's eye E is estimated to have no disease.

[0151] The main controller 211 can cause the display unit 240A to display disease information including the presence or absence of a disease, the probability of the disease, or the type of disease. In some embodiments, the main controller 211 causes the display unit 240A to display the disease information together with at least one of the searched front image (or the front image including the searched region), the spectral distribution image, and the identified depth information. The main controller 211 may also cause the display unit 240A to display the spectral distribution image superimposed on the searched front image. In some embodiments, the main controller 211 causes the display unit 240A to identifiably display a region corresponding to a characteristic site in the front image corresponding to the characteristic region identified by the characteristic region identifying unit 2311C.

[0152] <User Interface 240> The user interface 240 includes a display unit 240A and an operation unit 240B. The display unit 240A includes the display device 3. The operation unit 240B includes various operation devices and input devices.

[0153] The user interface 240 may include a device that combines a display function and an operation function, such as a touch panel. In other embodiments, at least a portion of the user interface may not be included in the ophthalmic device. For example, the display device may be an external device connected to the ophthalmic device.

[0154] <Communications Department 250> The communication unit 250 has a function for communicating with an external device (not shown). The communication unit 250 has a communication interface according to the connection form with the external device. Examples of external devices include a server device, an OCT device, a scanning optical ophthalmoscope, a slit lamp ophthalmoscope, an ophthalmic measurement device, and an ophthalmic treatment device. Examples of ophthalmic measurement devices include an eye refraction examination device, a tonometer, a specular microscope, a wavefront analyzer, a perimeter, and a microperimeter. Examples of ophthalmic treatment devices include a laser treatment device, a surgical device, and a surgical microscope. The external device may also be a device (reader) that reads information from a recording medium or a device (writer) that writes information to a recording medium. Furthermore, the external device may also be a hospital information system (HIS) server, a DICOM (Digital Imaging and Communication in Medicine) server, a doctor's terminal, a mobile terminal, a personal terminal, a cloud server, etc.

[0155] The arithmetic and control unit 200 (control unit 210, image forming unit 220, and data processing unit 230) is an example of an "ophthalmologic information processing device" according to an embodiment. The spectral images (spectral fundus image, spectral anterior segment image) are an example of "spectral distribution data" according to an embodiment. The OCT data is an example of "measurement data" according to an embodiment. The disease estimation unit 2314C is an example of an "estimation unit" according to an embodiment. The control unit 210 (main control unit 211) is an example of a "display control unit" according to an embodiment. The imaging optical system 30 is an example of a "light receiving optical system" according to an embodiment. The optical system from the OCT unit 100 to the objective lens 22 is an example of an "OCT optical system" according to an embodiment.

[0156] <Operation> An example of the operation of the ophthalmologic apparatus 1 will be described.

[0157] The ophthalmologic apparatus 1 illuminates the fundus Ef with illumination light and receives return light from the fundus Ef having different wavelength ranges within a predetermined analysis wavelength range, thereby obtaining a plurality of spectral fundus images.

[0158] An example of a plurality of spectral fundus images according to the embodiment is shown in Fig. 6. Fig. 6 shows an example of the spectral fundus images displayed on the display unit 240A.

[0159] For example, the main controller 211 causes the display unit 240A to display a plurality of spectral fundus images acquired by the image sensor 38 sequentially receiving the returned light in a horizontal array. At this time, the main controller 211 can cause the display unit 240A to display each of the plurality of spectral fundus images in association with a wavelength range. This allows the spectral distribution of the fundus corresponding to the wavelength range to be easily grasped.

[0160] FIG. 7 is a diagram illustrating an example of the operation of the ophthalmologic apparatus 1 according to the embodiment.

[0161] The spectral distribution data processing unit 231C calculates the correlation between one of the spectral fundus images IMG1 and each of the en-face images at different depth positions, and identifies the en-face image with the highest correlation. The spectral distribution data processing unit 231C specifies the depth information of the identified en-face image as the depth information of the spectral fundus image IMG1. The spectral fundus image IMG1 may be a spectral fundus image to be analyzed in which a characteristic region or a site of interest is depicted.

[0162] This allows the depth position or layer region of the spectral fundus image IMG1 to be identified with high accuracy, and makes it possible to analyze the spectral distribution of the spectral fundus image IMG1 while understanding the tissues, parts, etc. depicted in the spectral fundus image IMG1. Therefore, the accuracy of disease estimation can be improved by using at least one of the spectral distribution and the depth position (layer region).

[0163] FIG. 8 is an explanatory diagram of another operation example of the ophthalmologic apparatus 1 according to the embodiment.

[0164] The spectral distribution data processing unit 231C analyzes one of the spectral fundus images IMG2 to identify a characteristic region CS, calculates the correlation between a characteristic region image IMG3 including the identified characteristic region CS and each of the en-face images at different depth positions, and identifies the en-face image with the highest correlation. The spectral distribution data processing unit 231C specifies the depth information of the identified en-face image as the depth information of the characteristic region image IMG3. The spectral fundus image IMG2 may be the spectral fundus image in which the characteristic region is most clearly depicted among the multiple spectral fundus images.

[0165] This allows the depth position or layer region of the characteristic region CS in the spectral fundus image IMG2 to be identified with high accuracy, and makes it possible to analyze the spectral distribution of the spectral fundus image IMG2 while grasping the tissue, part, etc. in the characteristic region CS. Therefore, the accuracy of disease estimation can be improved by using at least one of the spectral distribution and the depth position (layer region).

[0166] As another example of the operation of the ophthalmologic apparatus 1 according to the embodiment, the spectral fundus image identified by the spectral distribution data processing unit 231C may be superimposed on an en-face image and displayed on the display unit 240A. Specifically, the spectral distribution data processing unit 231C calculates the correlation between the spectral fundus image and each of multiple en-face images at different depth positions and identifies the en-face image with the highest correlation. The main controller 211 superimposes the above-mentioned spectral fundus image on the identified en-face image and displays it on the display unit 240A. In this case, the spectral fundus image may be a desired spectral fundus image from the multiple spectral fundus images, or a spectral fundus image from the multiple spectral fundus images in which a characteristic region is most clearly depicted.

[0167] This makes it possible to understand the correlation between the area detected using light in a predetermined wavelength range and the area depicted in the en-face image.

[0168] As another example of the operation of the ophthalmologic apparatus 1 according to the embodiment, the display unit 240A may display an en-face image corresponding to the spectral fundus image identified by the spectral distribution data processing unit 231C in a display format corresponding to the spectral fundus image. For example, the en-face image is displayed on the display unit 240A by assigning color information corresponding to the luminance value of the spectral fundus image to each pixel, each predetermined region, or each part. Specifically, the spectral distribution data processing unit 231C calculates the correlation between the spectral fundus image and each of multiple en-face images at different depth positions and identifies the en-face image with the highest correlation. The main control unit 211 assigns color information corresponding to the spectral fundus image to the identified en-face image and displays it on the display unit 240A.

[0169] 9 to 11 show an example of the operation of the ophthalmic apparatus 1 according to the embodiment. FIG. 9 is a flow diagram of an example of the operation of the ophthalmic apparatus 1 when acquiring a plurality of spectral fundus images. FIG. 10 is a flow diagram of an example of the operation of the ophthalmic apparatus 1 when estimating a disease using spectral fundus images. FIG. 11 is a flow diagram of an example of the operation of the ophthalmic apparatus 1 when superimposing a spectral fundus image on an OCT image and displaying it.

[0170] The storage unit 212 stores a computer program for realizing the processes shown in Figures 9 to 11. The main control unit 211 operates in accordance with this computer program to execute the processes shown in Figures 9 to 11.

[0171] First, an operation example shown in FIG. 9 will be described.

[0172] (S1: Alignment) First, the main control unit 211 performs alignment.

[0173] For example, the main controller 211 controls the anterior eye cameras 5A and 5B to capture images of the anterior eye Ea of the subject's eye E substantially simultaneously. The characteristic site identification unit 231A, under the control of the main controller 211, analyzes the pair of anterior eye images captured substantially simultaneously by the anterior eye cameras 5A and 5B and identifies the position of the pupil center of the subject's eye E as the characteristic site. The three-dimensional position calculation unit 231B obtains the three-dimensional position of the subject's eye E. This processing includes, for example, calculation processing using trigonometry based on the positional relationship between the pair of anterior eye cameras 5A and 5B and the subject's eye E, as described in Japanese Patent Application Laid-Open No. 2013-248376.

[0174] The main control unit 211 controls the movement mechanism 150 based on the three-dimensional position of the subject's eye E obtained by the three-dimensional position calculation unit 231B so that the optical system (e.g., the fundus camera unit 2) and the subject's eye E have a predetermined positional relationship. Here, the predetermined positional relationship is a positional relationship that allows imaging and examination of the subject's eye E to be performed using the optical system. As a typical example, when the three-dimensional position (x coordinate, y coordinate, z coordinate) of the subject's eye E is obtained by the three-dimensional position calculation unit 231B, a position where the x coordinate and y coordinate of the optical axis of the objective lens 22 coincide with the x coordinate and y coordinate of the subject's eye E, respectively, and where the difference between the z coordinate of the objective lens 22 (front lens surface) and the z coordinate of the subject's eye E (corneal surface) is equal to a predetermined distance (working distance) is set as the movement destination of the optical system.

[0175] (S2: Autofocus) Next, the main control unit 211 starts autofocus.

[0176] For example, the main controller 211 controls the focus optical system 60 to project a split index onto the subject's eye E. Under the control of the main controller 211, the analysis unit 231 analyzes the observation image of the fundus Ef onto which the split index is projected, thereby extracting a pair of split index images and calculating the relative deviation between the pair of split indexes. The main controller 211 controls the focus driver 31A and the focus driver 43A based on the calculated deviation (deviation direction, deviation amount).

[0177] (S3: Set wavelength range) Next, the main control unit 211 controls the tunable filter 80 to set the wavelength selection range of the transmitted light to a predetermined wavelength range. An example of the predetermined wavelength range is an initial wavelength range when wavelength range selection is repeated sequentially to cover the analysis wavelength range.

[0178] (S4: Acquire image data) Next, the main controller 211 causes image data of the spectral fundus image to be acquired.

[0179] For example, the main control unit 211 controls the illumination optical system 10 to illuminate the subject's eye E with illumination light, captures the reception results of the reflected light of the illumination light obtained by the image sensor 38, and acquires image data of the spectral fundus image.

[0180] (S5:Next?) Next, the main controller 211 determines whether to acquire a spectral fundus image in the next wavelength range. For example, when the wavelength selection is changed sequentially in predetermined wavelength range steps within the analysis wavelength range, the main controller 211 can determine whether to acquire the next spectral fundus image based on the number of times the wavelength range is changed. For example, the main controller 211 can determine whether to acquire the next spectral fundus image by determining whether all of a plurality of predetermined wavelength ranges have been selected.

[0181] In step S5, when it is determined that the next spectral fundus image is to be acquired (step S5: Y), the operation of the ophthalmologic apparatus 1 proceeds to step S6. In step S5, when it is determined that the next spectral fundus image is not to be acquired (step S5: N), the operation of the ophthalmologic apparatus 1 ends (END).

[0182] (S6: Change wavelength range) When it is determined in step S5 that the next spectral fundus image is to be acquired (step S5: Y), the main controller 211 controls the tunable filter 80 to change the selection range of transmitted light to be selected next. Subsequently, the operation of the ophthalmologic apparatus 1 proceeds to step S4.

[0183] As described above, the ophthalmologic apparatus 1 according to the embodiment can acquire a plurality of spectral fundus images corresponding to a plurality of wavelength ranges within a predetermined analysis wavelength range.

[0184] Next, an operation example shown in Fig. 10 will be described. Fig. 10 shows an operation example in which a disease is estimated using a plurality of spectral fundus images acquired according to the operation example shown in Fig. 9 or any one of the plurality of acquired spectral fundus images.

[0185] (S11: Identify characteristic areas) First, the main controller 211 controls the characteristic region identifying unit 2311C to identify a characteristic region in the spectral fundus image. The characteristic region identifying unit 2311C executes the characteristic region identifying process on the spectral fundus image as described above.

[0186] In some embodiments, the characteristic region identifying unit 2311C identifies a characteristic region in a pre-selected spectral fundus image from among the plurality of spectral fundus images, and selects one characteristic region from the plurality of characteristic regions identified in each of the plurality of spectral fundus images.

[0187] (S12: Acquire OCT image) Next, the main controller 211 acquires an OCT image. In this embodiment, it is assumed that OCT data of the subject's eye E has been acquired in advance by performing OCT on the subject's eye E. It is also assumed that a three-dimensional OCT image or a plurality of en-face images at different depth positions has been formed based on the OCT data. In this case, the main controller 211 acquires the three-dimensional OCT image or the plurality of en-face images.

[0188] In some embodiments, in step S12, the main controller 211 controls the OCT unit 100 and the like to perform OCT on the subject's eye E and acquire OCT data. Based on the acquired OCT data, the data processor 230 forms a three-dimensional OCT image or a plurality of en-face images at different depth positions.

[0189] (S13: Search) Next, the main control unit 211 controls the depth information identification unit 2312C (search unit 2313C) to search the OCT image acquired in step S12 for the image area that has the highest correlation with the image including the feature area identified in step S11, or an en-face image including that image area.

[0190] (S14: Identify the area on the fundus) Next, the main controller 211 controls the depth information identifying unit 2312C to identify a site on the fundus (such as a layer region or depth position) corresponding to the characteristic region identified in step S11. The depth information identifying unit 2312C identifies depth information from the image region that has the highest correlation with the image including the characteristic region searched for in step S13, or from the en-face image including the image region, and identifies the site on the fundus from the identified depth information.

[0191] (S15: Estimate the disease) Next, the main controller 211 controls the disease estimation part 2314C to determine the presence or absence of a disease, the probability of a disease, or the type of disease in the part on the fundus determined in step S14.

[0192] For example, the disease estimation unit 2314C performs the disease estimation process as described above. In some embodiments, the disease estimation unit 2314C determines the presence or absence of a disease, the probability of a disease, or the type of disease based on the spectral distribution (spectral characteristics) of the spectral fundus image in which the characteristic region is identified in step S11, the en-face image (OCT image) searched in step S13, and the site on the fundus identified in step S14.

[0193] (S16:Display) Next, the main control unit 211 causes the display unit 240A to display at least one of the spectral fundus image in which the characteristic region was identified in step S11, the characteristic region identified in step S11, the en-face image (OCT image) identified in step S13, the depth information corresponding to the characteristic region, the area on the fundus identified in step S14, and the presence or absence of disease, the probability of disease, or the type of disease estimated in step S15.

[0194] In some embodiments, in step S16, the main controller 211 causes the display unit 240A to display the spectral fundus image, whose characteristic region was identified in step S11, superimposed on the en-face image identified in step S13. In addition, in step S16, the main controller 211 may cause the display unit 240A to display a synthetic fundus image generated by assigning color components and changeable transparency information to each of the multiple spectral fundus images and superimposing them.

[0195] This is the end of the flow shown in FIG. 10 (end).

[0196] As described above, the ophthalmologic apparatus 1 according to the embodiment can identify a site corresponding to a characteristic region in a spectral fundus image of the subject's eye E based on the OCT data of the subject's eye E, and estimate a disease.

[0197] Next, an operation example shown in Fig. 11 will be described. Fig. 11 shows an operation example in which a plurality of spectral fundus images acquired according to the operation example shown in Fig. 9 or any one of a plurality of acquired spectral fundus images is used to superimpose on an OCT image and displayed.

[0198] (S21: Identify characteristic areas) First, similarly to step S11, the main controller 211 controls the characteristic region identifying part 2311C to identify a characteristic region in the spectral fundus image.

[0199] (S22: Acquire OCT image) Next, the main controller 211 acquires an OCT image, similar to step S12. In this embodiment, it is assumed that OCT data of the subject's eye E has been acquired in advance by performing OCT on the subject's eye E. It is also assumed that a three-dimensional OCT image or a plurality of en-face images at different depth positions has been formed based on the OCT data. In this case, the main controller 211 acquires the three-dimensional OCT image or the plurality of en-face images.

[0200] (S23: Search) Next, the main control unit 211 controls the depth information identification unit 2312C (search unit 2313C) to search the OCT image acquired in step S22 for an en-face image (or an image area in a three-dimensional OCT image) that has the highest correlation with the spectral fundus image whose characteristic area was identified in step S21.

[0201] (S24: Overlay display) Subsequently, the main controller 211 causes the display unit 240A to superimpose the spectral fundus image whose characteristic region has been identified in step S21 on the en-face image found in step S23. In some embodiments, the main controller 211 causes the display unit 240A to display the characteristic region identified in step S21 in a identifiable manner in step S24.

[0202] This is the end of the flow shown in FIG. 11 (END).

[0203] As described above, the ophthalmologic apparatus 1 according to the embodiment can display the spectral fundus image of the subject's eye E superimposed on the OCT data of the subject's eye E.

[0204] <Effect> An ophthalmological information processing apparatus, an ophthalmological apparatus, an ophthalmological information processing method, and a program according to an embodiment will be described.

[0205] An ophthalmologic information processing device (control unit 210, image forming unit 220, and data processing unit 230) according to some embodiments includes a characteristic region identifying unit (2311C) and a depth information identifying unit (2312C). The characteristic region identifying unit identifies a characteristic region in spectral distribution data acquired by receiving return light within a predetermined wavelength range from an eye (E) illuminated with illumination light. The depth information identifying unit identifies depth information of the characteristic region based on measurement data of the eye (E) that has a higher resolution in the depth direction than the spectral distribution data.

[0206] This configuration makes it possible to accurately identify which tissue in the depth direction of the measurement site a characteristic region in the spectral distribution data belongs to. It also makes it possible to correct positional deviations in the spectral distribution data caused by eye movement. This allows for more detailed analysis of the spectral distribution data.

[0207] In some embodiments, the characteristic region identification unit identifies a characteristic region in one of a plurality of spectral distribution data obtained by illuminating the test eye with illumination light and receiving return light from the test eye having different wavelength ranges.

[0208] With this configuration, different parts of the subject's eye appear in the spectral distribution data depending on the wavelength range, so it is possible to identify a feature region with a distinctive spectral distribution and to identify with high accuracy which tissue in the depth direction in the measurement region the identified feature region belongs to.

[0209] In some embodiments, the measurement data is OCT data obtained by performing optical coherence tomography on the subject's eye.

[0210] According to this configuration, it is possible to use a configuration capable of performing OCT on the subject's eye to identify with high accuracy which tissue in the depth direction in the measurement region a feature region in the spectral distribution data belongs to.

[0211] In some embodiments, the depth information determination unit includes a search unit (2313C) that searches for the front image that has the highest correlation with the spectral distribution data from among multiple front images that are formed based on OCT data and have different depth positions, and determines depth information based on the front image searched for by the search unit.

[0212] According to this configuration, a front image having the highest correlation with the spectral distribution data is identified by a search process on a plurality of front images formed based on OCT data, so that highly accurate depth information of the spectral distribution data can be easily identified.

[0213] In some embodiments, the depth information determination unit includes a search unit (2313C) that searches for a front image containing an image area that has the highest correlation with an image containing a characteristic area from among multiple front images that are formed based on OCT data and have different depth positions, and determines depth information based on the front image searched by the search unit.

[0214] According to this configuration, a front image including an image area that has the highest correlation with an image including a characteristic area in the spectral distribution data is identified by performing a search process on a plurality of front images formed based on OCT data, so that highly accurate depth information of the characteristic area can be easily identified.

[0215] Some embodiments include an estimation unit (disease estimation unit 2314C) that estimates the presence or absence of a disease, the probability of a disease, or the type of disease based on the front image searched by the search unit.

[0216] With this configuration, it becomes possible to estimate a disease with high accuracy from the spectral distribution data.

[0217] Some embodiments include a display control unit (control unit 210, main control unit 211) that causes a display means (display unit 240A) to display disease information including the presence or absence of a disease, the probability of a disease, or the type of disease estimated by the estimation unit.

[0218] According to this configuration, disease information estimated from the spectral distribution data can be displayed and notified to the outside.

[0219] Some embodiments include a display control unit (control unit 210, main control unit 211) that causes the display means (display unit 240A) to display the front image searched by the search unit and the depth information.

[0220] According to this configuration, the front image and the depth information corresponding to the spectral distribution data can be displayed, and the front image and the depth information can be notified to the outside.

[0221] Some embodiments include a display control unit (control unit 210, main control unit 211) that superimposes the spectral distribution data on the front image searched for by the search unit and displays it on the display means (display unit 240A).

[0222] According to this configuration, the spectral distribution data can be displayed superimposed on the front image, and the distribution data can be associated with the front image.

[0223] In some embodiments, the display control unit causes the display means to identifiably display an area corresponding to the characteristic portion in the front image that corresponds to the characteristic area.

[0224] According to this configuration, it becomes easy to grasp the area corresponding to the characteristic portion in the front image that corresponds to the characteristic area.

[0225] Some embodiments include a display control unit (control unit 210, main control unit 211) that causes the display means (display unit 240A) to display the spectral distribution data and the depth information.

[0226] According to this configuration, the spectral distribution data and the depth information can be displayed, and the spectral distribution data and the depth information can be notified to the outside.

[0227] In some embodiments, the depth information includes at least one of information representing a depth position, a depth range, and a layer region relative to a reference site of the subject's eye.

[0228] According to this configuration, it is possible to specify at least one of information indicating a depth position, a depth range, and a layer region relative to a reference portion of the eye to be examined.

[0229] An ophthalmic device (1) according to some embodiments includes an illumination optical system (10) that illuminates an eye to be examined with illumination light, a light-receiving optical system (photographing optical system 30) that receives return light of the illumination light from the eye to be examined, the return light having different wavelength ranges from the illumination light, an OCT optical system (optical system from the OCT unit to the objective lens) that performs optical coherence tomography on the eye to be examined, and an ophthalmic information processing device described in any one of the above.

[0230] According to this configuration, it is possible to provide an ophthalmologic apparatus that can identify with high accuracy which tissue in the depth direction of the measurement site a characteristic region in the spectral distribution data belongs to.

[0231] An ophthalmologic information processing method according to some embodiments includes a feature region identifying step and a depth information identifying step. The feature region identifying step identifies a feature region in spectral distribution data acquired by receiving return light within a predetermined wavelength range from an eye (E) illuminated with illumination light. The depth information identifying step identifies depth information of the feature region based on measurement data of the eye (E) having a higher resolution in the depth direction than the spectral distribution data.

[0232] This method makes it possible to identify with high accuracy which tissue in the depth direction of the measurement site a characteristic region in the spectral distribution data belongs to. It also makes it possible to correct positional deviations in the spectral distribution data caused by eye movement. This allows for more detailed analysis of the spectral distribution data.

[0233] In some embodiments, the characteristic region identifying step identifies a characteristic region in any of a plurality of spectral distribution data obtained by illuminating the test eye with illumination light and receiving return light from the test eye having different wavelength ranges.

[0234] According to this method, the part of the subject's eye that appears in the spectral distribution data differs depending on the wavelength range, so it is possible to identify a feature region with a distinctive spectral distribution and to identify with high accuracy which tissue in the depth direction in the measurement part the identified feature region belongs to.

[0235] In some embodiments, the measurement data is OCT data obtained by performing optical coherence tomography on the subject's eye.

[0236] According to this method, it is possible to identify with high accuracy which tissue in the depth direction in the measurement region a characteristic region in the spectral distribution data belongs to, using a configuration capable of performing OCT on the subject's eye.

[0237] In some embodiments, the depth information identification step includes a search step of searching for a front image that has the highest correlation with the spectral distribution data from among a plurality of front images formed based on OCT data and having different depth positions, and the depth information is identified based on the front image searched in the search step.

[0238] According to this method, a front image having the highest correlation with the spectral distribution data is identified by a search process on a plurality of front images formed based on OCT data, so that highly accurate depth information of the spectral distribution data can be easily identified.

[0239] In some embodiments, the depth information identification step includes a search step of searching for a front image including an image area that is most highly correlated with an image including a characteristic area from among a plurality of front images formed based on OCT data and having different depth positions, and the depth information is identified based on the front image searched in the search step.

[0240] According to this method, a front image including an image area that has the highest correlation with an image including a characteristic area in the spectral distribution data is identified by performing a search process on a plurality of front images formed based on OCT data, so that highly accurate depth information of the characteristic area can be easily identified.

[0241] Some embodiments include an estimation step of estimating the presence or absence of a disease, the probability of a disease, or the type of disease based on the frontal image searched in the search step.

[0242] According to this method, it becomes possible to estimate diseases with high accuracy from spectral distribution data.

[0243] Some embodiments include a display control step of causing a display means (display unit 240A) to display disease information including the presence or absence of a disease, the probability of a disease, or the type of disease estimated in the estimation step.

[0244] According to this method, disease information estimated from the spectral distribution data can be displayed and notified to the outside.

[0245] Some embodiments include a display control step of causing a display means (display unit 240A) to display the front image and depth information searched in the search step.

[0246] According to this method, the front image and the depth information corresponding to the spectral distribution data can be displayed, and the front image and the depth information can be notified to the outside.

[0247] Some embodiments include a display control step of superimposing the spectral distribution data on the front image found in the search step and displaying the data on a display means (display unit 240A).

[0248] According to this method, the spectral distribution data can be displayed superimposed on the front image, and the distribution data can be associated with the front image.

[0249] In some embodiments, the display control step causes the display means to identifiably display an area corresponding to the characteristic portion in the front image that corresponds to the characteristic area.

[0250] According to this method, it becomes possible to easily grasp the area corresponding to the characteristic portion in the front image that corresponds to the characteristic area.

[0251] Some embodiments include a display control step of displaying the spectral distribution data and the depth information on a display means (display unit 240A).

[0252] According to this method, the spectral distribution data and the depth information can be displayed and reported to the outside.

[0253] In some embodiments, the depth information includes at least one of information representing a depth position, a depth range, and a layer region relative to a reference site of the subject's eye.

[0254] According to this method, it is possible to identify at least one of information representing a depth position, a depth range, and a layer region relative to a reference portion of the eye to be examined.

[0255] A program according to some embodiments causes a computer to execute each step of any of the ophthalmologic information processing methods described above.

[0256] This program makes it possible to identify with high accuracy which tissue in the depth direction of the measurement site a characteristic region in the spectral distribution data belongs to. It is also possible to correct positional deviations in the spectral distribution data caused by eye movement. This makes it possible to provide a computer program that enables more detailed analysis of the spectral distribution data.

[0257] The embodiment described above is merely an example of the present invention. Those who wish to implement the present invention may freely make modifications (omissions, substitutions, additions, etc.) within the scope of the gist of the present invention.

[0258] In some embodiments, a program for causing a computer to execute the ophthalmologic information processing method is stored in the storage unit 212. Such a program may be stored in any computer-readable recording medium. The recording medium may be an electronic medium that utilizes magnetism, light, magneto-optical technology, semiconductors, or the like. Typically, the recording medium is a magnetic tape, a magnetic disk, an optical disk, a magneto-optical disk, a flash memory, a solid-state drive, or the like. [Explanation of symbols]

[0259] 1 Ophthalmology equipment 2 Fundus camera unit 10 Illumination optical system 22 Objective Lens 30. Shooting optical system 80 Tunable wavelength filter 100 OCT units 210 Control Unit 211 Main control unit 220 Image forming unit 230 Data Processing Unit 231 Analysis Department 231A Characteristic part identification part 231B 3D position calculation unit 231C Spectral distribution data processing unit 2311C Feature region identification unit 2312C Depth information identification unit 2313C Search Department 2314C Disease Estimation Department E. Examined eye Ef fundus LS measurement light

Claims

1. a characteristic region identifying unit that identifies a characteristic region in spectral distribution data acquired by receiving return light in a predetermined wavelength range from the subject's eye illuminated with illumination light; a depth information specifying unit that specifies depth information of the feature region based on measurement data of the eye to be examined, the measurement data having a resolution in the depth direction higher than that of the spectral distribution data; An ophthalmology information processing device comprising:

2. The characteristic region identifying unit identifies the characteristic region in any of a plurality of spectral distribution data acquired by illuminating the eye to be inspected with illumination light and receiving return light from the eye to be inspected, the return light having different wavelength ranges from each other.

2. The ophthalmological information processing apparatus according to claim 1.

3. The measurement data is OCT data obtained by performing optical coherence tomography on the subject's eye.

3. The ophthalmologic information processing apparatus according to claim 1 or 2.

4. The depth information specifying unit a search unit that searches for a front image having a highest correlation with the spectral distribution data from among a plurality of front images formed based on the OCT data and having different depth positions; The depth information is identified based on the front image searched by the search unit.

4. The ophthalmological information processing apparatus according to claim 3.

5. The depth information specifying unit a search unit that searches for a front image including an image region that has the highest correlation with the image including the characteristic region from a plurality of front images that are formed based on the OCT data and have different depth positions from each other, The depth information is identified based on the front image searched by the search unit.

4. The ophthalmological information processing apparatus according to claim 3.

6. and an estimation unit that estimates the presence or absence of a disease, the probability of a disease, or the type of a disease based on the front image searched by the search unit.

6. The ophthalmologic information processing apparatus according to claim 4 or 5.

7. a display control unit that displays, on a display means, disease information including the presence or absence of the disease, the probability of the disease, or the type of the disease estimated by the estimation unit.

7. The ophthalmologic information processing apparatus according to claim 6,

8. a display control unit that causes a display unit to display the front image searched by the search unit and the depth information.

6. The ophthalmologic information processing apparatus according to claim 4 or 5.

9. a display control unit that displays the spectral distribution data on a display means by superimposing the data on the front image found by the search unit; 6. The ophthalmologic information processing apparatus according to claim 4 or 5.

10. The display control unit causes the display means to identifiably display an area corresponding to the characteristic portion in the front image that corresponds to the characteristic area.

10. The ophthalmological information processing apparatus according to claim 8 or 9.

11. a display control unit that displays the spectral distribution data and the depth information on a display unit; 8. The ophthalmologic information processing apparatus according to claim 1, wherein the ophthalmologic information processing apparatus is a computer.

12. The depth information includes at least one of information representing a depth position, a depth range, and a layer region relative to a reference portion of the subject's eye. The ophthalmological information processing apparatus according to any one of claims 1 to 11.

13. an illumination optical system that illuminates the eye to be examined with illumination light; a light receiving optical system that receives return light of the illumination light from the subject's eye, the return light having wavelength ranges different from each other; an OCT optical system that performs optical coherence tomography on the subject's eye; An ophthalmological information processing device according to any one of claims 1 to 12; 1. An ophthalmic device comprising:

14. a characteristic region identifying step of identifying a characteristic region in spectral distribution data acquired by receiving return light in a predetermined wavelength range from the subject's eye illuminated with illumination light; a depth information specifying step of specifying depth information of the feature region based on measurement data of the eye to be examined, the measurement data having a resolution in the depth direction higher than that of the spectral distribution data; An ophthalmological information processing method, comprising:

15. The characteristic region identifying step identifies the characteristic region in any of a plurality of spectral distribution data acquired by illuminating the subject's eye with illumination light and receiving return light from the subject's eye having different wavelength ranges.

15. The ophthalmologic information processing method according to claim 14.

16. The measurement data is OCT data obtained by performing optical coherence tomography on the subject's eye.

16. The ophthalmologic information processing method according to claim 14 or 15.

17. The depth information specifying step includes: a searching step of searching for a front image having a highest correlation with the spectral distribution data from among a plurality of front images formed based on the OCT data and having different depth positions; The depth information is identified based on the front image searched in the searching step.

17. The ophthalmologic information processing method according to claim 16.

18. The depth information specifying step includes: a searching step of searching for a front image including an image region having a highest correlation with an image including the characteristic region from among a plurality of front images formed based on the OCT data and having different depth positions from each other, The depth information is identified based on the front image searched in the searching step.

17. The ophthalmologic information processing method according to claim 16.

19. The spectral distribution data processing means for processing the spectral distribution data includes an estimation step of estimating the presence or absence of a disease, the probability of a disease, or the type of a disease based on the front image searched in the search step.

19. The ophthalmologic information processing method according to claim 17 or 18.

20. The disease information display control means includes a display control step of displaying disease information including the presence or absence of the disease, the probability of the disease, or the type of the disease estimated in the estimation step on a display means.

20. The ophthalmologic information processing method according to claim 19.

21. a display control step of displaying the front image and the depth information searched for in the search step on a display means.

19. The ophthalmologic information processing method according to claim 17 or 18.

22. a display control step of superimposing the spectral distribution data on the front image searched for in the search step and displaying the superimposed data on a display means.

19. The ophthalmologic information processing method according to claim 17 or 18.

23. The display control step causes the display means to identifiably display an area corresponding to the characteristic portion in the front image that corresponds to the characteristic area.

23. The ophthalmologic information processing method according to claim 21 or 22.

24. A depth information display control step includes a display control step of displaying the spectral distribution data and the depth information on a display means. The ophthalmologic information processing method according to any one of claims 14 to 19.

25. The depth information includes at least one of information representing a depth position, a depth range, and a layer region relative to a reference portion of the subject's eye. The ophthalmologic information processing method according to any one of claims 14 to 24.

26. A program causing a computer to execute each step of the ophthalmologic information processing method according to any one of claims 14 to 25.

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