Image processing method, program, and image processing apparatus

Abstract

Visualize the diameter of choroidal blood vessels. [Solution] The location of vortex veins is detected from a choroidal vessel image in which the choroidal vessels are visualized. By image processing the choroidal vessel image, a first-thickness choroidal vessel and a second-thickness choroidal vessel, which is different from the first thickness, are extracted from the choroidal vessel image. A rectangular frame indicating the location of the vortex veins is superimposed on the choroidal vessel image, and a thickness-analyzed fundus image is generated in which the first-thickness choroidal vessel is displayed in red and the second-thickness choroidal vessel is displayed in blue.

Description

Technical Field

[0001] The technology of the present disclosure relates to an image processing method, a program, and an image processing apparatus.

Background Art

[0002] Japanese Patent Application Laid-Open No. 2015-131 discloses a technique for quantifying the choroidal vascular network from measurement data of OCT (Optical Coherence Tomography; hereinafter referred to as OCT).

Summary of the Invention

[0003] The image processing method according to the first aspect of the technology of the present disclosure includes: detecting a position of a vortex vein from a fundus image in which choroidal blood vessels are visualized; extracting a first-thickness choroidal blood vessel having a first thickness and a second-thickness choroidal blood vessel having a second thickness different from the first thickness by performing image processing on the fundus image; superimposing and displaying a position display image indicating the position of the vortex vein on the fundus image, and generating a thickness analysis fundus image in which the first-thickness choroidal blood vessels are displayed by a first display method and the second-thickness choroidal blood vessels are displayed by a second display method different from the first display method.

[0004] The image processing method according to the second aspect of the technology of the present disclosure includes: detecting a position of a vortex vein from a fundus image in which choroidal blood vessels are visualized; detecting intersections between a circle centered on the position of the vortex vein and the choroidal blood vessels; specifying the thickness of the choroidal blood vessels at the intersections; and creating a graph showing the relationship between the thickness of the choroidal blood vessels at the intersections.

[0005] The image processing method according to the third aspect of the technology of the present disclosure includes: detecting a position of a vortex vein from a fundus image in which choroidal blood vessels are visualized; detecting intersections between a circle centered on the position of the vortex vein and the choroidal blood vessels; specifying the vessel diameter of the choroidal blood vessels at the intersections; and creating a histogram of the vessel diameter and the number of choroidal blood vessels.

[0006] A program of a fourth aspect of the technology of this disclosure causes a computer to execute any of the image processing methods of the first to third aspects.

[0007] An image processing apparatus according to a fifth aspect of the technology of this disclosure comprises a storage device for storing a program for causing the processing apparatus to execute an image processing method, and a processing apparatus that executes the image processing method by executing the program stored in the storage device, wherein the image processing method is any of the first to third aspects.

[0008] A sixth aspect of the technology of this disclosure is an image processing method that includes the steps of: detecting the location of vortex veins from a fundus image in which choroidal blood vessels are visualized; analyzing the thickness of the choroidal blood vessels in the fundus image; and creating a display screen that shows the relationship between the location of the vortex veins and the thickness of the choroidal blood vessels. [Brief explanation of the drawing]

[0009] [Figure 1] This is a block diagram of the ophthalmology system 100. [Figure 2] This is a schematic diagram showing the overall configuration of the ophthalmic device 110. [Figure 3] This is a block diagram of the electrical system configuration of management server 140. [Figure 4] This is a block diagram of the functions of CPU 162 on management server 140. [Figure 5] This is a flowchart of the image processing program according to the first embodiment. [Figure 6] This is a diagram showing choroidal vascular images. [Figure 7] This figure shows a binarized image of choroidal blood vessels. [Figure 8] Figure 5 is a flowchart of the choroidal vessel diameter analysis processing program in step 204. [Figure 9A] This is an explanatory diagram illustrating the process of analyzing the diameter of choroidal blood vessels. [Figure 9B]This is an explanatory diagram illustrating the process of analyzing the diameter of choroidal blood vessels. [Figure 9C] This is an explanatory diagram illustrating the process of analyzing the diameter of choroidal blood vessels. [Figure 9D] This is an explanatory diagram illustrating the process of analyzing the diameter of choroidal blood vessels. [Figure 9E] This is an explanatory diagram illustrating the process of analyzing the diameter of choroidal blood vessels. [Figure 9F] This is an explanatory diagram illustrating the process of analyzing the diameter of choroidal blood vessels. [Figure 9G] This is an explanatory diagram illustrating the process of analyzing the diameter of choroidal blood vessels. [Figure 9H] This is an explanatory diagram illustrating the process of analyzing the diameter of choroidal blood vessels. [Figure 9I] This is an explanatory diagram illustrating the process of analyzing the diameter of choroidal blood vessels. [Figure 9J] This is an explanatory diagram illustrating the process of analyzing the diameter of choroidal blood vessels. [Figure 10] This figure shows the display screen 300 of the choroidal vascular analysis mode. [Figure 11] This figure shows a display screen 300 that includes a display screen for showing the diameter of blood vessels. [Figure 12] This figure shows a display screen 300 in which the VV position is superimposed on the display screen that shows the blood vessel diameter. [Figure 13] This figure shows the display screen 300 that appears when the thickness 1 icon 362 is clicked. [Figure 14] This figure shows the display screen 300 that appears when the thickness 2 icon 364 is clicked. [Figure 15] This figure shows the display screen 300 that appears when the thickness 3 icon 366 is clicked. [Figure 16] This is a flowchart of the image processing program according to the fourth embodiment. [Figure 17] This figure shows a binarized image generated from choroidal vascular images, with a circle 404 set with a predetermined radius centered at position VV 402. [Figure 18] This diagram shows the detection of the intersection point 406 between circle 404 and the thin line. [Figure 19] It is a diagram showing a distance image generated from a binary image of a choroidal blood vessel image. [Figure 20] It is a graph of the angle from the uppermost end of the circle and the blood vessel diameter. [Figure 21] It is a histogram of the number of choroidal blood vessels and the blood vessel diameter. [Figure 22] It is a diagram showing a display screen for displaying each data of the blood vessel diameter. [Figure 23] It is a diagram showing a display screen combining the blood vessel diameter analysis result and the VV position analysis result. [Figure 24] It is a flowchart of an image processing program.

Mode for Carrying Out the Invention

[0010] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. In the following, for convenience of explanation, a Scanning Laser Ophthalmoscope is referred to as "SLO".

[0011] Referring to FIG. 1, the configuration of the ophthalmic system 100 will be described. As shown in FIG. 1, the ophthalmic system 100 includes an ophthalmic device 110, an axial length measuring device 120, a management server device (hereinafter referred to as "management server") 140, and an image display device (hereinafter referred to as "image viewer") 150. The ophthalmic device 110 acquires a fundus image. The axial length measuring device 120 measures the axial length of a patient's eye. The management server 140 stores a plurality of fundus images and axial lengths obtained by photographing the fundus of a plurality of patients by the ophthalmic device 110 in correspondence with the patient ID's. The image viewer 150 displays the fundus image acquired by the management server 140.

[0012] The ophthalmic device 110, the axial length measuring device 120, the management server 140, and the image viewer 150 are interconnected via a network 130.

[0013] Furthermore, other ophthalmic devices (such as OCT measurement, visual field measurement, and intraocular pressure measurement equipment) and diagnostic support devices that perform image analysis using artificial intelligence may be connected to the ophthalmic device 110, axial length measuring instrument 120, management server 140, and image viewer 150 via the network 130.

[0014] Next, the configuration of the ophthalmic device 110 will be described with reference to Figure 2. As shown in Figure 2, the ophthalmic device 110 comprises a control unit 20, a display / operation unit 30, and an SLO unit 40, and photographs the posterior segment (fundus) of the eye under examination 12. Furthermore, it may also include an OCT unit (not shown) for acquiring OCT data of the fundus.

[0015] The control unit 20 includes a CPU 22, memory 24, and a communication interface (I / F) 26, etc. The display / operation unit 30 is a graphic user interface that displays captured images and accepts various instructions, including instructions to take pictures, and includes a display 32 and an input / instruction device 34.

[0016] The SLO unit 40 is equipped with a light source 42 for G light (green light: wavelength 530 nm), a light source 44 for R light (red light: wavelength 650 nm), and a light source 46 for IR light (infrared light (near-infrared light): wavelength 800 nm). The light sources 42, 44, and 46 emit their respective lights when commanded by the control unit 20. The SLO unit 40 is equipped with optical systems 50, 52, 54, and 56 that reflect or transmit the light from the light sources 42, 44, and 46 into a single optical path. Optical systems 50 and 56 are mirrors, and optical systems 52 and 54 are beam splitters. The G light is reflected by optical systems 50 and 54, the R light is transmitted by optical systems 52 and 54, and the IR light is reflected by optical systems 52 and 56, and each is guided into a single optical path.

[0017] The SLO unit 40 includes a wide-angle optical system 80 that scans light from light sources 42, 44, and 46 in a two-dimensional manner across the posterior segment (fundus) of the eye under examination 12. The SLO unit 40 includes a beam splitter 58 that reflects green light and transmits other light from the light coming from the posterior segment (fundus) of the eye under examination 12. The SLO unit 40 includes a beam splitter 60 that reflects red light and transmits other light from the light transmitted through the beam splitter 58. The SLO unit 40 includes a beam splitter 62 that reflects infrared light from the light transmitted through the beam splitter 60. The SLO unit 40 includes a green light detection element 72 that detects green light reflected by the beam splitter 58, a red light detection element 74 that detects red light reflected by the beam splitter 60, and an infrared light detection element 76 that detects infrared light reflected by the beam splitter 62.

[0018] The wide-angle optical system 80 includes an X-direction scanning device 82 composed of polygon mirrors that scan light from light sources 42, 44, and 46 in the X direction, a Y-direction scanning device 84 composed of galvanometer mirrors that scan light in the Y direction, and an optical system 86 that widens the scanned light, including a slit mirror and an elliptical mirror (not shown). The optical system 86 makes the field of view (FOV) of the fundus larger than that of conventional technology, allowing for imaging of a wider area of ​​the fundus than with conventional technology. Specifically, it is possible to image a wide area of ​​the fundus with an external light illumination angle of approximately 120 degrees from outside the eye 12 (approximately 200 degrees as the internal light illumination angle that is substantially captureable when the fundus of the eye 12 is illuminated by scanning light, with the center O of the eyeball of the eye 12 as the reference position). The optical system 86 may also be configured using multiple lens groups instead of the slit mirror and elliptical mirror. The X-direction scanning device 82 and the Y-direction scanning device 84 may each use a two-dimensional scanner configured with a MEMS mirror.

[0019] When using a system including a slit mirror and an elliptical mirror as the optical system 86, a configuration using an elliptical mirror as described in international applications PCT / JP2014 / 084619 and PCT / JP2014 / 084630 is also acceptable. The disclosures of international application PCT / JP2014 / 084619 (International Publication WO2016 / 103484), filed internationally on 26 December 2014, and international application PCT / JP2014 / 084630 (International Publication WO2016 / 103489), filed internationally on 26 December 2014, are incorporated herein by reference in their entirety.

[0020] When the ophthalmic device 110 is placed on a horizontal plane, the horizontal direction is defined as the "X direction," the direction perpendicular to the horizontal plane is defined as the "Y direction," and the direction connecting the center of the pupil of the anterior segment of the eye under examination 12 to the center of the eyeball is defined as the "Z direction." Therefore, the X, Y, and Z directions are perpendicular to each other.

[0021] A color fundus image is obtained by simultaneously capturing the fundus of the eye under examination 12 with green light and red light. More specifically, the control unit 20 controls the light sources 42 and 44 to emit light simultaneously, and the wide-angle optical system 80 scans the fundus of the eye under examination 12 with green light and red light. The green light reflected from the fundus of the eye under examination 12 is detected by the green light detection element 72, and image data of the second fundus image (green color fundus image) is generated by the CPU 22 of the ophthalmic device 110. Similarly, the red light reflected from the fundus of the eye under examination 12 is detected by the red light detection element 74, and image data of the first fundus image (red color fundus image) is generated by the CPU 22 of the ophthalmic device 110. Furthermore, if IR light is irradiated, the IR light reflected from the fundus of the eye under examination 12 is detected by the IR light detection element 76, and image data of the IR fundus image is generated by the CPU 22 of the ophthalmic device 110.

[0022] The structure of the eye consists of the vitreous humor surrounded by multiple layers with different structures. These layers, from the innermost to the outermost layer on the vitreous side, include the retina, choroid, and sclera. Red light passes through the retina and reaches the choroid. Therefore, the first fundus image (red color fundus image) contains information about the blood vessels present in the retina (retinal blood vessels) and the blood vessels present in the choroid (choroidal blood vessels). In contrast, green light only reaches the retina. Therefore, the second fundus image (green color fundus image) contains information about the blood vessels present in the retina (retinal blood vessels).

[0023] The CPU 22 of the ophthalmic device 110 mixes the first fundus image (red-color fundus image) and the second fundus image (green-color fundus image) in a predetermined ratio and displays the resulting color fundus image on the display 32. Alternatively, instead of a color fundus image, the first fundus image (red-color fundus image), the second fundus image (green-color fundus image), or an IR fundus image may be displayed.

[0024] Image data of the first fundus image (R-color fundus image), the second fundus image (G-color fundus image), and the IR fundus image are sent from the ophthalmic device 110 to the management server 140 via the communication IF26.

[0025] Since the fundus of the eye 12 being examined is captured simultaneously with G-light and R-light in this manner, each position in the first fundus image (R-color fundus image) and the corresponding position in the second fundus image (G-color fundus image) are the same position in the fundus.

[0026] The axial length measuring device 120 in Figure 1 has two modes: a first mode and a second mode, for measuring the axial length of the eye 12 in the axial direction (Z direction). In the first mode, light from a light source (not shown) is guided to the eye 12, and the device receives the interference light of the reflected light from the fundus and the reflected light from the cornea. The axial length is measured based on the interference signal indicating the received interference light. The second mode is a mode that measures the axial length using ultrasound (not shown). The axial length measuring device 120 transmits the axial length measured by the first mode or the second mode to the management server 140. The axial length may be measured using both the first mode and the second mode; in this case, the average of the axial lengths measured in both modes is transmitted to the management server 140 as the axial length.

[0027] The axial length of the eye is stored as patient information on the management server 140 as part of the patient's data, and is also used for fundus image analysis.

[0028] Next, the configuration of the management server 140 will be described with reference to Figure 3. As shown in Figure 3, the management server 140 comprises a control unit 160 and a display / operation unit 170. The control unit 160 includes a computer with a CPU 162, a memory 164 which is a storage device, and a communication interface (I / F) 166, etc. The memory 164 stores an image processing program. The display / operation unit 170 is a graphic user interface that displays images and accepts various instructions, and comprises a display 172 and a touch panel 174.

[0029] The configuration of the image viewer 150 is the same as that of the management server 140, so its explanation will be omitted.

[0030] Next, referring to Figure 4, various functions realized by the CPU 162 of the management server 140 executing the image processing program will be explained. The image processing program includes image processing functions, display control functions, and processing functions. When the CPU 162 executes the image processing program having these functions, the CPU 162 functions as an image processing unit 182, a display control unit 184, and a processing unit 186, as shown in Figure 4.

[0031] Next, we will explain in detail the image processing performed by the management server 140 using Figure 5. The CPU 162 of the management server 140 executes an image processing program, thereby realizing the image processing (image processing method) shown in the flowchart of Figure 5.

[0032] The image processing program is executed when the management server 140 receives a fundus image from the ophthalmic device 110 and generates a choroidal vascular image based on the fundus image.

[0033] The choroidal vascular images are generated as follows: The image processing unit 182 of the management server 140 extracts retinal blood vessels from the second fundus image (G-color fundus image) by applying a black hat filter to the second fundus image (G-color fundus image). Next, the image processing unit 182 removes the retinal blood vessels from the first fundus image (R-color fundus image) by inpainting using the retinal blood vessels extracted from the second fundus image (G-color fundus image). In other words, it uses the positional information of the retinal blood vessels extracted from the second fundus image (G-color fundus image) to fill in the retinal vascular structure of the first fundus image (R-color fundus image) with the same value as the surrounding pixels. Then, the image processing unit 182 emphasizes the choroidal blood vessels in the first fundus image (R-color fundus image) by applying Contrast Limited Adaptive Histograph Equalization to the image data of the first fundus image (R-color fundus image) from which the retinal blood vessels have been removed. This yields the choroidal vascular image shown in Figure 6. The generated choroidal vascular image is stored in memory 164. Furthermore, although a choroidal vascular image is generated from the first fundus image (R-color fundus image) and the second fundus image (G-color fundus image), the image processing unit 182 may generate the choroidal vascular image using the first fundus image (R-color fundus image) or an IR fundus image captured with IR light. The disclosure of a method for generating a choroidal fundus image in Japanese Patent Application No. 2018-052246, filed on March 20, 2018, is incorporated herein by reference in its entirety.

[0034] When the image processing program starts, in step 200 of Figure 5, the processing unit 186 reads the choroidal vascular image (see Figure 6) from memory 164.

[0035] In step 202, the image processing unit 182 extracts the fundus region from the choroidal blood vessel image (removing eyelids, etc.), performs a binarization process on the fundus region, and generates a binarized image (Figure 7). In step 204, the image processing unit 182 performs a thickness analysis process to analyze the thickness of choroidal blood vessels that appear white in the binarized image. The thickness analysis process generates a first-thickness blood vessel image in which only blood vessels of the first thickness with a thickness of t3 (μm) or greater are extracted, a second-thickness blood vessel image in which only blood vessels of the second thickness with a thickness between t2 (μm) or greater and less than t3 (μm) are extracted, and a third-thickness blood vessel image in which only blood vessels of the third thickness with a thickness between t1 (μm) or greater and less than t2 (μm) are extracted. Here, t1 is set to 160 (μm), t2 to 320 (μm), and t3 to 480 (μm). Note that while t1 is set to 160 (μm) and t2 to 320 (μm), these values ​​for classifying blood vessel diameters are merely examples, and other values ​​may be used for each. Details of the blood vessel diameter analysis process will be described later.

[0036] In step 206, the display control unit 184 generates three images in which the blood vessel portion of the first blood vessel image is colored red, the blood vessel portion of the second blood vessel image is colored green, and the blood vessel portion of the third blood vessel image is colored blue. Furthermore, these three blood vessel images are combined to generate a colored choroidal blood vessel image that is color-coded according to its thickness. The blood vessel portions of the first blood vessel image, the second blood vessel image, and the third blood vessel image are colored red, green, and blue, respectively, but they may be different colors.

[0037] In step 208, the processing unit 186 saves the various images generated in step 206 to the memory 164.

[0038] Next, referring to Figure 8, we will describe the choroidal vessel diameter analysis process in step 204, which is performed by the image processing unit 182 of the management server 140. In step 212, the image processing unit 182 performs a first contraction process on the generated binarized image (see Figure 7). Figure 9A is a schematic representation of a part of the choroidal blood vessels, showing three different thicknesses of blood vessels 242A, 244A, and 246A (first thickness: 7 pixels, second thickness: 5 pixels, third thickness: 3 pixels) and two areas of noise 241 and 243 (1 pixel size) in white. When the first contraction process (changing the color of pixels from white to black) is performed on Figure 9A, contracting by 3 pixels from the edges of the white areas, as shown in Figure 9B, a part 242B of the first thickness blood vessel 242A remains white, while the other white areas disappear. Next, in step 214, the image processing unit 182 performs a first dilation process on the binarized image (Figure 9B) that has undergone the first contraction process. In the first dilation process, three white pixels are dilated outward from the white area (changing the color of the pixels from black to white). As a result of this process, only the blood vessel 242A of the first thickness is reproduced, as shown in Figure 9C. Then, in step 216, the image processing unit 182 adds red to the portion of the blood vessel 242A of the first thickness, thereby removing noise 241 and 243 and generating a red image of the first thickness blood vessel BG1, as shown in Figure 9D.

[0039] In step 218, the image processing unit 182 performs a second stenosis process on the generated binarized image (see Figure 7). When the second stenosis process (changing the color of pixels from white to black) is performed on Figure 9A, shrinking by 2 pixels from the edge of the white area, as shown in Figure 9E, the first-width blood vessel 242A and parts 242C and 244C of the second-width blood vessel 244A remain white, while the other white areas disappear. Next, in step 220, the image processing unit 182 performs a second dilation process on the binarized image (Figure 9E) that has undergone the second stenosis process. In the second dilation process, the white pixels are dilated by 2 pixels outward from the white area. As a result of this process, as shown in Figure 9F, only the first-width blood vessel 242A and the second-width blood vessel 244A are reproduced. Then, in step 222, the image processing unit 182 takes the difference between the binarized image after the second dilation process (Figure 9F) and the binarized image after the first dilation process (Figure 9C), and adds green to the remaining portion, thereby generating a second diameter blood vessel image BG2, which is free of noise and green, as shown in Figure 9G.

[0040] In step 224, the image processing unit 182 performs a third stenosis process on the generated binarized image (see Figure 7). When the third stenosis process (changing the color of pixels from white to black) is performed on Figure 9A, which stenoses one pixel from the edge of the white area, as shown in Figure 9H, the first blood vessel 242A, the second blood vessel 244A, and parts 242D, 244D, and 246D of the third blood vessel 246A, along with some noise, remain white, while the other white areas disappear. Next, in step 226, the image processing unit 182 performs a third dilation process on the binarized image (Figure 9H) that has undergone the third stenosis process. In the third dilation process, white pixels are dilated one pixel outward from the white area. As a result of this process, the first, second, and third blood vessels are reproduced, as shown in Figure 9I. Then, in step 228, the difference between the binarized image after the third dilation process (Figure 9I) and the binarized image after the second dilation process (Figure 9F) is taken, and the remaining portion is colored blue, thereby removing the noise shown in Figure 9J and generating a blue third-largest vessel image BG3.

[0041] In step 230, the image processing unit 182 extracts the location of the first-size vessel from the first-size vessel image BG1, the location of the second-size vessel from the second-size vessel image BG2, and the location of the third-size vessel from the third-size vessel image BG3, and creates information that combines the size information and the vessel location information.

[0042] In step 232, the image processing unit 182 saves the combined information of diameter information and vessel position information, along with the first diameter vessel image BG1, the second diameter vessel image BG2, and the third diameter vessel image BG3, to the memory 164. Then, the process proceeds to step 206 in Figure 5.

[0043] Next, the display screen of the choroidal vascular analysis mode of the first embodiment will be described. The management server 140 has various data to be displayed on the choroidal vascular analysis mode display screen as follows.

[0044] First, as described above, image data of fundus images (first fundus image (R-color fundus image) and second fundus image (G-color fundus image)) is transmitted from the ophthalmic device 110 to the management server 140, and the management server 140 has the image data of fundus images (first fundus image (R-color fundus image) and second fundus image (G-color fundus image)). The management server 140 has data for each choroidal blood vessel and color data associated with each choroidal blood vessel according to the thickness of the choroidal blood vessel.

[0045] Furthermore, when a patient's fundus is photographed, the ophthalmic device 110 receives the patient's personal information. This personal information includes the patient's ID, name, age, and visual acuity. When the fundus is photographed, information indicating whether the eye being photographed is the right or left eye is also entered. Additionally, the date and time of the photograph are entered. The ophthalmic device 110 transmits the personal information, right / left eye information, and the date and time of the photograph to the management server 140. The management server 140 holds the personal information, right / left eye information, and the date and time of the photograph. The management server 140 also holds the axial length data.

[0046] As described above, the management server 140 has data (content data) to be displayed on the display screen of the choroidal vascular analysis mode.

[0047] Incidentally, there are times when a doctor diagnoses the condition of a patient's choroidal blood vessels. In this case, the doctor sends a request to the management server 140 via the image viewer 150 to generate a display screen for choroidal blood vessel analysis mode. Upon receiving this instruction, the management server 140 sends data for the choroidal blood vessel analysis mode display screen to the image viewer 150. Upon receiving the data for the choroidal blood vessel analysis mode display screen, the image viewer 150 displays the choroidal blood vessel analysis mode display screen 300 shown in Figure 10 on the display 172 of the image viewer 150 based on the data for the choroidal blood vessel analysis mode display screen.

[0048] Here, we will explain the display screen 300 of the choroidal vascular analysis mode shown in Figure 10. As shown in Figure 10, the display screen 300 of the choroidal vascular analysis mode has a personal information display area 302 for displaying the patient's personal information, an image display area 320, and a choroidal analysis tool display area 330.

[0049] The personal information display area 302 includes a patient ID display area 304, a patient name display area 306, an age display area 308, an axial length display area 310, a visual acuity display area 312, and a patient selection icon 314. The patient ID display area 304, patient name display area 306, age display area 308, axial length display area 310, and visual acuity display area 312 display the respective information. When the patient selection icon 314 is clicked, a list of patients is displayed on the display 172 of the image viewer 150, and the user (doctor) is prompted to select the patient to be analyzed.

[0050] The image display area 320 includes shooting date display areas 322N1 to 322N3, right eye information display area 324R, left eye information display area 324L, RG image display area 326, and choroidal vascular image display area 328. The shooting date display areas 322N1 to 322N3 correspond to the shooting dates of January 1, 2016, January 1, 2017, and January 1, 2018, respectively. The RG image is obtained by combining the first fundus image (R-color fundus image) and the second fundus image (G-color fundus image) with the size of each pixel value in a predetermined ratio (for example, 1:1).

[0051] The choroidal analysis tool display area 330 is a field where icons for selecting multiple choroidal analyses are displayed. It includes vortex vein location icons 332, symmetry icons 334, vessel diameter icons 336, vortex vein / macula / optic disc icons 338, and choroidal analysis report icons 340. The vortex vein location icon 332 indicates that the analysis results for vortex vein location should be displayed. The symmetry icon 334 indicates that the analysis results for the symmetry of choroidal vessels in the fundus should be displayed. The vessel diameter icon 336 indicates that the analysis results for the diameter of choroidal vessels should be displayed. The vortex vein / macula / optic disc icon 338 indicates that the analysis results for the position between vortex veins, macula, and optic disc should be displayed. The choroidal analysis report icon 340 indicates that the choroidal analysis report should be displayed.

[0052] In the example shown in Figure 10, the fundus of the right eye of the patient identified by patient ID: 123456 (icon 324R is lit) displays the RG image and choroidal image taken on the day corresponding to the date of acquisition of acquisition date display field 322N3, which is one of the acquisition date display fields 322N1 to 322N3 that was clicked.

[0053] Next, the first display mode of the choroidal vascular analysis mode screen displayed on the image viewer 150 will be described. The image viewer 150 displays the choroidal vascular analysis mode screen 300 shown in Figure 10 on the display 172 of the image viewer 150. When the vessel diameter icon 336 in the choroidal analysis tool display area 330 of Figure 10 is clicked, the display changes to the vessel diameter display screen shown in Figure 11 (the image display area 320 of Figure 10 changes to the vessel diameter display screen 320a of Figure 11).

[0054] As shown in Figure 11, the vessel diameter display screen 320a includes a colored vessel diameter image display area 352 that displays a colored vessel diameter image, an enlarged image display area 354 that displays an enlarged image of a part of the colored vessel diameter image, and a reduced choroidal vessel image display area 356 that displays a reduced choroidal vessel image.

[0055] The image viewer 150, via its GUI (Graphical User Interface, hereinafter referred to as GUI), displays a rectangular frame 353 in the corresponding position in the colored vessel diameter image display area 352 when a region, for example, a rectangular region as shown in Figure 11, is specified in the reduced choroidal vessel image display area 356. At the same time, it displays an enlarged image of the specified region in the enlarged image display area 354.

[0056] The image display area 320a is further provided with thickness 1 icons 362, thickness 2 icons 364, and thickness 3 icons 366, which instruct the display of images of choroidal vessels of the first thickness, second thickness, and third thickness, respectively, and an ALL icon 368, which instructs the display of images of choroidal vessels of all thicknesses.

[0057] The blood vessel diameter⇔choroid icon 370 is a button that switches the display content between the colored blood vessel diameter image display area 352 and the reduced choroidal blood vessel image display area 356. When the blood vessel diameter⇔choroid icon 370 is clicked in the display state shown in Figure 11, the choroidal fundus image is displayed in the colored blood vessel diameter image display area 352, and the reduced choroidal blood vessel image is displayed in the reduced choroidal blood vessel image display area 356. In Figure 11, the ALL icon 368 is clicked, and images of choroidal blood vessels of all diameters are displayed in both the colored blood vessel diameter image display area 352 and the enlarged image display area 354. Also in Figure 11, an example is shown where the blood vessel diameter⇔choroid icon 370 is clicked, and the blood vessel diameter image in the colored blood vessel diameter image display area 352 is displayed larger than the choroidal blood vessel image in the choroidal blood vessel image display area 356.

[0058] If the Thickness 1 icon 362 is clicked, only the first-largest vessel, displayed in red, will be displayed in the first-largest vessel image, colored vessel diameter image display area 352. If the Thickness 2 icon 364 is clicked, only the second-largest vessel, displayed in green, will be displayed in the second-largest vessel image, colored vessel diameter image display area 352. If the Thickness 3 icon 366 is clicked, only the third-largest vessel, displayed in blue, will be displayed in the third-largest vessel image, colored vessel diameter image display area 352.

[0059] The display screen of the image viewer 150, as described later, displays icons and buttons for instructing the generation of images, as described later. When a user of the image viewer 150 (such as an ophthalmologist) clicks an icon, etc., the image viewer 150 sends an instruction signal corresponding to the clicked icon, etc. to the management server 140. Upon receiving the instruction signal from the image viewer 150, the management server 140 generates an image corresponding to the instruction signal and sends the image data of the generated image to the image viewer 150. Upon receiving the image data from the management server 140, the image viewer 150 displays the image on the display based on the received image data. The display screen generation process on the management server 140 is performed by a display screen generation program running on the CPU 162.

[0060] Next, the second display mode of the choroidal vascular analysis mode screen displayed on the image viewer 150 will be described. Similar to the first display mode, the image viewer 150 displays the choroidal vascular analysis mode screen 300 shown in Figure 10 on the display 172 of the image viewer 150. When the vessel diameter icon 336 in the choroidal analysis tool display area 330 of Figure 10 is clicked, the display screen changes to the vessel diameter display screen shown in Figure 12 (the image display area 320 of Figure 10 changes to the vessel diameter display screen 320b of Figure 12). In the second display mode, the same reference numerals are used for the display content as in the first display mode, and their explanations are omitted.

[0061] As shown in Figure 12, the vessel diameter display screen 320b includes a colored vessel diameter image display area 352 that displays a colored vessel diameter image, an enlarged image display area 354 that displays an enlarged image of the colored vessel diameter image, and a reduced choroidal vessel image display area 356 in which the positions of vortex veins (hereinafter referred to as VV) are superimposed on a reduced choroidal vessel image. In the choroidal vessel image displayed in the reduced choroidal vessel image display area 356, the VV positions 376 are indicated by circular frames. In Figure 12, three VV positions are indicated by circular frames.

[0062] Vortex veins (VV) are the outflow pathways for blood flow that has entered the choroid, and there are 4 to 6 of them located near the posterior pole of the equatorial region of the eyeball. The location of the VV is calculated based on the direction of the choroidal blood vessels.

[0063] The image viewer 150 receives the data for the display screen 300 shown in Figure 12 from the management server 140. The management server 140 then executes the display screen data creation processing program shown in Figure 24 to create the data for the display screen 300 shown in Figure 12. The display screen data creation processing program shown in Figure 24 will be described below. In step 200, the processing unit 186 reads the choroidal vascular image (see Figure 6) from the memory 164.

[0064] In step 401, the VV position detection process is executed to detect the position of VV. The VV position detection process will now be explained. The VV position detection process is performed by analyzing the choroidal vascular image read in step 200. The image processing unit 182 analyzes the VV position as follows.

[0065] The image processing unit 182 detects the direction of course (vascular course) of each choroidal vessel in the choroidal vessel image. Specifically, firstly, the image processing unit 182 performs the following processing for each pixel in the choroidal vessel image. That is, the image processing unit 182 sets a region (cell) centered on the pixel and creates a histogram of the gradient direction of brightness for each pixel within the cell. The direction of the brightness gradient is indicated by an angle ranging from 0 degrees or more to less than 180 degrees. Note that 0 degrees is defined as the direction of a straight line (horizontal line). The image processing unit 182 creates a histogram with nine bins (each bin width of 20 degrees) where the brightness gradient direction is, for example, 0 degrees, 20 degrees, 40 degrees, 60 degrees, 80 degrees, 100 degrees, 120 degrees, 140 degrees, and 160 degrees. To do this, the unit counts the number of pixels in the cells corresponding to the gradient direction of each bin. Each bin in the histogram corresponds to a width of 20 degrees. The 0-degree bin is set to the number of pixels (count values) within a cell with gradient directions of 0 degrees to less than 10 degrees and 170 degrees to less than 180 degrees. The 20-degree bin is set to the number of pixels (count values) within a cell with gradient directions of 10 degrees to less than 30 degrees. Similarly, count values ​​are set for the bins at 40 degrees, 60 degrees, 80 degrees, 100 degrees, 120 degrees, 140 degrees, and 160 degrees. Since there are 9 bins in the histogram, the direction of blood vessel course for each pixel is defined by one of 9 different directions. Note that the resolution of blood vessel course can be increased by narrowing the bin width and increasing the number of bins. The count values ​​in each bin (vertical axis of the histogram) are normalized, and a histogram is created for the analysis points. Next, the image processing unit 182 determines the gradient direction of the bin with the lowest count in the histogram for each cell as the gradient direction for the pixel within each cell. This gradient direction corresponds to the direction of blood vessel course. The reason why the gradient direction with the lowest count corresponds to the direction of blood vessel course is as follows: The brightness gradient is small in the direction of blood vessel course, while the brightness gradient is large in other directions (for example, there is a large difference in brightness between blood vessels and non-blood vessels). Therefore, when a histogram of the brightness gradient for each pixel is created, the count for the direction of blood vessel course will be small. Through the above processing, the direction of blood vessel course for each pixel in the choroidal blood vessel image is detected.

[0066] The image processing unit 182 sets the initial positions of M (natural number) × N (natural number) (=L) virtual particles. Specifically, the image processing unit 182 sets M initial positions vertically and N initial positions horizontally, for a total of L, at equal intervals on the choroidal vessel image. By using the detected information on the direction of vessel course, the position of vortex vein VV is estimated by moving the virtual particles on the choroidal vessel in the direction of vessel course. Since vortex vein VV is a region where multiple choroidal vessels converge, this process utilizes the fact that the multiple virtual particles placed on the image will eventually follow the vessels and converge at the position of the vortex vein.

[0067] The image processing unit 182 estimates the VV position. Specifically, the image processing unit 182 performs the following processing for each of the L positions. That is, the image processing unit 182 obtains the direction of blood vessel movement at the initial position (any of the L positions), moves a virtual particle a predetermined distance along the obtained direction of blood vessel movement, obtains the direction of blood vessel movement again at the moved position, and moves the virtual particle a predetermined distance along the obtained direction of blood vessel movement. This process of moving along the direction of blood vessel movement by a predetermined distance is repeated for a predetermined number of moves. The above processing is performed for all L positions. The point where a certain number of virtual particles have gathered at that point is defined as the VV position. VV position information (such as the number of VVs and their coordinates on the choroidal vessel image) is stored in memory 164. VV position information is used to create the screens of the third embodiment of the choroidal vessel analysis mode display screen shown in Figures 12 to 15 and Figure 22, which will be described later.

[0068] In step 204, the image processing unit 182 performs a thickness analysis process to analyze the thickness of choroidal blood vessels that appear white in the binarized image, as described above. In step 403, the image processing unit 182 saves the VV position and thickness analysis results to the memory 164. In step 405, the image processing unit 182 creates a display screen (such as Figure 12).

[0069] In this way, the image viewer 150 receives data for the display screen 300 shown in Figure 12 from the management server 140. When the management server 140 executes the display screen data creation processing program shown in Figure 12 to create data for the display screen 300, such as Figure 12, the management server 140 sends the display screen data to the image viewer 150. VV position information (such as the number of VVs and their coordinates on the choroidal vessel image) is stored in memory 164. VV position information is used to create the screens of the third embodiment of the choroidal vessel analysis mode display screen shown in Figures 12 to 15 and Figure 22, which will be described later.

[0070] When a VV region to be enlarged, for example a rectangular area as shown in Figure 12, is specified in the GUI of the reduced choroidal vessel image display area 356 of the image viewer 150, a rectangular frame 353 and a circular frame surrounding the VV position 376 within it are displayed at the corresponding position in the colored vessel diameter image display area 352. Then, an enlarged image of the specified VV region is displayed in the enlarged image display area 354. The VV position 376 and the circular frame surrounding it are superimposed on the enlarged image.

[0071] In Figure 12, when the ALL icon 368 is clicked, images of choroidal vessels of all diameters are displayed in both the colored vessel diameter image display area 352 and the magnified image display area 354. In this state, for example, if the diameter 1 icon 362 is clicked, the display content in the colored vessel diameter image display area 352 and the magnified image display area 354 will show only images of vessels of the first diameter, as shown in the vessel diameter image display area 372R and the magnified image display area 374R in Figure 13. Since the first diameter vessel is associated with red, it will be displayed in red. When the diameter 2 icon 364 is clicked, the display content in the colored vessel diameter image display area 352 and the magnified image display area 354 will show only images of vessels of the second diameter, as shown in the vessel diameter image display area 372B and the magnified image display area 374B in Figure 14. Since the second diameter vessel is associated with blue, it will be displayed in green. When the thickness 3 icon 366 is clicked, the display contents of the colored vessel diameter image display area 352 and the enlarged image display area 354 will show only images of vessels of the third thickness, as shown in the vessel diameter image display area 372G and the enlarged image display area 374G in Figure 15. Since the third thickness is associated with green, the third thickness vessels will be displayed in blue.

[0072] Next, a third display mode of the choroidal vascular analysis mode screen displayed on the image viewer 150 will be described. Similar to the first display mode, the image viewer 150 displays the choroidal vascular analysis mode screen 300 shown in Figure 10 on the display 172 of the image viewer 150. When the vessel diameter icon 336 in the choroidal analysis tool display area 330 of Figure 10 is clicked, the display screen changes to a combined display screen of the vessel diameter analysis results and VV position analysis results shown in Figure 22 (the image display area 320 in Figure 10 changes to the vessel diameter display screen 320c in Figure 22).

[0073] Next, the third display mode of the choroidal vascular analysis mode screen will be explained. In the third display mode, the same reference numerals are used for parts that are the same as in the first display mode, and their explanations are omitted.

[0074] As shown in Figure 22, the vessel diameter display screen 320c displays a choroidal vessel image in the reduced choroidal vessel image display area 356, with the VV position 376 superimposed on the choroidal vessel image. In Figure 22, a circular frame with a predetermined radius centered on the VV position is displayed on the choroidal vessel image. In Figure 12, three VV positions are shown with circular frames. The vessel diameter display screen 320c further includes display fields for displaying a VV position magnified image 420, a VV thinned line image 422, a VV vessel diameter direction map 424, a vessel diameter histogram 426, and a thickness analysis plot icon 380. The thickness analysis plot icon 380 is a button that switches the display content to the display screen shown in Figure 23, which will be described later. When a VV (Vestibular Vein) location is specified in the GUI, a rectangular frame 377 is displayed in the reduced choroidal vessel image display area 356 of the choroidal vessel image, surrounding the circular frame of the specified VV location. Then, an enlarged image 420 of the VV location within the rectangular frame 377 is displayed in the display area. The enlarged VV location image 420 is created and displayed using data from a detailed analysis of the choroidal vessels around the specified VV. Similarly, a VV vessel diameter direction map 424 is created and displayed in the VV vessel diameter direction map display area.

[0075] Next, with reference to Figure 16, the method for creating the VV thinning image 422 and the VV vascular diameter direction map 424 (image processing program) will be described in detail. The image processing program shown in Figure 16 is executed when a choroidal vascular image is generated based on the fundus image, similar to the program in Figure 5.

[0076] In step 1232 of Figure 16, the processing unit 186 reads the choroidal vascular image (see Figure 6), and in step 1234, the image processing unit 182 performs the VV position analysis process described above.

[0077] In step 1236, the image processing unit 182 extracts an image of a predetermined region including the VV position in the choroidal vascular image.

[0078] In step 1238, the image processing unit 182 generates a binarized image from the extracted image of a predetermined region. In step 1240, as shown in Figure 17, the image processing unit 182 sets a circle 404 with a predetermined radius centered on the VV position 402 in the generated binarized image. The predetermined radius of the circle 404 is 6 mm. Depending on the required analysis, the radius of the circle 404 may be set between 2 mm and 20 mm. The radius of the circle 404 may also be set based on the vascular course pattern around the VV position. In step 1242, the image processing unit 182 performs a thinning process on the binarized image. In step 1244, the image processing unit 182 detects the intersection points 406 of the circle 404 and the thin lines, as shown in Figure 18. In step 1246, the image processing unit 182 generates a depth image from the binarized image, as shown in Figure 19. The depth image is an image in which the brightness gradually increases from the edges of the lines towards the center, depending on the thickness of the lines in the binarized image, and the brightness at the center of the lines increases as the thickness of the lines increases.

[0079] In step 1248, the image processing unit 182 extracts the brightness values ​​of the positions corresponding to each intersection 406 from the depth image. In step 1250, the image processing unit 182 converts the brightness values ​​of each intersection 406 to the blood vessel diameter according to a lookup table stored in memory 164 that shows the correspondence between pixel brightness and blood vessel diameter.

[0080] In step 1252, the display control unit 184 creates a graph, as shown in Figure 20, with the angle from a predetermined position (e.g., the uppermost end) of the circle where the intersection point 406 is located on the horizontal axis, and the diameter of the blood vessel at the intersection point 406 on the vertical axis. From this graph, the thickness of the blood vessel running from position VV 402 and the direction of the blood vessel's course can be visualized. In step 1254, the display control unit 184 aggregates the vessel diameters at each intersection 406, as shown in Figure 21, and creates a histogram of the number of choroidal vessels and their diameters, where there are 6 bottles and the bottle width is 200 μm. From this histogram, the distribution of vessel diameters leading to the VV can be visualized, making it possible to estimate the blood flow rate into the VV.

[0081] In step 1256, the processing unit 186 saves the following data: VV position, binarized image, circle 404 with a predetermined radius centered on VV position 402, intersection 406 of circle 404 and thin line, distance image, brightness value of the position corresponding to each intersection 406, vessel diameter converted from the brightness value of each intersection 406, graph of angle and vessel diameter, and histogram of the number of choroidal vessels and vessel diameter. This data is saved in memory 164.

[0082] Next, we will explain the fourth display mode of the choroidal vessel analysis mode screen displayed in the image viewer 150 when the thickness analysis plot icon 380 in Figure 22 is clicked. When the thickness analysis plot icon 380 in Figure 22 is clicked, the display screen changes to one that combines the vessel diameter analysis results and VV position analysis results shown in Figure 23 (the image display area 320c in Figure 22 changes to the image display area 320d in Figure 23). In the fourth display mode, the same reference numerals are used for parts of the display mode that are the same as in the first display mode, and their explanations are omitted.

[0083] Next, we will explain the image display area 320d in Figure 23. In the center of the image display area 320d, a colored choroidal vessel image 500 is displayed with the locations of the vortex veins (VVs) superimposed. In Figure 23, there are four VVs in the choroidal vessel image 500: VV520 in the upper left, VV540 in the lower left, VV560 in the upper right, and VV580 in the lower right. Furthermore, a circle 522 with a predetermined radius centered on VV520 is superimposed on the choroidal vascular image 500. Similarly, circles 542, 562, and 582 are superimposed on the other VVs.

[0084] In the upper left of the image display area 320d, a circle enlargement image 524 and a pie chart 526 are also displayed. The circle enlargement image 524 is an enlarged view of the colored choroidal blood vessel image of the area enclosed by circle 522. The pie chart 526 shows the proportion of pixels occupied by the blood vessel region of each of several different thicknesses, with the total number of pixels in the blood vessel region within circle 522 being set to 100. Specifically, for example, the pie chart 526 includes, firstly, the proportion of pixels occupied by the blood vessel region of the first thickness (480 μm or more), which is a large blood vessel; secondly, the proportion of pixels occupied by the blood vessel region of the second thickness (320 μm or more but less than 480 μm), which is a medium-sized blood vessel; and thirdly, the proportion of pixels occupied by the blood vessel region of the third thickness (less than 320 μm), which is a small blood vessel. Similarly, the enlarged circle image 544 and pie chart 546 are displayed in the lower left of image display area 320d, the enlarged circle image 564 and pie chart 566 are displayed in the upper right of image display area 320d, and the enlarged circle image 584 and pie chart 586 are displayed in the lower right of image display area 320d. Each image displayed in the image display area 320d is created by the image processing unit 182 of the management server 140.

[0085] In the fourth display mode, users such as ophthalmologists can comprehensively grasp the location of all VVs, as well as magnified images of each VV and the distribution of blood vessel diameters, on the display screen.

[0086] In each of the embodiments described above, choroidal blood vessels are extracted from the fundus image, and the thickness of the choroidal blood vessels is determined.

[0087] Conventionally, the choroidal vascular network is quantified from OCT measurement data, but its thickness cannot be determined. However, as described above, in each embodiment, retinal blood vessels and choroidal blood vessels are separated from the first fundus image (R-color fundus image) or IR fundus image and the second fundus image (G-color fundus image), the thickness of the choroidal blood vessels is determined, and the determined thickness is visualized by displaying it in a different color. Therefore, the thickness of the choroidal blood vessels can be determined. Furthermore, by analyzing and visualizing the diameter of choroidal blood vessels around the vortex vein VV location, it can assist ophthalmologists in their diagnoses. In the above embodiment, the position of the VV can be analyzed, and the diameter of the choroidal blood vessels around the VV can be analyzed. In the above embodiment, since the positional information of each diameter of the choroidal blood vessels is retained, statistical processing can be easily performed. In the above embodiment, a wide area of ​​the fundus is photographed with an external light irradiation angle of approximately 120 degrees (approximately 200 degrees with the internal light irradiation angle), making it possible to visualize the choroid of a wide area of ​​the fundus. Therefore, it is possible to analyze not only the thickness of the choroidal blood vessels in the peripheral part of the fundus, but also the thickness of the choroidal blood vessels around vortex vein VV located near the equator of the eyeball.

[0088] Next, various modifications of the technology of this disclosure will be described. <First variation> In the embodiments described above, choroidal vascular images are analyzed, but the technology of this disclosure is not limited thereto. For example, images of cross-sections of the fundus obtained by OCT-En Face images (fundus images constructed from 3D OCT data), images obtained by ICG (indocyanine green) fluorescence angiography, images obtained by FA (Fluorescein Angiography), FAF (Fundus Autofluorescence, images obtained by autofluorescence imaging), etc., may also be analyzed.

[0089] <Second variation> In the embodiments described above, choroidal blood vessels are displayed by changing the color according to their thickness, but the technology of this disclosure is not limited thereto, and choroidal blood vessels may also be displayed by changing the brightness value according to their thickness.

[0090] <Third variation> In the above embodiment, the management server 140 has already executed an image processing program, but the technology of this disclosure is not limited thereto. For example, the following may be done: For example, when the display screen 300 of the choroidal blood vessel analysis mode shown in Figure 10 is displayed on the display 172 of the image viewer 150, the management server 140 executes an image processing program when the blood vessel diameter icon 336 is clicked. Specifically, when the blood vessel diameter icon 336 is clicked, the image viewer 150 sends a command to the management server 140. The management server 140 may execute an image processing program when it receives the command.

[0091] <Fourth variation> In the above embodiment, an example was described in which a fundus image with an internal light illumination angle of approximately 200 degrees is acquired using an ophthalmic device 110. The technology of this disclosure is not limited to this, and the technology of this disclosure may also be applied to fundus images taken with an ophthalmic device with an internal illumination angle of 100 degrees or less, or to montage images obtained by combining multiple fundus images.

[0092] <Fifth variation> In the above embodiment, fundus images are captured using an ophthalmic device 110 equipped with an SLO imaging unit. However, fundus images obtained using a fundus camera capable of capturing choroidal blood vessels may also be used, or the technology of this disclosure may be applied to images obtained by OCT angiography.

[0093] <Sixth variation> In the above embodiment, the management server 140 executes the image processing program. The technology of this disclosure is not limited thereto. For example, the ophthalmic device 110 or the image viewer 150 may execute the image processing program. When the ophthalmic device 110 executes the image processing program, the image processing program is stored in memory 24. When the image viewer 150 executes the image processing program, the image processing program is stored in the memory 164 of the image viewer 150.

[0094] <Seventh variation> In the above embodiment, an ophthalmic system 100 comprising an ophthalmic device 110, an axial length measuring instrument 120, a management server 140, and an image viewer 150 was described as an example, but the technology of this disclosure is not limited thereto. For example, as a first example, the axial length measuring instrument 120 may be omitted, and the ophthalmic device 110 may further have the functions of the axial length measuring instrument 120. As a second example, the ophthalmic device 110 may further have the functions of at least one of the management server 140 and the image viewer 150. For example, if the ophthalmic device 110 has the functions of the management server 140, the management server 140 can be omitted. In this case, the image processing program is executed by either the ophthalmic device 110 or the image viewer 150. Also, if the ophthalmic device 110 has the functions of the image viewer 150, the image viewer 150 can be omitted. As a third example, the management server 140 may be omitted, and the image viewer 150 may perform the functions of the management server 140.

[0095] <Other variations> The data processing described in the above embodiment is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose. Furthermore, while the above embodiments illustrate cases where data processing is realized by a software configuration using a computer, the technology of this disclosure is not limited thereto. For example, instead of a software configuration using a computer, data processing may be performed solely by a hardware configuration such as an FPGA or ASIC. Alternatively, some of the data processing may be performed by a software configuration, and the remaining processing may be performed by a hardware configuration.

Claims

[Claim 1] The steps include detecting the location of vortex veins from fundus images in which the pleural vessels are visualized, and The process involves extracting a first-width choroidal blood vessel and a second-width choroidal blood vessel, which is different from the first-width, by image processing of the fundus image. The steps include generating a thickness-analyzed fundus image in which a position indicator image showing the location of the vortex veins is superimposed on the fundus image, and the first thickness choroidal vessel is displayed using a first display method, and the second thickness choroidal vessel is displayed using a second display method different from the first display method, Image processing methods including [specific details omitted].

Images