Image processing method, program, and image processing device

Abstract

To visualize the size of choroidal blood vessels.SOLUTION: A vortex vein position is detected from a choroidal vascular image in which choroidal blood vessels have been visualized. Image processing is applied to the choroidal vascular image to extract first size choroidal blood vessels of a first size and second size choroidal blood vessels of a second size different from the first size, from the choroidal vascular image. A size analysis fundus image is generated in which a rectangular frame indicating the vortex vein position is displayed superimposed on the choroidal vascular image and in which the first size choroidal blood vessels are displayed in red and the second size choroidal blood vessels are displayed in blue.SELECTED DRAWING: Figure 12

Description

[Technical Field]

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

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

[0003] An image processing method according to a first aspect of the disclosed technique includes the steps of: detecting the position of a vortex vein from a fundus image in which choroidal vessels are visualized; extracting first-thickness choroidal vessels having a first thickness and second-thickness choroidal vessels having a second thickness different from the first thickness by image processing the fundus image; and generating a thickness analysis fundus image in which a position display image indicating the position of the vortex vein is superimposed on the fundus image and the first-thickness choroidal vessels are displayed in a first display method and the second-thickness choroidal vessels are displayed in a second display method different from the first display method.

[0004] An image processing method according to a second aspect of the disclosed technique includes the steps of detecting the 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, identifying 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] An image processing method according to a third aspect of the disclosed technique includes the steps of detecting the position of a vortex vein from a fundus image in which choroidal blood vessels are visualized, detecting an intersection between a circle centered on the position of the vortex vein and the choroidal blood vessel, identifying the diameter of the choroidal blood vessel at the intersection, and creating a histogram of the diameter and the number of choroidal blood vessels.

[0006] A program according to a fourth aspect of the technique of the present disclosure causes a computer to execute the image processing method according to any one of the first to third aspects.

[0007] An image processing device according to a fifth aspect of the disclosed technology is an image processing device comprising a storage device that stores a program for causing a processing device to execute an image processing method, and a processing device that executes the image processing method by executing the program stored in the storage device, wherein the image processing method is any one of the image processing methods according to the first to third aspects.

[0008] An image processing method according to a sixth aspect of the disclosed technique includes the steps of detecting the position of a vortex vein 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 showing the relationship between the position of the vortex vein and the thickness of the choroidal blood vessels. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a block diagram of an ophthalmology system 100. [Figure 2] 1 is a schematic diagram showing the overall configuration of an ophthalmologic apparatus 110. FIG. [Figure 3] FIG. 2 is a block diagram of the electrical configuration of the management server 140. [Figure 4] FIG. 2 is a functional block diagram of a CPU 162 of a management server 140. [Figure 5] 4 is a flowchart of an image processing program according to the first embodiment. [Figure 6] FIG. 10 is a diagram showing an image of choroidal blood vessels. [Figure 7] FIG. 10 is a diagram showing a binarized image of a choroidal blood vessel image. [Figure 8] 6 is a flowchart of a choroidal vessel thickness analysis processing program in step 204 of FIG. 5. [Figure 9A] FIG. 10 is an explanatory diagram illustrating a choroidal blood vessel thickness analysis process. [Figure 9B]FIG. 10 is an explanatory diagram illustrating a choroidal blood vessel thickness analysis process. [Figure 9C] FIG. 10 is an explanatory diagram illustrating a choroidal blood vessel thickness analysis process. [Figure 9D] FIG. 10 is an explanatory diagram illustrating a choroidal blood vessel thickness analysis process. [Figure 9E] FIG. 10 is an explanatory diagram illustrating a choroidal blood vessel thickness analysis process. [Figure 9F] FIG. 10 is an explanatory diagram illustrating a choroidal blood vessel thickness analysis process. [Figure 9G] FIG. 10 is an explanatory diagram illustrating a choroidal blood vessel thickness analysis process. [Figure 9H] FIG. 10 is an explanatory diagram illustrating a choroidal blood vessel thickness analysis process. [Figure 9I] FIG. 10 is an explanatory diagram illustrating a choroidal blood vessel thickness analysis process. [Figure 9J] FIG. 10 is an explanatory diagram illustrating a choroidal blood vessel thickness analysis process. [Figure 10] FIG. 3 is a diagram showing a display screen 300 in a choroidal vessel analysis mode. [Figure 11] FIG. 3 is a diagram showing a display screen 300 including a display screen displaying a blood vessel diameter. [Figure 12] FIG. 10 is a diagram showing a display screen 300 in which a VV position is superimposed on a display screen that displays a blood vessel diameter. [Figure 13] FIG. 10 is a diagram showing a display screen 300 that is displayed when a thickness 1 icon 362 is clicked. [Figure 14] FIG. 10 is a diagram showing a display screen 300 that is displayed when a thickness 2 icon 364 is clicked. [Figure 15] FIG. 10 is a diagram showing a display screen 300 that is displayed when a thickness 3 icon 366 is clicked. [Figure 16] 10 is a flowchart of an image processing program according to a fourth embodiment. [Figure 17] This is a diagram in which a circle 404 of a predetermined radius is set with a VV position 402 as its center in a binarized image generated from a choroidal blood vessel image. [Figure 18] This is a diagram showing the intersection 406 between the circle 404 and the thin line. [Figure 19] FIG. 10 is a diagram showing a distance image generated from a binarized image of a choroidal blood vessel image. [Figure 20] 1 is a graph showing the relationship between the angle from the top of the circle and the diameter of the blood vessel. [Figure 21] 1 is a histogram of the number and diameter of choroidal vessels. [Figure 22] FIG. 10 is a diagram showing a display screen that displays each piece of data on blood vessel diameter. [Figure 23] FIG. 10 is a diagram showing a display screen combining the results of vascular diameter analysis and VV position analysis. [Figure 24] 10 is a flowchart of an image processing program. DETAILED DESCRIPTION OF THE INVENTION

[0010] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. For convenience of explanation, a scanning laser ophthalmoscope will be referred to as an "SLO" below.

[0011] The configuration of an ophthalmologic system 100 will be described with reference to Fig. 1. As shown in Fig. 1, the ophthalmologic system 100 includes an ophthalmologic apparatus 110, an axial length measuring device 120, a management server apparatus (hereinafter referred to as "management server") 140, and an image display device (hereinafter referred to as "image viewer") 150. The ophthalmologic apparatus 110 acquires fundus images. The axial length measuring device 120 measures the axial length of a patient. The management server 140 stores a plurality of fundus images and axial lengths obtained by photographing the funduses of a plurality of patients using the ophthalmologic apparatus 110, in association with the patient IDs. The image viewer 150 displays the fundus images acquired by the management server 140.

[0012] The ophthalmologic apparatus 110, the axial length measuring device 120, the management server 140, and the image viewer 150 are connected to one another via a network .

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

[0014] Next, the configuration of the ophthalmologic apparatus 110 will be described with reference to Fig. 2. As shown in Fig. 2, the ophthalmologic apparatus 110 includes a control unit 20, a display / operation unit 30, and an SLO unit 40, and captures an image of the posterior segment (fundus) of the subject's eye 12. The apparatus may further include an OCT unit (not shown) that acquires OCT data of the fundus.

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

[0016] The SLO unit 40 includes a light source 42 of G light (green light: wavelength 530 nm), a light source 44 of R light (red light: wavelength 650 nm), and a light source 46 of IR light (infrared (near-infrared light): wavelength 800 nm). The light sources 42, 44, and 46 emit their respective lights in response to commands from the control unit 20. The SLO unit 40 includes optical systems 50, 52, 54, and 56 that reflect or transmit the light from the light sources 42, 44, and 46 to guide them into one optical path. The optical systems 50 and 56 are mirrors, and the optical systems 52 and 54 are beam splitters. The G light is reflected by the optical systems 50 and 54, the R light is transmitted through the optical systems 52 and 54, and the IR light is reflected by the optical systems 52 and 56 to be guided into one optical path, respectively.

[0017] The SLO unit 40 includes a wide-angle optical system 80 that two-dimensionally scans light from the light sources 42, 44, and 46 over the posterior segment (fundus) of the subject's eye 12. The SLO unit 40 includes a beam splitter 58 that reflects G light from the posterior segment (fundus) of the subject's eye 12 and transmits all light other than G light. The SLO unit 40 includes a beam splitter 60 that reflects R light from the light that has passed through the beam splitter 58 and transmits all light other than R light. The SLO unit 40 includes a beam splitter 62 that reflects IR light from the light that has passed through the beam splitter 60. The SLO unit 40 includes a G light detecting element 72 that detects G light reflected by the beam splitter 58, an R light detecting element 74 that detects R light reflected by the beam splitter 60, and an IR light detecting element 76 that detects IR light reflected by the beam splitter 62.

[0018] The wide-angle optical system 80 includes an X-direction scanning device 82 composed of a polygon mirror that scans light from the light sources 42, 44, and 46 in the X direction, a Y-direction scanning device 84 composed of a galvanometer mirror that scans light in the Y direction, and an optical system 86 including a slit mirror and an elliptical mirror (not shown) that widens the angle of the scanned light. The optical system 86 increases the field of view (FOV) of the fundus to a larger angle than conventional techniques, enabling a wider fundus area to be imaged than conventional techniques. Specifically, it is possible to image a wider fundus area with an external light irradiation angle of approximately 120 degrees from outside the subject's eye 12 (approximately 200 degrees, with the center O of the eyeball of the subject's eye 12 as the reference position, and the internal light irradiation angle that can be substantially imaged by irradiating the fundus of the subject's eye 12 with scanning light). The optical system 86 may be configured using a group of multiple lenses instead of a slit mirror and an elliptical mirror. Each of the scanning devices, the X-direction scanning device 82 and the Y-direction scanning device 84, may be a two-dimensional scanner configured using MEMS mirrors.

[0019] When a system including a slit mirror and an elliptical mirror is used as optical system 86, a configuration using a system using an elliptical mirror as described in International Application No. PCT / JP2014 / 084619 or International Application No. PCT / JP2014 / 084630 may be used. The disclosures of International Application No. PCT / JP2014 / 084619 filed on December 26, 2014 (International Publication No. WO2016 / 103484) and International Application No. PCT / JP2014 / 084630 filed on December 26, 2014 (International Publication No. WO2016 / 103489) are each incorporated herein by reference in their entirety.

[0020] When the ophthalmologic apparatus 110 is placed on a horizontal plane, the horizontal direction is defined as the "X direction," the vertical direction relative 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 subject's eye 12 and the center of the eyeball is defined as the "Z direction." Therefore, the X direction, Y direction, and Z direction are perpendicular to each other.

[0021] A color fundus image is obtained by simultaneously photographing the fundus of the subject's eye 12 with G light and R light. More specifically, the control unit 20 controls the light sources 42 and 44 to emit light simultaneously, and the G light and R light are scanned across the fundus of the subject's eye 12 by the wide-angle optical system 80. The G light reflected from the fundus of the subject's eye 12 is detected by the G light detection element 72, and image data of a second fundus image (G-color fundus image) is generated by the CPU 22 of the ophthalmic apparatus 110. Similarly, the R light reflected from the fundus of the subject's eye 12 is detected by the R light detection element 74, and image data of a first fundus image (R-color fundus image) is generated by the CPU 22 of the ophthalmic apparatus 110. Furthermore, when IR light is irradiated, the IR light reflected from the fundus of the subject's eye 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 apparatus 110.

[0022] The eye is structured such that the vitreous body is covered by multiple layers with different structures. These multiple layers, from the innermost on the vitreous body side to the outermost, include the retina, choroid, and sclera. R light passes through the retina and reaches the choroid. Therefore, the first fundus image (R-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, G light only reaches the retina. Therefore, the second fundus image (G-color fundus image) contains information about the blood vessels present in the retina (retinal blood vessels).

[0023] The CPU 22 of the ophthalmologic apparatus 110 mixes the first fundus image (red fundus image) and the second fundus image (green fundus image) at a predetermined ratio to display a color fundus image on the display 32. Note that instead of the color fundus image, the first fundus image (red fundus image), the second fundus image (green fundus image), or an IR fundus image may be displayed.

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

[0025] In this way, the fundus of the test eye 12 is photographed simultaneously using G light and R light, so that 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 positions on the fundus.

[0026] The axial length measuring device 120 in FIG. 1 has two modes, a first mode and a second mode, for measuring the axial length of the subject's eye 12, which is the length in the axial direction (Z direction). In the first mode, light from a light source (not shown) is guided to the subject's eye 12, and then interference light between reflected light from the fundus and reflected light from the cornea is received, and the axial length is measured based on an interference signal indicating the received interference light. In the second mode, ultrasound (not shown) is used to measure the axial length. The axial length measuring device 120 transmits the axial length measured in the first mode or the second mode to the management server 140. The axial length may be measured in 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 is stored as one of the patient data in the management server 140 as patient information, and is also used in fundus image analysis.

[0028] Next, the configuration of the management server 140 will be described with reference to Fig. 3. As shown in Fig. 3, the management server 140 includes a control unit 160 and a display / operation unit 170. The control unit 160 includes a computer including a CPU 162, a memory 164 which is a storage device, and a communication interface (I / F) 166. An image processing program is stored in the memory 164. The display / operation unit 170 is a graphic user interface which displays images and accepts various instructions, and includes 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, and therefore a description thereof will be omitted.

[0030] Next, various functions realized by the CPU 162 of the management server 140 executing the image processing program will be described with reference to Fig. 4. The image processing program has an image processing function, a display control function, and a processing function. 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 Fig. 4.

[0031] Next, the image processing by the management server 140 will be described in detail with reference to Fig. 5. The CPU 162 of the management server 140 executes an image processing program to realize the image processing (image processing method) shown in the flowchart of Fig. 5.

[0032] The image processing program is executed when the management server 140 receives a fundus image from the ophthalmologic apparatus 110 and generates a choroidal blood vessel image based on the fundus image.

[0033] The choroidal blood vessel image is generated as follows: The image processing unit 182 of the management server 140 extracts retinal blood vessels from the second fundus image (green fundus image) by applying black hat filtering to the second fundus image. Next, the image processing unit 182 removes the retinal blood vessels from the first fundus image (red fundus image) by inpainting using the retinal blood vessels extracted from the second fundus image (green fundus image). That is, the image processing unit 182 paints the retinal blood vessel structure of the first fundus image (red fundus image) with the same value as the surrounding pixels using the position information of the retinal blood vessels extracted from the second fundus image (green fundus image). The image processing unit 182 then performs adaptive histogram equalization (Contrast Limited Adaptive Histograph Equalization) on the image data of the first fundus image (red fundus image) from which the retinal blood vessels have been removed, thereby enhancing the choroidal blood vessels in the first fundus image (red fundus image). This produces the choroidal vessel image shown in Figure 6. The generated choroidal vessel image is stored in memory 164. Furthermore, although the choroidal blood vessel image is generated from the first fundus image (red fundus image) and the second fundus image (green fundus image), the image processing unit 182 may generate the choroidal blood vessel image using the first fundus image (red fundus image) or an IR fundus image captured with IR light. Regarding a method for generating a choroidal fundus image, the disclosure of 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 FIG. 5, the processing unit 186 reads out the choroidal vessel image (see FIG. 6) from the memory 164.

[0035] In step 202, the image processing unit 182 cuts out the fundus region from the choroidal vessel image (removing the eyelids and the like), and performs binarization processing on the fundus region to generate a binarized image (FIG. 7). In step 204, the image processor 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 a first thickness (thickness t3 (μm) or greater) are extracted, a second-thickness blood vessel image in which only blood vessels of a second thickness (thickness t2 (μm) or greater but less than t3 (μm)) are extracted, and a third-thickness blood vessel image in which only blood vessels of a third thickness (thickness t1 (μm) or greater but less than t2 (μm)) are extracted. Here, t1 is 160 (μm), t2 is 320 (μm), and t3 is 480 (μm). Although t1 is set to 160 (μm) and t2 is set to 320 (μm), these values ​​for classifying the thickness of blood vessels are merely examples, and other values ​​may be used for each. The blood vessel size analysis process will be described in detail later.

[0036] In step 206, the display control unit 184 generates three images in which the blood vessel portions of the first thickness blood vessel image are colored red, the blood vessel portions of the second thickness blood vessel image are colored green, and the blood vessel portions of the third thickness blood vessel image are colored blue. These three blood vessel images are then combined to generate a colored choroidal blood vessel image, color-coded by thickness. While the blood vessel portions of the first thickness blood vessel image, the blood vessel portions of the second thickness blood vessel image, and the blood vessel portions of the third thickness blood vessel image are colored red, green, and blue, respectively, they may be different colors.

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

[0038] Next, the choroidal vessel size analysis process in step 204, which is executed by the image processing unit 182 of the management server 140, will be described with reference to FIG. In step 212, the image processing unit 182 performs a first contraction process on the generated binarized image (see FIG. 7). FIG. 9A is a diagram showing a schematic representation of a portion of choroidal blood vessels, showing blood vessels 242A, 244A, and 246A of three different thicknesses—a first thickness (seven pixels), a second thickness (five pixels), and a third thickness (three pixels)—and two white spots representing noise 241 and 243 each having a size of one pixel. When a first contraction process (changing the pixel color from white to black) is performed on the image in FIG. 9A, which contracts the white portion by three pixels from the edge of the white portion, a portion 242B of the blood vessel 242A of the first thickness remains white, and the other white portions disappear, as shown in FIG. 9B. Next, in step 214, the image processing unit 182 performs a first expansion process on the binarized image (FIG. 9B) that has been subjected to the first contraction process. In the first dilation process, white pixels are expanded three pixels outward from the white portion (changing the pixel color from black to white). This process reproduces only the first thickness blood vessel 242A, as shown in Fig. 9C. Then, in step 216, the image processor 182 applies red to the first thickness blood vessel 242A, thereby generating a red first thickness blood vessel image BG1 from which noise 241 and 243 have been removed, as shown in Fig. 9D.

[0039] In step 218, the image processing unit 182 performs a second contraction process on the generated binarized image (see FIG. 7). When the second contraction process (changing the pixel color from white to black) is performed on FIG. 9A, which contracts two pixels from the edge of the white portion, portions 242C and 244C of the first-thickness blood vessel 242A and the second-thickness blood vessel 244A remain white, and the other white portions disappear, as shown in FIG. 9E. Next, in step 220, the image processing unit 182 performs a second expansion process on the binarized image (FIG. 9E) that has been subjected to the second contraction process. In the second expansion process, white pixels are expanded by two pixels outward from the white portion. This process reproduces only the first-thickness blood vessel 242A and the second-thickness blood vessel 244A, as shown in FIG. 9F. Then, in step 222, the image processing unit 182 takes the difference between the binary image after the second expansion process (Figure 9F) and the binary image after the first expansion process (Figure 9C), and applies green color to the remaining part, thereby generating a noise-free, green second-thickness blood vessel image BG2 shown in Figure 9G.

[0040] In step 224, the image processing unit 182 performs a third contraction process on the generated binarized image (see FIG. 7). When the third contraction process (changing the pixel color from white to black) is performed on FIG. 9A, which contracts one pixel from the edge of the white portion, as shown in FIG. 9H, the first thickness blood vessel 242A, the second thickness blood vessel 244A, and portions 242D, 244D, and 246D of the third thickness blood vessel 246A, as well as some noise, remain in white, while the other white portions disappear. Next, in step 226, the image processing unit 182 performs a third expansion process on the binarized image (FIG. 9H) that has undergone the third contraction process. In the third expansion process, white pixels are expanded one pixel outward from the white portion. This process reproduces the first thickness blood vessel, the second thickness blood vessel, and the third thickness blood vessel, as shown in FIG. 9I. Then, in step 228, the difference between the binary image after the third expansion process (Figure 9I) and the binary image after the second expansion process (Figure 9F) is taken, and the remaining part is colored blue, thereby generating a noise-removed, blue third thickness blood vessel image BG3 shown in Figure 9J.

[0041] In step 230, the image processing unit 182 extracts the positions of blood vessels of the first thickness from the first thickness blood vessel image BG1, extracts the positions of blood vessels of the second thickness from the second thickness blood vessel image BG2, and extracts the positions of blood vessels of the third thickness from the third thickness blood vessel image BG3, and creates information that combines thickness information and blood vessel position information.

[0042] In step 232, the image processing unit 182 stores the combined information of the thickness information and the blood vessel position information, as well as the first thickness blood vessel image BG1, the second thickness blood vessel image BG2, and the third thickness blood vessel image BG3 in the memory 164. Then, the process proceeds to step 206 in FIG.

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

[0044] First, as described above, image data of fundus images (first fundus image (red-colored fundus image) and second fundus image (green-colored fundus image)) are transmitted from the ophthalmologic apparatus 110 to the management server 140, and the management server 140 has the image data of the fundus images (first fundus image (red-colored fundus image) and second fundus image (green-colored fundus image)). The management server 140 has data of each choroidal blood vessel and a color associated with each choroidal blood vessel according to the thickness of the choroidal blood vessel.

[0045] Furthermore, when the fundus of the patient is photographed, the patient's personal information is input to the ophthalmologic apparatus 110. The personal information includes the patient's ID, name, age, eyesight, etc. Furthermore, when the fundus of the patient is photographed, information indicating whether the eye whose fundus is being photographed is the right eye or the left eye is also input. Furthermore, when the fundus of the patient is photographed, the date and time of photographing is also input. The ophthalmologic apparatus 110 transmits data on the personal information, information on the right eye and the left eye, and the date and time of photographing to the management server 140. The management server 140 has data on the personal information, information on the right eye and the left eye, and the date and time of photographing. The management server 140 has data on the axial length.

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

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

[0048] Here, we will explain the display screen 300 of the choroidal vessel analysis mode shown in Fig. 10. As shown in Fig. 10, the display screen 300 of the choroidal vessel analysis mode has a personal information display field 302 that displays the patient's personal information, an image display field 320, and a choroidal analysis tool display field 330.

[0049] The personal information display field 302 has a patient ID display field 304, a patient name display field 306, an age display field 308, an axial length display field 310, a visual acuity display field 312, and a patient selection icon 314. Each piece of information is displayed in the patient ID display field 304, the patient name display field 306, the age display field 308, the axial length display field 310, and the visual acuity display field 312. 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 allowed to select a patient to be analyzed.

[0050] The image display field 320 has photographing date display fields 322N1 to 322N3, a right eye information display field 324R, a left eye information display field 324L, an RG image display field 326, and a choroidal blood vessel image display field 328. The photographing date display fields 322N1 to 322N3 correspond to the photographing dates of January 1, 2016, January 1, 2017, and January 1, 2018, respectively. The RG image is an image obtained by combining the first fundus image (R-color fundus image) and the second fundus image (G-color fundus image) at a predetermined ratio (for example, 1:1) of the size of each pixel value.

[0051] The choroid analysis tool display field 330 is a field displaying icons for selecting multiple choroidal analyses. It includes a vortex vein location icon 332, a symmetry icon 334, a blood vessel diameter icon 336, a vortex vein and macula / optic disc icon 338, and a choroid analysis report icon 340. The vortex vein location icon 332 indicates that the analysis results of the vortex vein location are to be displayed. The symmetry icon 334 indicates that the analysis results of the symmetry of the choroidal blood vessels in the fundus are to be displayed. The blood vessel diameter icon 336 indicates that the analysis results of the diameter of the choroidal blood vessels are to be displayed. The vortex vein and macula / optic disc icon 338 indicates that the analysis results of the positions between the vortex vein, macula, and optic disc are to be displayed. The choroid analysis report icon 340 indicates that the choroid analysis report is to 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) is displayed with an RG image and a choroid image taken on the day corresponding to the shooting date display field 322N3 clicked among the shooting date display fields 322N1 to 322N3.

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

[0054] As shown in FIG. 11, the vascular diameter display screen 320a includes a colored vascular diameter image display field 352 that displays a colored vascular diameter image, an enlarged image display field 354 that displays an enlarged image of a portion of the colored vascular diameter image, and a reduced choroidal vascular image display field 356 that displays a reduced choroidal vascular image.

[0055] When an area, for example, a rectangular area as shown in FIG. 11 , is specified in a reduced choroidal vessel image display field 356 using a GUI (Graphical User Interface, hereinafter referred to as GUI), the image viewer 150 displays a rectangular frame 353 at the corresponding position in a colored vessel diameter image display field 352, and also displays an enlarged image of the specified area in an enlarged image display field 354.

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

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

[0058] When the thickness 1 icon 362 is clicked, only the first thickness blood vessels displayed in red are displayed as a first thickness blood vessel image in the colored blood vessel diameter image display field 352. When the thickness 2 icon 364 is clicked, only the second thickness blood vessels displayed in green are displayed as a second thickness blood vessel image in the colored blood vessel diameter image display field 352. When the thickness 3 icon 366 is clicked, only the third thickness blood vessels displayed in blue are displayed as a third thickness blood vessel image in the colored blood vessel diameter image display field 352.

[0059] The display screen of the image viewer 150, which will be described later, displays icons and buttons for instructing the generation of an image, which will be described later. When a user of the image viewer 150 (such as an ophthalmologist) clicks on an icon or the like, the image viewer 150 transmits an instruction signal corresponding to the clicked icon or the like 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 transmits image data of the generated image to the image viewer 150. Upon receiving 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 in the management server 140 is performed by a display screen generation program running on the CPU 162.

[0060] Next, a second display mode of the display screen of the choroidal vessel analysis mode displayed on the image viewer 150 will be described. As in the first display mode, the image viewer 150 displays the display screen 300 of the choroidal vessel analysis mode shown in FIG. 10 on the display 172 of the image viewer 150. When the vascular diameter icon 336 in the choroidal analysis tool display field 330 of FIG. 10 is clicked, the display screen changes to one displaying the vascular diameter shown in FIG. 12 (the image display field 320 of FIG. 10 changes to the vascular diameter display screen 320b of FIG. 12). In the second display mode, the same reference numerals are used to denote the display contents as in the first display mode, and their description will be omitted.

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

[0062] Vortex veins (VV) are the outflow routes for blood flowing into the choroid, and there are four to six of them located near the posterior pole of the equator of the eye. The location of the VVs is calculated based on the direction of the choroidal blood vessels.

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

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

[0065] The image processing unit 182 detects the running direction of each choroidal blood vessel (blood vessel running direction) in the choroidal blood vessel image. Specifically, first, the image processing unit 182 performs the following process for each pixel in the choroidal blood vessel image. That is, the image processing unit 182 sets a region (cell) centered on the pixel for that pixel, and creates a histogram of the brightness gradient direction for each pixel in the cell. The brightness gradient direction is expressed, for example, as an angle between 0 degrees and less than 180 degrees. 0 degrees is defined as the direction of a straight line (horizontal line). To create a histogram with nine bins (each bin has a 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, the image processing unit 182 counts the number of pixels in the cell of the gradient direction corresponding to each bin. The width of one bin in the histogram corresponds to 20 degrees. The 0-degree bin contains the number of pixels (count value) in the cell with a gradient direction between 0 and 10 degrees and between 170 and 180 degrees. The 20-degree bin contains the number of pixels (count value) in the cell with a gradient direction between 10 and 30 degrees. Similarly, count values ​​are set for the 40-degree, 60-degree, 80-degree, 100-degree, 120-degree, 140-degree, and 160-degree bins. Since the histogram has nine bins, the vascular direction of a pixel is defined as one of nine different directions. Note that the resolution of the vascular direction can be increased by narrowing the bin width and increasing the number of bins. The count values ​​in each bin (the vertical axis of the histogram) are normalized, and a histogram for the analysis point is created. 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 in each cell. This gradient direction corresponds to the blood vessel running direction. The gradient direction with the lowest count is determined to be the blood vessel running direction for the following reason: the brightness gradient is small in the blood vessel running direction, 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 blood vessel running direction is small. Through the above processing, the blood vessel running direction for each pixel of the choroidal blood vessel image is detected.

[0066] The image processing unit 182 sets the initial positions of M (a natural number) × N (a natural number) (= L) virtual particles. Specifically, the image processing unit 182 sets a total of L initial positions, M vertically and N horizontally, at equal intervals on the choroidal blood vessel image. Using information on the detected blood vessel running direction, the image processing unit 182 performs a process of moving virtual particles on the choroidal blood vessels in the blood vessel running direction, thereby estimating the position of the vortex vein VV. Because the vortex vein VV is a region where multiple choroidal blood vessels converge, this process utilizes the fact that multiple virtual particles arranged on the image ultimately follow the blood 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 process for each of the L positions. That is, the image processing unit 182 acquires the blood vessel running direction of the initial position (any of the L positions), moves the virtual particle a predetermined distance along the acquired blood vessel running direction, acquires the blood vessel running direction again at the moved position, and moves the virtual particle a predetermined distance along the acquired blood vessel running direction. In this way, moving the virtual particle a predetermined distance along the blood vessel running direction is repeated a preset number of times. The above process is performed for all L positions. The point where a certain number or more of virtual particles are gathered at that time is determined to be 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. The VV position information is used to create the display screens of the third embodiment of the choroidal vessel analysis mode shown in Figures 12 to 15 and Figure 22, which will be described later.

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

[0069] In this way, the image viewer 150 receives the data for the display screen 300 shown in FIG. 12 from the management server 140. When the management server 140 executes the display screen data creation processing program shown in FIG. 12 to create the data for the display screen 300 such as that shown in FIG. 12, the management server 140 transmits the data for the display screen 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. The VV position information is used to create the display screens of the third embodiment of the choroidal vessel analysis mode shown in Figures 12 to 15 and Figure 22, which will be described later.

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

[0071] In FIG. 12, when the ALL icon 368 is clicked, images of all sizes of choroidal vessels are displayed in the colored vessel diameter image display field 352 and the enlarged image display field 354. In this state, for example, when the size 1 icon 362 is clicked, the display contents of the colored vessel diameter image display field 352 and the enlarged image display field 354 change to images of only vessels of the first size, as shown in the vessel diameter image display field 372R and the enlarged image display field 374R in FIG. 13. Because red is associated with vessels of the first size, vessels of the first size are displayed in red. When the size 2 icon 364 is clicked, the display contents of the colored vessel diameter image display field 352 and the enlarged image display field 354 change to images of only vessels of the second size, as shown in the vessel diameter image display field 372B and the enlarged image display field 374B in FIG. 14. Because blue is associated with vessels of the second size, vessels of the second size are displayed in green. When the thickness 3 icon 366 is clicked, the display contents of the colored blood vessel diameter image display field 352 and the enlarged image display field 354 become images of only blood vessels of the third thickness, as shown in a blood vessel diameter image display field 372G and an enlarged image display field 374G in Fig. 15. Since green is associated with blood vessels of the third thickness, blood vessels of the third thickness are displayed in blue.

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

[0073] Next, a third display mode of the display screen in the choroidal vessel analysis mode will be described. In the third display mode, the same parts as in the first display mode are denoted by the same reference numerals, and their description will be omitted.

[0074] As shown in Fig. 22, the blood vessel diameter display screen 320c displays a choroidal vessel image in which a VV position 376 is superimposed on the choroidal vessel image in the reduced choroidal vessel image display field 356. In Fig. 22, a circular frame of a predetermined radius centered on the VV position is displayed on the choroidal vessel image. In Fig. 12, three VV positions are shown by circular frames. The blood vessel diameter display screen 320c further has display fields for displaying a VV position enlarged image 420, a VV thinned image 422, a VV blood vessel diameter directionality map 424, and a blood vessel diameter histogram 426, and a thickness analysis plot icon 380. The thickness analysis plot icon 380 is a button for switching the display content to the display screen of Fig. 23, which will be described later. When a VV position is specified in the GUI, a rectangular frame 377 is displayed in the reduced choroidal vessel image display field 356 of the choroidal vessel image, surrounding the circular frame of the specified VV position. Then, a VV position enlarged image 420 of the rectangular frame 377 is displayed in the display field. The VV position enlarged image 420 is created and displayed based on data obtained by analyzing in detail the choroidal vessels around the specified VV. A similarly created VV vessel diameter directionality map 424 is displayed in the VV vessel diameter directionality map display field.

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

[0076] In step 1232 of FIG. 16, the processing unit 186 reads out the choroidal vessel image (see FIG. 6), and in step 1234, the image processing unit 182 executes 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 from the choroidal vessel image.

[0078] In step 1238, the image processing unit 182 generates a binary image from the image of the extracted predetermined region. In step 1240, the image processing unit 182 sets a circle 404 of a predetermined radius centered on the VV position 402 in the generated binary image, as shown in FIG. 17. 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 be set based on the blood vessel running pattern around the VV position. In step 1242, image processing unit 182 performs thinning processing on the binary image. In step 1244, image processing unit 182 detects intersection 406 between circle 404 and thin line, as shown in Fig. 18. In step 1246, image processing unit 182 generates a distance image from the binary image, as shown in Fig. 19. The distance image is an image in which the brightness gradually increases from the edge of a line toward the center depending on the thickness of the line in the binary image, and the brightness at the center of the line increases as the thickness of the line increases.

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

[0080] 20, the display control unit 184 creates a graph in which the horizontal axis represents the angle from a predetermined position (for example, the top end) of the circle where the intersection 406 is located, and the vertical axis represents the blood vessel diameter at the intersection 406. From this graph, the thickness and direction of the blood vessel running from the VV position 402 can be visualized. In step 1254, the display control unit 184 tally the blood vessel diameters at each intersection 406 and create a histogram of the number of choroidal vessels and their diameters, with 6 bins and a bin width of 200 μm, as shown in Fig. 21. From this histogram, the distribution of the blood vessel diameters connected to the VV can be visualized, and the amount of blood flowing into the VV can be estimated.

[0081] In step 1256, the processing unit 186 stores the following data in the memory 164: the VV position, the binarized image, the circle 404 of a predetermined radius centered on the VV position 402, the intersections 406 between the circle 404 and the thin line, the distance image, the brightness values ​​at the positions corresponding to the intersections 406, the blood vessel diameters converted from the brightness values ​​at the intersections 406, the graph of the angle and blood vessel diameter, and the histogram of the number of choroidal blood vessels and blood vessel diameters.

[0082] Next, a fourth display mode of the display screen in choroidal vessel analysis mode, which is displayed in the image viewer 150 when the thickness analysis plot icon 380 in Fig. 22 is clicked, will be described. When the thickness analysis plot icon 380 in Fig. 22 is clicked, the display screen changes to one that combines the vascular diameter analysis results and VV position analysis results shown in Fig. 23 (image display field 320c in Fig. 22 changes to image display field 320d in Fig. 23). In the fourth display mode, parts of the display mode that are the same as those in the first display mode are assigned the same reference numerals, and their description will be omitted.

[0083] Next, the image display field 320d in Fig. 23 will be described. A colored choroidal vessel image 500 with the positions of vortex veins (VV) superimposed is displayed in the center of the image display field 320d. In Fig. 23, four VVs are present 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 of a predetermined radius centered on the VV 520 is superimposed on the choroidal vessel image 500. Similarly, circles 542, 562, and 582 are superimposed on the other VVs.

[0084] Further displayed in the upper left of the image display field 320d are an enlarged circle image 524 and a pie chart 526. The enlarged circle image 524 is an enlarged image of the colored choroidal blood vessel image of the area surrounded by the circle 522. The pie chart 526 shows the percentage of the number of pixels in the blood vessel region of each of a plurality of blood vessels of a plurality of thicknesses, when the total number of pixels in the blood vessel region within the circle 522 is 100. Specifically, for example, the pie chart 526 includes, first, the percentage of the number of pixels in the blood vessel region of a first thickness (480 μm or more), which is a thick blood vessel; second, the percentage of the number of pixels in the blood vessel region of a second medium thickness (320 μm or more to less than 480 μm); and third, the percentage of the number of pixels in the blood vessel region of a third thin thickness (less than 320 μm). Similarly, an enlarged circle image 544 and a pie chart 546 are displayed in the lower left corner of image display field 320d, an enlarged circle image 564 and a pie chart 566 are displayed in the upper right corner of image display field 320d, and an enlarged circle image 584 and a pie chart 586 are displayed in the lower right corner of image display field 320d. Each image displayed in the image display field 320d is created by the image processing unit 182 of the management server 140.

[0085] In the fourth display mode, a user such as an ophthalmologist can comprehensively grasp the positions of all VVs, enlarged images of each VV, and the blood vessel size distribution on the display screen.

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

[0087] Conventionally, the choroidal vascular network has been quantified from OCT measurement data, but it is not possible to grasp the thickness. However, in each of the above-described embodiments, the retinal blood vessels and choroidal blood vessels are separated from the first fundus image (red-colored fundus image) or IR fundus image and the second fundus image (green-colored fundus image), the thickness of the choroidal blood vessels is determined, and the determined thickness is displayed in different colors to visualize the blood vessels. Therefore, the thickness of the choroidal blood vessels can be grasped. Furthermore, the thickness of the choroidal blood vessels around the location of the vortex vein VV can be analyzed and visualized, thereby assisting ophthalmologists in their diagnosis. In the above embodiment, the VV position can be analyzed, and the thickness of the choroidal blood vessels around the VV can be analyzed. In the above embodiment, since position information of each thickness of the choroidal blood vessels is stored, statistical processing can be easily performed. In the above embodiment, a wide fundus region is imaged with an external light irradiation angle of approximately 120 degrees (approximately 200 degrees with the above internal light irradiation angle) from outside the subject's eye 12, making it possible to visualize the choroid of the fundus over a wide range. This makes it 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 the vortex vein VV present near the equator of the eyeball.

[0088] Next, various modifications of the technique of the present disclosure will be described. <First Modification> In each of the above embodiments, a choroidal vascular image is analyzed, but the technology of the present disclosure is not limited to this. For example, a cross-sectional image of the fundus obtained by an OCT-En Face image (a fundus image constructed from 3D OCT data), an image obtained by ICG (indocyanine green) fluorescence angiography, an image obtained by FA (fluorescein angiography), or FAF (fundus autofluorescence, an image obtained by autofluorescence photography) may also be analyzed.

[0089] <Second Modification> In each of the above embodiments, the choroidal blood vessels are displayed by changing the color depending on the thickness, but the technology of the present disclosure is not limited to this, and the choroidal blood vessels may be displayed by changing the brightness value depending on the thickness.

[0090] <Third Modification> In the above embodiment, the management server 140 executes an image processing program in advance, but the technology of the present disclosure is not limited to this. For example, the following may be performed. For example, when the vascular diameter icon 336 is clicked while the display screen 300 of the choroidal vascular analysis mode shown in FIG. 10 is displayed on the display 172 of the image viewer 150, the management server 140 executes the image processing program. Specifically, when the vascular diameter icon 336 is clicked, the image viewer 150 transmits a command to the management server 140. When the management server 140 receives the command, the image processing program may be executed.

[0091] <Fourth Modification> In the above embodiment, an example has been described in which a fundus image with an internal light irradiation angle of approximately 200 degrees is acquired by the ophthalmic apparatus 110. The technology of the present disclosure is not limited to this, and the technology of the present disclosure may also be applied to a fundus image captured by an ophthalmic apparatus with an internal irradiation angle of 100 degrees or less, or to a montage image in which multiple fundus images are combined.

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

[0093] <Sixth Modification> In the above embodiment, the management server 140 executes the image processing program. However, the technology of the present disclosure is not limited to this. For example, the ophthalmic apparatus 110 or the image viewer 150 may execute the image processing program. When the ophthalmic apparatus 110 executes the image processing program, the image processing program is stored in the 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 Modification> In the above embodiment, the ophthalmic system 100 including the ophthalmic apparatus 110, the axial length measuring device 120, the management server 140, and the image viewer 150 has been described as an example. However, the technology of the present disclosure is not limited thereto. For example, as a first example, the axial length measuring device 120 may be omitted, and the ophthalmic apparatus 110 may further have the functions of the axial length measuring device 120. Furthermore, as a second example, the ophthalmic apparatus 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 apparatus 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 the ophthalmic apparatus 110 or the image viewer 150. Furthermore, if the ophthalmic apparatus 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, and it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be changed, without departing from the spirit of the invention. Furthermore, in the above embodiment, an example was given in which data processing is realized by a software configuration using a computer, but the technology of the present disclosure is not limited to this. For example, instead of a software configuration using a computer, data processing may be performed only by a hardware configuration such as an FPGA or an ASIC. Part of the data processing may be performed by a software configuration, and the remaining part may be performed by a hardware configuration.

Claims

1. Detecting the position of a vortex vein from a fundus image in which choroidal blood vessels are visualized, the fundus image being constructed from the OCT data; setting a circle centered on the position of the vortex vein and detecting an intersection of the circle and the choroidal vessel; Analyzing the thickness of the choroidal vessels at the intersections; An image processing method comprising:

2. The step of analyzing the thickness of the choroidal blood vessels includes detecting the positions of the intersection points in the circles and analyzing the relationship between the positions of the intersection points and the thickness of the choroidal blood vessels at the intersection points. The image processing method according to claim 1 .

3. The step of analyzing the thickness of the choroidal vessels includes analyzing a relationship between the number of the choroidal vessels in the circle and the thickness of the choroidal vessels.

3. The image processing method according to claim 1.

4. Detecting the position of a vortex vein from a fundus image in which choroidal blood vessels are visualized, the fundus image being constructed from the OCT data; Analyzing the thickness of the choroidal vessels at a position a predetermined distance away from the position of the vortex vein; An image processing method comprising:

5. Detecting the position of a vortex vein from a fundus image in which choroidal blood vessels are visualized, the fundus image being constructed from the OCT data; A circle is set with the position of the vortex vein as its center, Analyzing the thickness of the choroidal vessels within the circle; Analyzing the thickness distribution of the choroidal blood vessels within the circle; detecting an intersection of the circle with the choroidal vessels; Analyzing the thickness of the choroidal vessels at the intersections; An image processing method comprising:

6. The step of analyzing the thickness of the choroidal blood vessels includes identifying the thickness based on the brightness value of the intersection point. The image processing method according to any one of claims 1 to 3.

7. and setting the circle includes determining a radius of the circle based on a blood vessel pattern around the location of the vortex vein. The image processing method according to any one of claims 1 to 3.

8. The step of detecting the position of the vortex vein includes detecting directions of the choroidal blood vessels, and detecting a point where the directions of the blood vessels converge as the position of the vortex vein. The image processing method according to any one of claims 1 to 7.

9. the step of detecting a position of a vortex vein includes detecting a plurality of positions of the vortex vein. The image processing method according to any one of claims 1 to 8.

10. The fundus image is an image obtained by OCT angiography or an OCT-En Face image. The image processing method according to any one of claims 1 to 9.

11. The step of analyzing the thickness of the choroidal vessels includes creating a display screen showing a relationship between the thickness of the choroidal vessels and the position of the vortex vein. The image processing method according to any one of claims 1 to 9.

12. creating the display screen includes creating a vortex vein position superimposed display image in which the vortex vein position is superimposed on the fundus image; The image processing method according to claim 11.

13. the step of analyzing the thickness of the choroidal blood vessels includes creating a superimposed display image in which the circle is superimposed on the fundus image.

6. The image processing method according to claim 1, 2, or 5.

14. creating the display screen includes outputting image data; The image processing method according to claim 11.

15. A program for causing a computer to execute the image processing method according to any one of claims 1 to 14.

16. a storage device that stores a program for causing the processing device to execute the image processing method; a processing device that executes the image processing method by executing a program stored in the storage device, The image processing method is an image processing method according to any one of claims 1 to 14. Image processing device.

Images