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 disclosed herein 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] The image processing method of the first aspect of the technology disclosed herein includes the steps of: detecting the position of a vortex vein from a fundus image in which choroidal vessels are visualized; extracting a first thickness choroidal vessel having a first thickness and a second thickness choroidal vessel 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 vessel is displayed in a first display method and the second thickness choroidal vessel is displayed in a second display method different from the first display method.

[0004] The image processing method of the second aspect of the technology disclosed herein includes the steps of detecting a vortex vein position from a fundus image in which choroidal blood vessels are visualized, detecting an intersection between a circle centered on the vortex vein position and the choroidal blood vessel, identifying the thickness of the choroidal blood vessel at the intersection, and creating a graph showing the relationship with the thickness of the choroidal blood vessel at the intersection.

[0005] The image processing method of the third aspect of the technology disclosed herein includes the steps of detecting a vortex vein position from a fundus image in which choroidal blood vessels are visualized, detecting an intersection between a circle centered on the vortex vein position and the choroidal blood vessel, identifying a vascular diameter of the choroidal blood vessel at the intersection, and creating a histogram of the vascular diameter and the number of the 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 of a fifth aspect of the technology disclosed herein is an image processing device comprising a memory 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 memory device, wherein the image processing method is any of the image processing methods of the first to third aspects.

[0008] The image processing method of the sixth aspect of the technology disclosed herein includes the steps of detecting a vortex vein position 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 vortex vein position and the thickness of the choroidal blood vessels. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a block diagram of an ophthalmology system 100. [Diagram 2] 1 is a schematic diagram showing the overall configuration of an ophthalmic apparatus 110. FIG. [Diagram 3] 2 is a block diagram of the electrical configuration of the management server 140. FIG. [Figure 4] 2 is a functional block diagram of a CPU 162 of the management server 140. FIG. [Diagram 5] 4 is a flowchart of an image processing program according to the first embodiment. [Figure 6] FIG. 13 is a diagram showing an image of choroidal blood vessels. [Figure 7] FIG. 13 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. 11 is an explanatory diagram for explaining a choroidal blood vessel thickness analysis process. [Figure 9B]FIG. 11 is an explanatory diagram for explaining a choroidal blood vessel thickness analysis process. [Figure 9C] FIG. 11 is an explanatory diagram for explaining a choroidal blood vessel thickness analysis process. [Figure 9D] FIG. 11 is an explanatory diagram for explaining a choroidal blood vessel thickness analysis process. [Figure 9E] FIG. 11 is an explanatory diagram for explaining a choroidal blood vessel thickness analysis process. [Figure 9F] FIG. 11 is an explanatory diagram for explaining a choroidal blood vessel thickness analysis process. [Figure 9G] FIG. 11 is an explanatory diagram for explaining a choroidal blood vessel thickness analysis process. [Figure 9H] FIG. 11 is an explanatory diagram for explaining a choroidal blood vessel thickness analysis process. [Figure 9I] FIG. 11 is an explanatory diagram for explaining a choroidal blood vessel thickness analysis process. [Figure 9J] FIG. 11 is an explanatory diagram for explaining a choroidal blood vessel thickness analysis process. [Figure 10] FIG. 3 is a diagram showing a display screen 300 in a choroidal blood 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. 13 is a diagram showing a display screen 300 in which a VV position is superimposed on the display screen displaying the blood vessel diameter. [Figure 13] FIG. 13 shows a display screen 300 that is displayed when a thickness 1 icon 362 is clicked. [Figure 14] FIG. 13 shows a display screen 300 that is displayed when a thickness 2 icon 364 is clicked. [Figure 15] FIG. 13 shows a display screen 300 that is displayed when a thickness 3 icon 366 is clicked. [Figure 16] 13 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 the VV position 402 as its center in a binarized image generated from a choroidal blood vessel image. [Figure 18] This is a diagram showing an intersection 406 between a circle 404 and a thin line that has been detected. [Figure 19] FIG. 13 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 blood vessels. [Figure 22] FIG. 13 is a diagram showing a display screen displaying each piece of data on blood vessel diameter. [Diagram 23] FIG. 13 is a diagram showing a display screen combining the results of vascular diameter analysis and VV position analysis. [Figure 24] 13 is a flowchart of an image processing program. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, an embodiment 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 "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 a fundus image. 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 by the ophthalmologic apparatus 110 in association with the patient ID. The image viewer 150 displays the fundus image 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 each other via a network 130.

[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 ophthalmic apparatus 110 will be described with reference to Fig. 2. As shown in Fig. 2, the ophthalmic 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 photographing, 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 light (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 and guide it to 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 and each is guided to one optical path.

[0017] The SLO unit 40 includes a wide-angle optical system 80 that two-dimensionally scans the 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 light other than G light. The SLO unit 40 includes a beam splitter 60 that reflects R light from the light that has transmitted through the beam splitter 58 and transmits light other than R light. The SLO unit 40 includes a beam splitter 62 that reflects IR light from the light that has transmitted through the beam splitter 60. The SLO unit 40 includes a G light detection element 72 that detects G light reflected by the beam splitter 58, an R light detection element 74 that detects R light reflected by the beam splitter 60, and an IR light detection 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 the 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 in the Y direction, and an optical system 86 that includes a slit mirror and an elliptical mirror (not shown) and converts the scanned light into a wide angle. The optical system 86 makes the field of view (FOV) of the fundus larger than that of the conventional technology, and can capture a wider range of fundus area than that of the conventional technology. Specifically, it is possible to capture a wider range of fundus area with an external light irradiation angle of about 120 degrees from the outside of the subject's eye 12 (an internal light irradiation angle of about 200 degrees that can be practically captured by irradiating the fundus of the subject's eye 12 with scanning light, with the center O of the eyeball of the subject's eye 12 as the reference position). 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 of the X-direction scanning device 82 and the Y-direction scanning device 84 may be a two-dimensional scanner composed of a MEMS mirror.

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

[0020] When the ophthalmic apparatus 110 is placed on a horizontal plane, the horizontal direction is defined as the "X direction", the vertical direction to the horizontal plane is defined as the "Y direction", and the direction connecting the center of the pupil of the anterior part 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] The color fundus image is obtained by photographing the fundus of the subject's eye 12 simultaneously 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 over the fundus of the subject's eye 12 by the wide-angle optical system 80. Then, 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 the second fundus image (G color fundus image) is generated by the CPU 22 of the ophthalmic device 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 the first fundus image (R color fundus image) is generated by the CPU 22 of the ophthalmic device 110. In addition, 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 device 110.

[0022] The eye is structured such that the vitreous body is covered by multiple layers with different structures. The multiple layers include, from the innermost on the vitreous body side to the outermost, 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 on 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 on the blood vessels present in the retina (retinal blood vessels).

[0023] The CPU 22 of the ophthalmologic apparatus 110 mixes the first fundus image (R-color fundus image) and the second fundus image (G-color fundus image) at a predetermined ratio, and displays the result as a color fundus image on the display 32. Note that instead of the color fundus image, the first fundus image (R-color fundus image), the second fundus image (G-color fundus image), or the IR fundus image may be displayed.

[0024] The image data of the first fundus image (R-color fundus image), the image data of the second fundus image (G-color fundus image), and the 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 instrument 120 in FIG. 1 has two modes, a first mode and a second mode, for measuring the axial length, which is the 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 then the interference light between the reflected light from the fundus and the 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, the axial length is measured using ultrasound (not shown). The axial length measuring instrument 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 the first mode and the second mode, and 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 piece of 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 similar to 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. By the CPU 162 executing 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, image processing by management server 140 will be described in detail with reference to Fig. 5. Image processing (image processing method) shown in the flowchart of Fig. 5 is realized by CPU 162 of management server 140 executing an image processing program.

[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 (G-color fundus image) by applying black hat filter processing to the second fundus image (G-color fundus image). Next, the image processing unit 182 removes retinal blood vessels from the first fundus image (R-color fundus image) by inpainting processing using the retinal blood vessels extracted from the second fundus image (G-color fundus image). That is, the image processing unit 182 performs processing to paint the retinal blood vessel structure of the first fundus image (R-color fundus image) to the same value as the surrounding pixels using the position information of the retinal blood vessels extracted from the second fundus image (G-color fundus image). Then, the image processing unit 182 enhances the choroidal blood vessels in the first fundus image (R-color fundus image) by applying adaptive histogram equalization processing (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 produces the choroidal vessel image shown in Fig. 6. The generated choroidal vessel image is stored in memory 164. In addition, 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. The disclosure of Japanese Patent Application No. 2018-052246, filed on March 20, 2018, regarding a method for generating a choroidal fundus image, 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 blood vessel image (removing the eyelids and the like), performs binarization processing on the fundus region, and generates a binarized image (FIG. 7). In step 204, the image processor 182 executes a thickness analysis process to analyze the thickness of the choroidal blood vessels that are 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, which are t3 (μm) or more, are extracted, a second thickness blood vessel image in which only blood vessels of a second thickness, which are t2 (μm) or more but less than t3 (μm), are extracted, and a third thickness blood vessel image in which only blood vessels of a third thickness, which are t1 (μm) or more but less than t2 (μm), are extracted. Here, t1 is 160 (μm), t2 is 320 (μm), and t3 is 480 (μm). Although t1 is 160 (μm) and t2 is 320 (μm), the 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 portion of the first thickness blood vessel image is colored red, the blood vessel portion of the second thickness blood vessel image is colored green, and the blood vessel portion of the third thickness blood vessel image is colored blue. Furthermore, these three blood vessel images are combined to generate a colored choroidal blood vessel image colored according to thickness. The blood vessel portion of the first thickness blood vessel image, the blood vessel portion of the second thickness blood vessel image, and the blood vessel portion of the third thickness blood vessel image are colored red, green, and blue, respectively, but 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 thickness 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 processor 182 performs a first contraction process on the generated binary image (see FIG. 7). FIG. 9A is a diagram showing a schematic representation of a part of a choroidal blood vessel, in which blood vessels 242A, 244A, and 246A of three types of thickness, namely, a first thickness (seven pixels), a second thickness (five pixels), and a third thickness (three pixels), and two locations of noise 241 and 243 of one pixel size are displayed in white. When a first contraction process (changing the color of the pixel from white to black) is performed on the edge of the white portion of FIG. 9A, a part 242B of the blood vessel 242A of the first thickness remains in white, and the other white portions disappear, as shown in FIG. 9B. Next, in step 214, the image processor 182 performs a first expansion process on the binary image (FIG. 9B) that has been subjected to the first contraction process. In the first dilation process, a process is performed in which 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 noises 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 binary image (see FIG. 7). When a second contraction process (changing the color of a pixel from white to black) is performed on FIG. 9A, which contracts two pixels from the edge of the white portion, parts 242C and 244C of the first thickness blood vessel 242A and the second thickness blood vessel 244A remain in white, and 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 binary image (FIG. 9E) that has been subjected to the second contraction process. In the second expansion process, a process is performed to expand white pixels 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 binarized image after the second expansion process (Figure 9F) and the binarized image after the first expansion process (Figure 9C), and applies the color green to the remaining part to generate a noise-free, green second thickness blood vessel image BG2 as shown in Figure 9G.

[0040] In step 224, the image processing unit 182 performs a third contraction process on the generated binary image (see FIG. 7). When a third contraction process (changing the color of a pixel from white to black) is performed on FIG. 9A, which contracts one pixel from the edge of the white portion, parts 242D, 244D, and 246D of the first thickness blood vessel 242A, the second thickness blood vessel 244A, and the third thickness blood vessel 246A and parts of noise remain in white, as shown in FIG. 9H, and other white portions disappear. Next, in step 226, the image processing unit 182 performs a third expansion process on the binary image (FIG. 9H) that has been subjected to the third contraction process. In the third expansion process, a process is performed to expand the white pixel by one pixel outward from the white portion. This process reproduces the first thickness blood vessel, the second thickness blood vessel, and the third blood vessel as shown in FIG. 9I. Then, in step 228, the difference is taken between the binary image after the third expansion process (Figure 9I) and the binary image after the second expansion process (Figure 9F), and the remaining part is colored blue, thereby removing noise and generating a blue third thickness blood vessel image BG3 as 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 combining the thickness information and the 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-color fundus image) and second fundus image (green-color fundus image)) are transmitted from the ophthalmic device 110 to the management server 140, and the management server 140 has the image data of the fundus images (first fundus image (red-color fundus image) and second fundus image (green-color 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] When the fundus of the patient is photographed, the patient's personal information is input to the ophthalmologic device 110. The personal information includes the patient's ID, name, age, eyesight, etc. When the fundus of the patient is photographed, information indicating whether the eye whose fundus is to be photographed is the right eye or the left eye is also input. When the fundus of the patient is photographed, the photographing date and time is also input. The ophthalmologic device 110 transmits the personal information, the right eye / left eye information, and the photographing date and time data to the management server 140. The management server 140 has the personal information, the right eye / left eye information, and the photographing date and time data. The management server 140 has the axial length data.

[0046] As described above, the management server 140 has data (content data) to be displayed on the display screen in the choroidal blood 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 in choroidal blood vessel analysis mode to the management server 140 via the image viewer 150. The management server 140, which has received the instruction, transmits data of the display screen in choroidal blood vessel analysis mode to the image viewer 150. The image viewer 150, which has received the data of the display screen in choroidal blood vessel analysis mode, displays a display screen 300 in choroidal blood vessel analysis mode shown in FIG. 10 on the display 172 of the image viewer 150 based on the data of the display screen in choroidal blood vessel analysis mode.

[0048] Here, we will explain the display screen 300 in the choroidal vessel analysis mode shown in Fig. 10. As shown in Fig. 10, the display screen 300 in the choroidal vessel analysis mode has a personal information display field 302 that displays the personal information of a patient, 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 in which icons for selecting a plurality of choroidal analyses are displayed. The field includes a vortex vein position icon 332, a symmetry icon 334, a blood vessel diameter icon 336, a vortex vein-macula / optical disk icon 338, and a choroid analysis report icon 340. The vortex vein position icon 332 indicates that the analysis result of the vortex vein position is to be displayed. The symmetry icon 334 indicates that the analysis result of the symmetry of the choroidal blood vessels of the fundus is to be displayed. The blood vessel diameter icon 336 indicates that the analysis result regarding the diameter of the choroidal blood vessels is to be displayed. The vortex vein-macula / optical disk icon 338 indicates that the analysis result of the position between the vortex vein, the macula, and the optic disk is 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 FIG. 10, the fundus of the right eye of a 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, a first display mode of the display screen of the choroidal blood vessel analysis mode displayed on the image viewer 150 will be described. The image viewer 150 displays a display screen 300 of the choroidal blood vessel analysis mode shown in Fig. 10 on the display 172 of the image viewer 150. When the blood vessel diameter icon 336 in the choroidal analysis tool display field 330 in Fig. 10 is clicked, the display screen is changed to the blood vessel diameter display screen shown in Fig. 11 (the image display field 320 in Fig. 10 is changed to the blood vessel 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 for displaying a colored vascular diameter image, an enlarged image display field 354 for displaying an enlarged image of a portion of the colored vascular diameter image, and a reduced choroidal vessel image display field 356 for displaying a reduced choroidal vessel 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 (Graphic User Interface, hereinafter referred to as GUI), the image viewer 150 displays a rectangular frame 353 at a 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 a first thickness, a second thickness, and a third thickness, 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 for switching the display contents between the colored blood vessel diameter image display field 352 and the reduced choroidal blood vessel image display field 356. When the blood vessel diameter ⇔ choroid icon 370 is clicked in the display state of FIG. 11, a choroidal fundus image is displayed in the colored blood vessel diameter image display field 352, and a reduced colored blood vessel image is displayed in the reduced choroidal blood vessel image display field 356. In FIG. 11, the ALL icon 368 is clicked, and images of choroidal blood vessels of all thicknesses are displayed in each of the colored blood vessel diameter image display field 352 and the enlarged image display field 354. Also, FIG. 11 shows an example in which the blood vessel diameter ⇔ choroid icon 370 is clicked, and the blood vessel diameter image in the colored blood vessel diameter image display field 352 is displayed larger than the choroidal blood vessel image in the choroidal blood vessel image display field 356.

[0058] When the thickness 1 icon 362 is clicked, only the first thickness blood vessel displayed in red is displayed in the 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 vessel displayed in green is displayed in the 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 vessel displayed in blue is displayed in the third thickness blood vessel image in the colored blood vessel diameter image display field 352.

[0059] Icons and buttons for instructing to generate an image, which will be described later, are displayed on a display screen of the image viewer 150, which will be described later. When a user of the image viewer 150 (such as an ophthalmologist) clicks on an icon or the like, an instruction signal corresponding to the clicked icon or the like is transmitted from the image viewer 150 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 the image data from the management server 140, the image viewer 150 displays an image on a 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 in the choroidal blood vessel analysis mode displayed on the image viewer 150 will be described. As in the first display mode, the image viewer 150 displays a display screen 300 in the choroidal blood vessel analysis mode shown in FIG. 10 on the display 172 of the image viewer 150. When the blood vessel diameter icon 336 in the choroidal analysis tool display field 330 in FIG. 10 is clicked, the display screen is changed to one displaying the blood vessel diameter shown in FIG. 12 (the image display field 320 in FIG. 10 is changed to the blood vessel diameter display screen 320b in FIG. 12). In the second display mode, the same reference numerals are used for 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 for a choroidal blood vessel image in which the position of a vortex vein (hereinafter referred to as VV) is superimposed on a reduced choroidal blood vessel image. In the choroidal blood vessel image displayed in the reduced choroidal blood vessel image display field 356, a VV position 376 is displayed in a circular frame. In Fig. 12, three VV positions are shown in circular frames.

[0062] The vortex vein VV is an outflow route for blood flowing into the choroid, and there are four to six of them near the posterior pole of the equator of the eye. The location of the VV is calculated based on the running direction of the choroidal blood vessels.

[0063] The image viewer 150 receives data of 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 of 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 blood 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 in the choroidal blood vessel image (blood vessel running direction). Specifically, first, the image processing unit 182 executes 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 the pixel, and creates a histogram of the gradient direction of brightness for each pixel in the cell. The luminance gradient direction is indicated by, for example, an angle of 0 degrees or more and less than 180 degrees. 0 degrees is defined as the direction of a straight line (horizontal line). The image processing unit 182 counts the number of pixels in a cell in the gradient direction corresponding to each bin to create a histogram having nine bins (each bin has a width of 20 degrees) in which the luminance 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 width of one bin of the histogram corresponds to 20 degrees, and the number of pixels (count value) in the cell with a gradient direction of 0 degrees or more and less than 10 degrees and 170 degrees or more and less than 180 degrees is set in the 0 degree bin. The number of pixels (count value) in the cell with a gradient direction of 10 degrees or more and less than 30 degrees is set in the 20 degree bin. Similarly, the count values ​​of the 40 degree, 60 degree, 80 degree, 100 degree, 120 degree, 140 degree, and 160 degree bins are also set. Since the number of bins in the histogram is 9, the blood vessel running direction of a pixel is defined as one of 9 different directions. Note that the resolution of the blood vessel running direction can be increased by narrowing the bin width and increasing the number of bins. The count value in each bin (vertical axis of the histogram) is 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 smallest 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 smallest count is determined to be the blood vessel running direction for the following reason. The luminance gradient is small in the blood vessel running direction, while the luminance gradient is large in other directions (for example, there is a large difference in luminance between blood vessels and non-blood vessels). Therefore, when a histogram of the luminance gradient for each pixel is created, the count for the blood vessel running direction is small. By the above process, 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 (natural number) × N (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, a process is performed to move virtual particles on the choroidal blood vessel in the blood vessel running direction, thereby estimating the position of the vortex vein VV. Since the vortex vein VV is a region where multiple choroidal blood vessels gather, this process utilizes the fact that multiple virtual particles arranged on the image eventually follow the blood vessels and gather 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 first 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, the predetermined distance movement 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. The VV position information (such as the number of VVs and their coordinates on the choroidal vessel image) is stored in the memory 164. The VV position information is used to create the display screen of the choroidal vessel analysis mode in the third embodiment of FIGS. 12 to 15 and FIG. 22 described later.

[0068] In step 204, the image processing unit 182 executes thickness analysis processing for analyzing the thickness of the choroidal blood vessels that appear in 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, data for the display screen 300 shown in FIG. 12 is transmitted from the management server 140 to the image viewer 150. When the management server 140 executes the display screen data creation processing program shown in FIG. 12 to create 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. The VV position information (such as the number of VVs and their coordinates on the choroidal vessel image) is stored in the memory 164. The VV position information is used to create the display screen of the choroidal vessel analysis mode in the third embodiment of FIGS. 12 to 15 and FIG. 22 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 by the 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 a circular frame surrounding it are superimposed on the enlarged image.

[0071] In FIG. 12, when the ALL icon 368 is clicked, images of all the choroidal vessels of all thicknesses are displayed in the colored vessel diameter image display field 352 and the enlarged image display field 354. In this state, when the thickness 1 icon 362 is clicked, the display contents of the colored vessel diameter image display field 352 and the enlarged image display field 354 become images of only the first thickness vessels, as shown in the vessel diameter image display field 372R and the enlarged image display field 374R in FIG. 13. Since the first thickness vessels are associated with red, the first thickness vessels are displayed in red. When the thickness 2 icon 364 is clicked, the display contents of the colored vessel diameter image display field 352 and the enlarged image display field 354 become images of only the second thickness vessels, as shown in the vessel diameter image display field 372B and the enlarged image display field 374B in FIG. Since the second thickness vessels are associated with blue, the second thickness vessels 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 of the choroidal blood vessel analysis mode displayed on the image viewer 150 will be described. As in the first display mode, the image viewer 150 displays a display screen 300 of the choroidal blood vessel analysis mode shown in Fig. 10 on the display 172 of the image viewer 150. When the blood vessel 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 blood vessel diameter analysis result and the VV position analysis result shown in Fig. 22 (the image display field 320 in Fig. 10 is changed to the blood vessel diameter display screen 320c in Fig. 22).

[0073] Next, a third display mode of the display screen in the choroidal blood 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 the description thereof will be omitted.

[0074] As shown in Fig. 22, the blood vessel diameter display screen 320c displays a choroidal blood vessel image in which a VV position 376 is superimposed on the choroidal blood vessel image in the reduced choroidal blood 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 blood vessel image. In Fig. 12, three VV positions are displayed with 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 contents to the display screen of Fig. 23 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 so as to surround 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. Similarly, a VV vessel diameter directionality map 424 created is displayed in the VV vessel diameter directionality map display field.

[0075] Next, a process (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 vascular 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 blood vessel image (see FIG. 6), and in step 1234, the image processing unit 182 executes the above-mentioned VV position analysis process.

[0077] In step 1236, the image processing unit 182 extracts an image of a predetermined region including the VV position in 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. The radius of the circle 404 may be set between 2 mm and 20 mm depending on the required analysis. 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 according to 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, 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 according to 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 (e.g., the uppermost 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 of the blood vessel running from the VV position 402 and the running direction of the blood vessel can be visualized. In step 1254, the display control unit 184 counts the vascular diameters at each intersection 406 and creates a histogram of the number of choroidal vessels and their vascular diameters, with 6 bins and a bin width of 200 μm, as shown in Fig. 21. From this histogram, the distribution of the diameters of the blood vessels 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 luminance values ​​at the positions corresponding to the intersections 406, the blood vessel diameters converted from the luminance values ​​at the intersections 406, the graph of the angle and the blood vessel diameter, and the histogram of the number of choroidal blood vessels and the blood vessel diameter.

[0082] Next, a fourth display mode of the display screen in choroidal vessel analysis mode, which is displayed on 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 is changed to one that combines the vessel diameter analysis results and the VV position analysis results shown in Fig. 23 (the image display field 320c in Fig. 22 is changed to the image display field 320d in Fig. 23). In the fourth display mode, the same parts as in the first display mode are denoted by 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, in the upper left of the image display field 320d, a circle enlarged display image 524 and a pie chart 526 are displayed. The circle enlarged display image 524 is an enlarged display 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 of the blood vessel region of each of the blood vessels of a plurality of thicknesses when the total number of pixels of the blood vessel region in the circle 522 is 100. Specifically, for example, the pie chart 526 includes, first, the percentage of the number of pixels of 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 of the blood vessel region of a second thickness (320 μm or more to less than 480 μm) which is a medium blood vessel, and third, the percentage of the number of pixels of the blood vessel region of a third thickness (less than 320 μm). Similarly, an enlarged circle display image 544 and a pie chart 546 are displayed in the lower left corner of image display field 320d, an enlarged circle display image 564 and a pie chart 566 are displayed in the upper right corner of image display field 320d, and an enlarged circle display 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 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 is quantified from OCT measurement data, but the thickness cannot be grasped. However, in each embodiment as described above, the retinal blood vessels and the choroidal blood vessels are separated from the first fundus image (red-color fundus image) or the IR fundus image and the second fundus image (green-color fundus image), the thickness of the choroidal blood vessels is determined, and the determined thickness is displayed in different colors to visualize it. Therefore, the thickness of the choroidal blood vessels can be grasped. In addition, the thickness of the choroidal blood vessels around the location of the vortex vein VV is analyzed and visualized, thereby assisting ophthalmologists in making diagnoses. 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 with an external light irradiation angle of about 120 degrees (about 200 degrees with the above internal light irradiation angle) from outside the subject's eye 12 is photographed, so that the choroid of the fundus can be visualized over a wide range. Therefore, not only can the thickness of the choroidal blood vessels in the peripheral part of the fundus be analyzed, but also the thickness of the choroidal blood vessels around the vortex vein VV present near the equator of the eyeball can be analyzed.

[0088] Next, various modified examples of the technique of the present disclosure will be described. <First Modification> In each of the above embodiments, a choroidal blood vessel 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), an FAF (Fundus AutoFluorescence, an image obtained by autofluorescence photography), or the like may 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 luminance value depending on the thickness.

[0090] <Third Modification> In the above embodiment, the management server 140 executes the 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 blood vessel diameter icon 336 is clicked while the display screen 300 of the choroidal blood vessel 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 blood vessel 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 modified example> In the above embodiment, an example has been described in which a fundus image with an internal light irradiation angle of about 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 be applied to a fundus image captured by an ophthalmic apparatus with an internal irradiation angle of 100 degrees or less, or a montage image in which multiple fundus images are combined.

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

[0093] <Sixth Modification> In the above embodiment, the management server 140 executes the image processing program. The technology of the present disclosure is not limited to this. 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 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 Variation> In the above embodiment, the ophthalmic system 100 including the ophthalmic device 110, the axial length measuring device 120, the management server 140, and the image viewer 150 has been described as an example, but 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 device 110 may further have the function of the axial length measuring device 120. Also, as a second example, the ophthalmic device 110 may further have at least one of the functions of the management server 140 and the image viewer 150. For example, when the ophthalmic device 110 has the function of the management server 140, the management server 140 can be omitted. In this case, the image processing program is executed by the ophthalmic device 110 or the image viewer 150. Also, when the ophthalmic device 110 has the function 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 execute the function of the management server 140.

[0095] <Other Modifications> 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 may be added, or the processing order may be changed without departing from the spirit of the invention. In the above embodiment, the 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, the data processing may be performed only by a hardware configuration such as an FPGA or an ASIC. A part of the data processing may be performed by a software configuration, and the remaining processing may be performed by a hardware configuration.

Claims

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

2. The step of analyzing the thickness of the choroidal blood vessel includes detecting the position of the intersection point in the circle, and analyzing the relationship between the position of the intersection point and the thickness of the choroidal blood vessel at the intersection point. The image processing method according to claim 1 .

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

3. The image processing method according to claim 1.

4. Detecting a vortex vein position 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 blood vessels at a position a predetermined distance away from the vortex vein position; An image processing method comprising:

5. Detecting a vortex vein position 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 a center at the position of the vortex vein, Analyzing the thickness of the choroidal vessels within the circle; Analyzing a thickness distribution of the choroidal blood vessels within the circle; detecting an intersection of the circle with the choroidal vessel; Analyzing the thickness of the choroidal vessel at the intersection; An image processing method comprising:

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

7. and 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 blood vessels in the choroidal blood vessels, and detecting a point where the directions of 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 vortex vein position includes detecting a plurality of the vortex vein positions. 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 vessel includes creating a superimposed display image in which the circle is superimposed on the fundus image. 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