JP6860884B2 - Image processing equipment, fundus imaging system, image processing method, and program - Google Patents

Description

The present invention relates to an image processing apparatus, a fundus imaging system, an image processing method, and a program.
The present application claims priority based on Japanese Patent Application No. 2016-213815 filed in Japan on October 31, 2016, the contents of which are incorporated herein by reference.

An apparatus (hereinafter referred to as an OCT imaging apparatus) for imaging a tomographic image of the fundus using OCT (Optical Coherence Tomography) is known. From the image captured by the OCT imaging device (hereinafter referred to as OCT image), a high-intensity portion called Hyperreflective foci (hereinafter referred to as HRF) may be observed. This HRF is said to represent lipoproteins and macrophages. In recent years, academic reports have been made that there is a relationship between the number of HRF observed from OCT images of the eyeballs of patients suffering from diabetic retinopathy and the visual function of the patients.

Japanese Unexamined Patent Publication No. 2015-160105

Yabusaki, Katsumi, Joshua D. Hutcheson, Payal Vyas, Sergio Bertazzo, Simon C. Body, Masanori Aikawa, and Elena Aikawa. 2016. “Quantification of Calcified Particles in Human Valve Tissue Reveals Asymmetry of Calcific Aortic Valve Disease Development.” Frontiers in Cardiovascular Medicine 3 (1): 44.doi: 10.3389 / fcvm.2016.00044. Http://dx.doi.org/10.3389/fcvm.2016.00044.

However, in the conventional technique, although doctors and the like recognize HRF from OCT images, it is difficult to detect HRF by image processing.

The present invention has been made in consideration of such circumstances, and is an image processing device, a fundus imaging system, which can detect an event occurring in the eyeball (retina) such as HRF by image processing from an OCT image. One of the purposes is to provide an image processing method and a program.

One aspect of the present invention that solves the above problem is generated by irradiating the eyeball with light by the optical interference tomography method, and the resolution in the first direction is compared with the resolution in the second direction orthogonal to the first direction. A plurality of high optical interference tomographic images, which are obtained by an acquisition unit for acquiring a plurality of optical interference tomographic images arranged in a third direction orthogonal to each of the first direction and the second direction, and the acquisition unit. In a virtual three-dimensional image formed by a plurality of acquired optical interference tomographic images, the detection is based on a comparison of pixel values between the detection region and a control region set in the region surrounding the detection region. An image processing device including a determination unit for determining whether or not the region is a predetermined image region in which a predetermined event occurs in the eyeball.

According to the present invention, it is possible to detect an event occurring in the eyeball such as HRF by image processing from an OCT image.

It is a figure which shows an example of the structure of the fundus imaging system 1 including the image processing apparatus 200 in 1st Embodiment. It is a figure which shows an example of the structure of the OCT unit 110. It is a figure which shows an example of the structure of the image processing apparatus 200. It is a figure which shows typically the OCT three-dimensional data 212. It is a figure which shows an example of the scanning position information 214. It is a flowchart which shows an example of a series of processing by a control unit 220. It is a figure for demonstrating the segmentation process. It is a figure for demonstrating the segmentation process. It is a flowchart which shows an example of the extraction process of a high-luminance part. It is a figure for demonstrating an example of the setting method of the control region Rb. It is a figure for demonstrating an example of the setting method of the control region Rb. It is a figure for demonstrating an example of the setting method of the control region Rb. It is a figure for demonstrating another example of the setting method of a control region Rb. It is a figure for demonstrating another example of the setting method of a control region Rb. It is a figure for demonstrating another example of the setting method of a control region Rb. It is a figure which shows an example of the generation method of the image area group GP. It is a figure which shows an example of the generation method of the image area group GP. It is a figure which shows an example of the generation method of the image area group GP. It is a figure which shows another example of the generation method of the image area group GP. It is a figure which shows another example of the generation method of the image area group GP. It is a figure which shows another example of the generation method of the image area group GP. It is a figure which shows an example of the display unit 204 which displayed the image based on the diagnosis result by the diagnosis determination unit 234. It is a figure for demonstrating an example of the method of setting the control region Rb by providing the gap with the detection region Ra. It is a figure which shows an example of the detection result of the high-luminance part when the gap is not provided between the detection area Ra and the control area Rb. It is a figure which shows an example of the detection result of the high-luminance part when the gap is provided between the detection area Ra and the control area Rb. It is a figure which shows an example of the variation of the setting method of the control region Rb when providing a gap. It is a figure which shows an example of the variation of the setting method of the control region Rb when providing a gap. It is a figure which shows an example of the variation of the setting method of the control region Rb when providing a gap. It is a figure which shows an example of the variation of the setting method of the control region Rb when providing a gap. It is a figure which shows an example of the variation of the setting method of the control region Rb when providing a gap. It is a figure which shows an example of the hardware composition of the image processing apparatus 200 of an embodiment.

Hereinafter, embodiments of the image processing apparatus, fundus imaging system, image processing method, and program of the present invention will be described with reference to the drawings.

(First Embodiment)
[overall structure]
FIG. 1 is a diagram showing an example of a configuration of a fundus imaging system 1 including an image processing device 200 according to the first embodiment. The fundus imaging system 1 includes, for example, an OCT imaging device (optical coherence tomography imaging device) 100 and an image processing device 200. The OCT imaging device 100 in the present embodiment irradiates the eyeball E of a human or the like with light, and measures the interference light in which the reflected light of the light and a part of the irradiated light interfere with each other to measure the interference light inside the eyeball E. It is a device that measures displacement. As a result, for example, an OCT image IM in which the fundus Er including the retina is projected is acquired. In the OCT imaging apparatus 100 of the present embodiment, the resolution of the eyeball E in the depth direction (z direction in the figure) is higher than the resolution in the direction orthogonal to the depth direction (for example, the x direction in the figure). To do. The resolution in the depth direction is, for example, about 2 [μm]. Further, the OCT imaging device 100 in the present embodiment includes Fourier-domain OCT (Fourier-domain OCT) such as Spectral-domain OCT (SD-OCT) and Swept-source OCT (SS-OCT). FD-OCT), but is not limited to this. The OCT imaging apparatus 100 may employ, for example, a time domain OCT (TD-OCT) or other method.

The image processing device 200 performs various image processing on the OCT image IM generated by the OCT image pickup device 100, and extracts an image region in which a predetermined event occurs in the eyeball E from the OCT image IM. The predetermined event is, for example, HRF. For example, the image processing device 200 extracts a high-brightness portion indicating HRF from the OCT image IM.

[Configuration of OCT imaging device]
Hereinafter, each device in the fundus imaging system 1 will be described. As shown in FIG. 1, the OCT imaging device 100 includes, for example, an OCT unit 110, an illumination optical system 120, and an imaging optical system 130. The OCT unit 110 irradiates light and causes the reflected light and the irradiation light to interfere with each other to generate an OCT image IM. The OCT unit 110 and the imaging optical system 130 are connected to each other by, for example, an optical fiber Fa. The irradiation light emitted by the OCT unit 110 is guided to the imaging optical system 130 via the optical fiber Fa. Further, the irradiation light emitted by the OCT unit 110 is guided to the imaging optical system 130 via the optical fiber Fa.

FIG. 2 is a diagram showing an example of the configuration of the OCT unit 110. As shown in the illustrated example, the OCT unit 110 includes a light source 111, a signal detection unit 112, an optical coupler 113, an optical fiber 113a to 113d, a reference optical collimator 114 and 117, a glass block 115, and a filter 116. And a reference mirror 118.

The light source 111 irradiates, for example, irradiation light (probe light) having a wavelength of near infrared rays (for example, about 700 to 1100 nm). The light source 111 may be, for example, a wavelength sweep light source such as an SLD (super luminescent diode) or an ultra-short wave pulse laser.

The irradiation light emitted from the light source 111 guides the inside of the optical fiber 113a to the light guided to the reference light side collimator 114 side by the optical coupler 113 and to the optical fiber Fa side, that is, the imaging optical system 130 side. It is divided into light that is guided. Hereinafter, the light that guides the light to the reference light side collimator 114 side is referred to as "reference light LR", and the light that guides the light to the imaging optical system 130 side is referred to as "measurement light LS".

The reference light LR is guided to the reference light side collimator 114 via the optical fiber 113b, and is changed to parallel light by the reference light side collimator 114, for example. The parallel light then passes through the glass block 115 and the filter 116 and is guided to the reference light side collimator 117. The glass block 115 and the filter 116 are provided to match the optical path lengths of the reference light LR and the measurement light LS, and to match the dispersion characteristics. The parallel light guided by the reference light side collimator 117 is collected by the reference light side collimator 117. The light (reference light) collected by the reference light side collimator 117 is reflected by the reference mirror 118. The reference light reflected by the reference mirror 118 is changed to parallel light by, for example, the reference light side collimator 117, and then the parallel light is collected by the reference light side collimator 114 and guided to the optical coupler 113 via the optical fiber 113b. Be lit. When the OCT imaging device 100 is a time domain OCT, the reference mirror 118 is not fixed, and the reference mirror 118 or another optical system can be driven so as to change the optical path length from the light source 111 to the reference mirror 118. You can keep it.

On the other hand, the measurement light LS is guided to the imaging optical system 130 via the optical fiber 113c and Fa, and is irradiated to the eyeball E. The measurement light LS (reflected light) applied to the eyeball E is reflected by the reflecting surface of the eyeball E (such as the fundus Er) and is incident on the optical fibers 113c and Fa.

The optical coupler 113 guides the reference light LR reflected by the reference mirror 118 and the measurement light LS reflected by the eyeball E to the signal detection unit 112 via, for example, a coaxial optical fiber 113d. The reference light LR and the measurement light LS guided to the optical fiber 113d interfere with each other inside the optical coupler 113. Hereinafter, the reference light LR and the measurement light LS that interfere with each other are referred to as “interference light LC”.

The signal detection unit 112 includes, for example, an interference light side collimator lens 112a, a diffraction grating 112b, an imaging lens 112c, and a light receiving element 112d. The interference light LC guided by the signal detection unit 112 is converted into parallel light via the interference light side collimator lens 112a and then separated by the diffraction grating 112b. The light dispersed by the diffraction grating 112b is imaged on the light receiving surface of the light receiving element 112d by the imaging lens 112c. The light receiving element 112d is, for example, a photodiode sensor such as a CCD (Charge Coupled Device), detects light through the imaging lens 112c, and generates a detection signal according to the detected light. Then, the signal detection unit 112 displays an OCT image (optical interference) showing a fault in the depth direction (z direction in the figure) of the eyeball E based on the detection signals sequentially generated according to the scanning of the irradiation light by the imaging optical system 130. Tomographic image) Generate IM. The OCT image IM is a so-called B-mode image or a B-scan image.

Returning to the description of FIG. The illumination optical system 120 includes, for example, a light source for illumination (not shown) such as a halogen lamp or a xenon lamp, and illuminates the fundus Er by guiding the light emitted from the light source to the fundus Er.

The imaging optical system 130 guides the reflected light reflected by the fundus Er to the OCT unit 110 side via the optical fiber Fa. Further, the imaging optical system 130 guides the eyeball E to the eyeball E while scanning the irradiation light guided from the OCT unit 110 via the optical fiber Fa. For example, the imaging optical system 130 includes a collimator, a galvanometer mirror (not shown), and the like, and the irradiation direction (z direction in the figure) of the irradiation light emitted to the eyeball E is orthogonal to the irradiation direction. Change with respect to the horizontal direction (x direction or y direction in the figure). That is, the imaging optical system 130 scans the irradiation light by the raster scan method. As a result, the irradiation light applied to the eyeball E is scanned in the x-direction and the y-direction.

[Configuration of image processing device]
FIG. 3 is a diagram showing an example of the configuration of the image processing device 200. As shown in the illustrated example, the image processing device 200 includes a communication interface 202, a display unit 204, a storage unit 210, and a control unit 220.

The communication interface 202 communicates with the OCT imaging device 100 by wire or wirelessly, for example. Further, the communication interface 202 may communicate with other devices other than the OCT imaging device 100.

The display unit 204 is, for example, a display device such as an LCD (Liquid Crystal Display) or an organic EL (Electroluminescence) display.

The storage unit 210 is realized by, for example, an HDD (Hard Disc Drive), a flash memory, an EEPROM (Electrically Erasable Programmable Read Only Memory), a ROM (Read Only Memory), a RAM (Random Access Memory), or the like. The storage unit 210 stores, for example, a program referred to by the control unit 220, OCT three-dimensional data 212, scanning position information 214, and the like.

FIG. 4 is a diagram schematically showing OCT three-dimensional data 212. As shown in the figure, the OCT three-dimensional data 212 is composed of a plurality of OCT image IM _n (n is an arbitrary natural number). The z direction of each OCT image IM _j (1 ≦ j ≦ n) represents a direction along the irradiation direction of the irradiation light (optical axis of the irradiation light), and represents the depth direction of the eyeball E. The direction along the irradiation direction of the irradiation light is, for example, a direction that allows an error (angle width) of about several degrees to a dozen degrees with respect to the optical axis of the irradiation light.

Further, the x direction of each OCT image IM _j represents any one direction of the plane orthogonal to the z direction. These OCT images IM _n are arranged in the y direction orthogonal to both the z direction and the x direction. The y direction corresponds to the imaging time t of each OCT image IM. That is, each OCT image IM is arranged in order of imaging time. In the present embodiment, since the OCT image IM is imaged by the OCT image pickup apparatus 100 whose resolution in the depth direction (z direction) is higher than the resolution in the other directions, the resolution of each OCT image IM _{j in} the z direction is high. , The resolution is finer than the resolution in the x-direction and the y-direction. The example of the illustrated OCT three-dimensional data 212 schematically shows the configuration of a plurality of OCT image IMs, and in reality, for each OCT image IM, the imaging time t and the y direction at the time of imaging thereof. The position information in the above may be treated as a set of associated data. The z direction is an example of the "first direction", the x direction is an example of the "second direction", and the y direction is an example of the "third direction".

FIG. 5 is a diagram showing an example of scanning position information 214. The scanning position information 214 is information regarding a set position of the detection region Ra, which will be described later, and is information in which a high-luminance portion flag is associated with the x-z coordinates in each OCT image IM. The xx coordinates indicate the coordinates of the pixels in each OCT image IM. Further, the high-luminance portion flag is a flag for indicating whether or not the pixel indicated by the x-z coordinate is a high-luminance portion. For example, when it is determined that the image area overlapping with a certain detection area Ra is a high-luminance part, a flag of "1" is given to the coordinates of all the pixels included in the image area, and the image area overlaps with the detection area Ra. If the image area is not a high-brightness area, a "0" flag is added. At this time, it is assumed that the high-luminance region flags of all the pixels included in the OCT image IM are given "0" in advance before determining whether or not they are high-luminance regions. This process is performed every time the position of the detection area is changed (the position is shifted), and finally the pixel to which the flag of "1" is given even once (the pixel whose flag is rewritten from "0" to "1"). Is a pixel that is a high-luminance portion, and the high-luminance portion flag shown in FIG. 5 is “1”. That is, once the high-luminance part flag is changed from "0" to "1", the flag is held in the state of "1".

The control unit 220 includes, for example, an acquisition unit 222, an image preprocessing unit 224, a detection area scanning unit 226, a brightness calculation unit 228, a high brightness portion determination unit 230, a group generation unit 232, and a diagnosis determination unit 234. And a display control unit 236. Some or all of these components are realized by a processor such as a CPU (Central Processing Unit) executing a program stored in the storage unit 210. Further, some or all of the components of the control unit 220 may be realized by hardware such as LSI (Large Scale Integration), ASIC (Application Specific Integrated Circuit), or FPGA (Field-Programmable Gate Array). , May be realized by the collaboration of software and hardware.

Hereinafter, a series of processes by the control unit 220 will be described with reference to a flowchart. FIG. 6 is a flowchart showing an example of a series of processes by the control unit 220. The processing of this flowchart may be repeated at a predetermined cycle.

First, the acquisition unit 222 acquires the OCT image IM from the OCT image pickup apparatus 100 via the communication interface 202 (step S100), and stores the acquired OCT image IM as OCT three-dimensional data 212 in the storage unit 210. Further, when the communication interface 202 communicates with a storage device (for example, a cloud server) that stores the OCT image IM, the acquisition unit 222 may acquire the OCT image IM from this storage device. When the acquisition unit 222 acquires the OCT image IM one by one from the OCT image pickup device 100 or the like, the acquisition unit 222 sequentially acquires the OCT image IM by referring to the imaging time t of each OCT image IM and the position information in the y direction at the time of imaging. The OCT image IMs may be arranged in the y direction. At this time, the acquisition unit 222 may appropriately rearrange the OCT images IM with respect to the y direction so as to be in chronological order, for example.

Next, the image preprocessing unit 224 performs various preprocessing on all the OCT image IMs included in the OCT three-dimensional data 212 (step S102). For example, the pre-processing includes distortion correction processing, noise removal processing, segmentation (layer boundary automatic detection) processing, and processing for dividing and setting a prohibited area and a permitted area. The image preprocessing unit 224 is an example of a “segmentation processing unit”.

The distortion correction process is, for example, a process of correcting the misalignment between the OCT image IMs, and corrects the misalignment in a part or all of the x direction, the y direction, and the z direction.

The noise removal process is, for example, a process of replacing the luminance value of a pixel of interest in the OCT image IM with the average value or the median of the luminance values of the peripheral pixels of the pixel of interest. The noise removal process generally removes noise in terms of reflection intensity, hue, brightness, and saturation instead of the brightness value, but the OCT image usually expresses the strength of the interference signal in shades of gray. Since it is a grayscale image or a pseudo-color image in which the intensity thereof is expressed by a difference in color, noise processing is performed by paying attention to the brightness value or the reflection intensity.

Further, the segmentation process is a process performed in advance to divide the OCT image IM into a prohibited area for prohibiting the setting of the detection area Ra and a permitted area for permitting the setting of the detection area Ra.

7 and 8 are diagrams for explaining the segmentation process. Since the direction of z (axis) in FIG. 7 is the positive direction from the anterior segment of the eye toward the fundus, the side of the eyeball E where the vitreous body exists is the negative side when viewed from the position of the retina, and is inside the eyeball E. It shows a shallower direction. On the contrary, the plus side in the z direction indicates a deeper direction in the eyeball E. For example, the image preprocessing unit 224 detects the line ILM and the line RPE from the OCT image IM. The line ILM is the boundary line with the vitreous body on the inner layer side of the retina, that is, the side closer to the center of the eyeball. The line RPE is the outer layer side of the retina, that is, the boundary line with the choroid. As shown in FIG. 8, the image preprocessing unit 224 sets the line ILM # at a position a certain distance away from the detected line ILM on the plus side in the z direction, and sets the line ILM # on the minus side in the z direction from the detected line RPE. Set the line RPE # at a position separated by a certain distance. The setting of these four lines is the segmentation process. Then, the image preprocessing unit 224 sets the image area between the line ILM # and the line RPE # as the permitted area, and sets the image area other than the permitted area as the prohibited area. Then, the image preprocessing unit 224 sets the detection region and the control region so that all or a part of the detection region and the control region include the permission region. In other words, a part of the detection area or the control area may be set on the prohibited area, and the setting of the detection area or the control area including only the prohibited area is prohibited.

For example, since light-sensitive proteins such as rhodopsin and capillaries are present in the image region between line ILM and line ILM #, or in the image region between line RPE and line RPE, these are detected as high-intensity regions. May be done. That is, it is difficult to distinguish whether or not the high-luminance portion is derived from HRF. Therefore, by setting such a region as a prohibited region in advance by segmentation processing, the region can be excluded from the extraction processing of the high-luminance portion in the subsequent stage, and the processing load can be increased while maintaining the HRF detection accuracy. Can be mitigated.

Next, the control unit 220 performs an extraction process of a high-luminance portion on the preprocessed OCT image (step S104). The details of the extraction process of the high-luminance portion will be described with reference to another flowchart.

FIG. 9 is a flowchart showing an example of the extraction process of the high-luminance portion. The processing of this flowchart corresponds to the processing of step S104 shown in FIG. 6 described above.

First, the detection area scanning unit 226 determines the size of the extraction target (HRF) to be extracted from the OCT image IM according to the resolution of the OCT image IM preprocessed by the image preprocessing unit 224 (step). S200). In the present embodiment, since the OCT image IM is an image in which the resolution in the z direction is larger than the resolution in the x direction, the size of the extraction target is the length in the z direction as compared with the x direction. Is apparently larger.

Next, the detection area scanning unit 226 selects one OCT image IM from a plurality of OCT image IMs preprocessed by the image preprocessing unit 224, and extracts an object for this OCT image IM. The detection area Ra is set according to the size of the OCT image IM, and the set position of the set detection area Ra is shifted by several pixels at a predetermined cycle to scan the detection area Ra with respect to the OCT image IM (step S202). At this time, the detection area scanning unit 226 sets the detection area Ra for the permitted area defined by the segmentation process. The detection region Ra may be a two-dimensional region in the x-z direction or a three-dimensional region in the x-yz direction. Since the OCT image IM in the present embodiment has a higher resolution in the z direction than the resolution in the x direction and the y direction, the size of the extraction target (HRF) is larger than that in the x direction and the y direction. The length in the z direction is apparently larger. That is, the extraction target is apparently elongated. Therefore, when set as a two-dimensional region, the detection region Ra is set to be larger in the z direction than in the x direction. The detection region Ra set as the three-dimensional region is set to be larger in the z direction than in the x direction and the y direction. In the following description, in order to simplify the description, it is assumed that the detection area Ra of the two-dimensional area is set.

Next, the luminance calculation unit 228 calculates the maximum luminance value A of the detection region Ra when the detection region Ra is scanned by the detection region scanning unit 226 (step S204). That is, the luminance calculation unit 228 calculates the maximum luminance value A of the detection region Ra every time the detection region scanning unit 226 sets the detection region Ra at a predetermined cycle. The maximum luminance value A is a luminance value that takes the maximum among the luminance values of a plurality of pixels included in the image region that overlaps with the detection region Ra.

Next, the high-luminance portion determination unit 230 determines whether or not the maximum luminance value A is equal to or greater than the maximum luminance threshold THa (step S206). For example, when the brightness value of a pixel in the OCT image IM is represented in the range of 0 to 255, the maximum brightness threshold THa is set to about 100. When the high-luminance region determination unit 230 determines that the maximum luminance value A is less than the maximum luminance threshold THa, it determines that the detection region Ra is not an image region indicating the high-luminance region (step S208). The maximum luminance threshold THa is an example of a "second threshold".

On the other hand, when it is determined that the maximum luminance value A is equal to or greater than the maximum luminance threshold THa, the luminance calculation unit 228 calculates the average luminance value B of the detection region Ra (step S210). The average luminance value B is the average of the luminance values of a plurality of pixels included in the image region that overlaps with the detection region Ra.

Next, the high-luminance portion determination unit 230 determines whether or not the average luminance value B is equal to or greater than the average luminance threshold THb (step S212). For example, when the brightness value of the pixel in the OCT image IM is expressed in the range of 0 to 255 as in the above-mentioned numerical example, the average brightness threshold THb is set to about 30. When the high-luminance region determination unit 230 determines that the average luminance value B is less than the average luminance threshold THb, the process proceeds to S208 and determines that the detection region Ra is not an image region indicating the high-luminance region. The average luminance threshold THb is an example of a “third threshold”.

On the other hand, when it is determined that the average luminance value B is equal to or greater than the average luminance threshold THb, the detection area scanning unit 226 is selected from among the plurality of OCT image IMs preprocessed by the image preprocessing unit 224, of S202. The OCT images before and after the OCT image IM selected in the process are selected (step S214). The "front and back OCT images" are images that are adjacent to each other in the OCT three-dimensional data 212 in the relationship immediately before and after in the y direction. For example, when the OCT image IM _j is selected in the process of S202, the OCT image IM _j-1 and the OCT image IM _{j + 1} are selected as the previous and next OCT images.

Next, the detection region scanning unit 226 refers to the control region Rb for each of the OCT image IM (hereinafter referred to as the focus OCT image IM) selected in the process of S202 and the OCT image IM before and after the focus OCT image. Is set (step S216).

10 to 12 are diagrams for explaining an example of a method of setting the control region Rb. FIG. 10 represents the OCT image IM _j-1 (OCT image before the OCT image of interest), FIG. 11 represents the OCT image IM _j (OCT image of interest), and FIG. 12 shows the OCT image IM _{j + 1} (OCT of interest). The OCT image after the image) is represented.

For example, when the _{control region Rb is set for the OCT image IM j} , the detection region scanning unit 226 sets the control region Rb on both sides of the detection region Ra in the x direction. Specifically, when the magnitude of the detection region Ra in the z direction is Δz, the magnitude in the x direction is Δx, and the center coordinate P _d of the detection region Ra is (x _d , z _d ), the detection region scanning unit 226 Sets the control region Rb with the coordinates P _c 1 (x _{d −} Δx, z _d ) and the coordinates P _c 2 (x _d + Δx, z _{d) as the center coordinates.}

Further, when the control region Rb is set for the OCT image IM _j-1 and the OCT image IM _{j + 1 , the detection region scanning unit 226 uses the center coordinates P d} (x) of the detection region Ra set for the _{OCT image IM j. d,} sets the control region Rb _{z d)} same coordinates as _P c _(x d, the _{z d)} as the center coordinates. These control regions Rb are set to have the same size and / or shape as the detection region Ra. As a result, the control region Rb is set as a region surrounding the detection region Ra in at least the xy plane of the three-dimensional image.

“Similar in size” means that, for example, the difference between the area of the detection region Ra and the area of the control region Rb is within a certain range (for example, about plus or minus 20 [%]), or the aspect ratio of the detection region Ra. It includes that the difference between the ratio and the aspect ratio of the control region Rb is within a certain range (for example, about plus or minus 10 [%]). Further, the “similar shape” includes, for example, that the shape of the detection region Ra and the shape of the control region Rb are similar to each other.

13 to 15 are diagrams for explaining another example of the method of setting the control region Rb. FIG. 13 represents the OCT image IM _j-1 (OCT image before the OCT image of interest) as in FIG. 10, and FIG. 14 represents the OCT image IM _j (OCT image of interest) as in FIG. , FIG. 15 represents the OCT image IM _{j + 1} (OCT image after the OCT image of interest) as in FIG. When the control region Rb is set for the OCT image IM _j-1 and the OCT image IM _{j + 1} , the detection region scanning unit 226 has a size (Δx) of the detection region Ra in the x direction as shown in FIGS. 13 and 15. ) May be set as a control region Rb having a size (3Δx) of about 3 times.

Here, the description of the flowchart of FIG. 9 returns. Next, the luminance calculation unit 228 calculates the average luminance value C of the control region Rb in the image region of each OCT image IM (step S218). The average luminance value C is the average of the luminance values of a plurality of pixels included in the image region that overlaps with the control region Rb.

Next, the high-luminance portion determination unit 230 determines whether or not the value (BC) obtained by subtracting the average luminance value C from the average luminance value B is equal to or greater than the differential luminance threshold THc (step S220). For example, when the brightness value of the pixel in the OCT image IM is represented in the range of 0 to 255 as in the numerical example described above, the differential brightness threshold THc is set to about 15. When the high-luminance region determination unit 230 determines that the value obtained by subtracting the average luminance value C from the average luminance value B is less than the differential luminance threshold THc, the process proceeds to S208, and the detection region Ra is an image showing the high-luminance region. Judge that it is not an area. The differential luminance threshold THc is an example of the “first threshold”.

On the other hand, when the high-luminance region determination unit 230 determines that the value obtained by subtracting the average luminance value C from the average luminance value B is equal to or greater than the differential luminance threshold THc, the detection region Ra is an image region indicating the high-luminance region. Determine (step S222).

Next, the high-luminance region determination unit 230 updates the high-luminance region flag corresponding to each of the pixels included in the detection region Ra in the scanning position information 214 (step S224). For example, when the high-intensity region determination unit 230 determines in the process of S208 that the detection region Ra is not an image region indicating a high-luminance region, in the scanning position information 214, the high-luminance region flag of the pixel of the detection region Ra Is set to "0". Further, when the high-luminance portion determination unit 230 determines in the process of S222 that the detection region Ra is an image region indicating a high-luminance portion, the high-luminance portion flag of the pixel of the detection region Ra is determined in the scanning position information 214. Is set to "1".

Next, the detection area scanning unit 226 determines whether or not the scanning of the detection area Ra is completed for the entire image area (permitted area) of the OCT image IM selected in the process of S202 (step S226). When the detection area scanning unit 226 determines that the scanning of the detection area Ra is not completed, the detection area scanning unit 226 returns to the process of S202 and changes the set position of the detection area Ra. As a result, the above-mentioned determination of the high-luminance portion is repeated.

On the other hand, when it is determined that the scanning of the detection area Ra is completed, the control unit 220 ends the process of this flowchart.

Here, the explanation returns to the explanation of the flowchart of FIG. Next, the group generation unit 232 generates an image region group GP in which image regions having the same average luminance value B among the image regions indicating high-luminance regions are grouped with reference to the scanning position information 214 ( Step S106). "The brightness values are about the same" means that, for example, the brightness values are the same within a range that allows an error of about several [%] to a dozen [%] with respect to the brightness value to be compared. Therefore, "the same degree of brightness value" includes that the brightness value is the same.

16 to 18 are diagrams showing an example of a method of generating an image region group GP. For example, as in the examples shown in FIGS. 16 and 17, when a plurality of detection areas Ra are set in the OCT image IM, the group generation unit 232 performs the labeling process to obtain the average luminance value of the plurality of detection areas Ra. Areas with similar B's are combined into one image area group GP.

For example, the group generation unit 232 selects a pixel that has not yet been labeled as a pixel of interest from all the pixels of the OCT image IM, and assigns a label to the pixel of interest. Next, the group generation unit 232 determines whether or not the pixels around the pixel of interest to which the label has been attached (for example, pixels adjacent to the pixel of interest in the x and z directions) have already been labeled. If no label is given to the surrounding pixels and the brightness value is about the same as that of the pixel of interest, the group generation unit 232 gives the surrounding pixels the same label as the label given to the pixel of interest. At this time, since the pixels belonging to the same image area group GP are treated as the same luminance value (for example, the average luminance value B), the same label is given. Next, the group generation unit 232 treats the peripheral pixels to which the label is attached as a new pixel of interest, and further confirms the presence / absence of the label and the brightness value of the surrounding pixels to assign the label. In this way, the group generation unit 232 assigns a label to all the pixels of the OCT image IM, and extracts a set of pixels to which the same label is given and which are adjacent to each other as one image area group GP. ..

Next, the group generation unit 232 determines whether or not the size of the image area group GP is within the permissible size (step S108). The permissible size is a prospective size obtained by scaling the actual size of the largest HRF that is expected to exist in the eyeball E according to the resolution of the device that captured the OCT image IM.

For example, the group generation unit 232 compares the maximum size ΔLX in the x direction of the image region group GP with the permissible size TH _ΔLX in the x direction, as shown in FIG. 18 described above. Further, the group generation unit 232 compares the maximum size ΔLZ in the z direction of the image region group GP with the allowable size TH _ΔLZ in the z direction. Group generation unit 232 determines the maximum size DerutaLX is below TH _DerutaLX, and if the maximum size DerutaLZ is below TH _DerutaLZ, the size of the image area groups GP is within the allowable size. On the other hand, the group generation unit 232 determines that if the maximum size DerutaLX exceeds TH _DerutaLX, or the maximum size DerutaLZ is when it exceeds TH _DerutaLZ, the size of the image area groups GP is not within the allowable size. The group generation unit 232 may determine that the size of the image area group GP is within the allowable size as long as it is equal to or smaller than the corresponding allowable size of either the maximum size ΔLX or the maximum size ΔLZ.

Further, in the above-described example, the group generation unit 232 generates the image region group GP by synthesizing the image regions in the x-direction and the z-direction, but the present invention is not limited to this. For example, the group generation unit 232 may generate the image area group GP by synthesizing the image areas in the x-direction, the z-direction, and the y-direction.

19 to 21 are diagrams showing other examples of the method of generating the image region group GP. For example, as shown in FIG. 19, when the detection region Ra is set for each OCT image IM arranged in the y direction, the group generation unit 232 has the same average brightness value as shown in FIG. One image region group GP is generated by synthesizing the image regions having B in the y direction. As shown in FIG. 20, the group generation unit 232 may synthesize image regions in consideration of a virtual width Δy that touches or overlaps with each other in the y direction. In the illustrated example, in order to simplify the explanation, the detection area Ra set in each OCT image IM is set to the same position in the x direction. Further, it is assumed that the interval of the OCT image IM in the y direction (that is, the scanning interval of the irradiation light in the y direction) is, for example, equal to or less than the maximum size of the assumed HRF.

Then, as described above, the group generation unit 232 compares the maximum size ΔLX and the maximum size ΔLZ with the allowable sizes corresponding to each, and also compares the maximum size ΔLY in the y direction of the image area group GP with the maximum size ΔLY in the y direction. By comparing with the permissible size TH _ΔLY , it may be determined whether or not the size of the image region group GP is within the permissible size.

As shown in FIG. 21, for example, in the group generation unit 232, if the size of the image area group GP is not within the allowable size, the high-luminance portion indicated by the image area group GP is an object different from the HRF to be extracted. (For example, a blood vessel or the like) is determined, and the high-luminance portion flag associated with the pixels of the plurality of image regions that are the source of the image region group GP is changed from "1" to "0" (step S110). ). As a result, the determination result that the image region is a high-luminance region made for the plurality of image regions that are the source of the image region group GP is rejected, and the image region is treated as not being a high-luminance region. .. On the other hand, if the size of the image area group GP is within the permissible size, the image area indicated by the image area group GP is detected as HRF.

Next, the group generation unit 232 calculates the number of image region group GPs for which the determination result of the high-luminance region has not been rejected, that is, the number of detected HRFs (step S112).

Next, the control unit 220 determines whether or not all the OCT image IMs included in the OCT three-dimensional data 212 have been subjected to a series of processes from S104 to S112 (step S114). When it is determined that the above-mentioned example processing has not been performed for all the OCT image IMs, the control unit 220 returns to the processing of S104.

On the other hand, when it is determined that all the OCT image IMs have undergone the above-mentioned example processing, the diagnostic determination unit 234 is based on the number of HRFs calculated by the group generation unit 232 (hereinafter referred to as the number of HRFs). , Diagnose the eyeball E as the subject (step S116). For example, the diagnostic determination unit 234 refers to the number of HRFs for each OCT image IM or the number of HRFs for each OCT three-dimensional data 212, and when the number of HRFs is larger than the reference value, "the subject has a specific disease (for example, diabetic retinopathy). You may be suffering from a disease). " For example, the reference value may be appropriately determined based on the correlation result between the observed number of HRFs and the presence or absence of the onset of a specific disease.

Next, the display control unit 236 causes the display unit 204 to display an image based on the diagnosis result by the diagnosis determination unit 234 (step S118). This completes the processing of this flowchart.

FIG. 22 is a diagram showing an example of a display unit 204 on which an image based on the diagnosis result by the diagnosis determination unit 234 is displayed. In the illustrated example, the display control unit 236 controls the display unit 204 to display a diagnostic result including the number of HRFs, a reference value of the number of HRFs, and the presence / absence (or probability of) of a specific disease. The extracted HRF is superimposed on the extraction position and displayed on a typical OCT image IM (for example, the image having the largest number of HRFs). By displaying such an image on the display unit 204, it is possible to quantitatively and objectively obtain a diagnosis result without depending on the experience and skill of each interpreter (for example, a doctor or a nurse). The display control unit 236 may simply display an image in which the number of HRFs calculated by the group generation unit 232 and the OCT image IM of the calculation source are associated with the display unit 204 on the display unit 204. This makes it possible to objectively quantify at least the number of HRFs.

In the processing of the above-mentioned flowchart, the segmentation processing by the image preprocessing unit 224 and the processing of dividing and setting the prohibited area and the permitted area are assumed to be performed before the extraction processing of the high-luminance portion shown in S104. I explained, but it is not limited to this. For example, the segmentation process and the process of dividing and setting the prohibited area and the permitted area may be performed after the extraction process of the high-luminance portion shown in S104. In this case, the detection region Ra is set in the entire OCT image IM, and a high-luminance portion can be extracted from the image region corresponding to the prohibited region. The high-intensity region determination unit 230 determines whether or not the high-luminance region extracted from the entire OCT image IM belongs to the prohibited region in the stage before the generation of the image region group GP. For example, the high-luminance region determination unit 230 changes the high-luminance region flag corresponding to the extraction region of the high-luminance region to "0" in the scanning position information 214 for the high-luminance region extracted from the prohibited region. Then, the judgment result that it is a high-luminance part is rejected. As a result, the processing load is increased while maintaining the HRF detection accuracy, as in the case where both the segmentation process and the process of dividing and setting the prohibited area and the permitted area are performed before the extraction process of the high-luminance portion. Can be mitigated.

Further, in the above-described first embodiment, the control region Rb has been described as being set to a _{certain OCT image IM j} of interest, and the OCT image IM _j-1 and the OCT image IM _{j + 1 before and after the control region Rb.} Not limited. For example, when the detection area Ra extends in the y direction, that is, when the detection area Ra is treated as a three-dimensional area, the detection area Ra is set across a plurality of OCT image IMs arranged in the y direction. In this case, for example, when two OCT image IM _j and _{IM j +} same detection region Ra for _one adjacent to each other in the y direction is set, the control region Rb is the previous OCT image IM _j OCT image _{IM j- 1,} while being set to a second previous OCT images _{IM j-2,} an OCT image _{IM j + 2} after the OCT image _{IM j + 1,} may be set to a later of the OCT image _{IM j + 3.} That is, a plurality of OCT image IMs in which the same detection region Ra is set are considered as one block (hereinafter referred to as a detection block), and blocks of the same size for setting a control region Rb before and after the detection block (hereinafter referred to as a detection block). , Called a control block) may be set. The same size means that the number of OCT image IMs included in the detection block is the same. For example, if the detection block contains two OCT image IMs, the front and rear control blocks are set to contain two OCT image IMs, respectively. The size of the control block may be different from that of the detection block. For example, the size of the control block may be twice or three times the size of the detection block.

According to the first embodiment described above, in the three-dimensional image indicated by the OCT three-dimensional data, the detection region Ra is determined based on the comparison of the pixel values of the detection region Ra and the control region Rb surrounding the detection region Ra. By determining whether or not it is a predetermined image region such as a high-intensity portion showing HRF, it is possible to detect an event occurring in the eyeball E such as HRF by image processing from the OCT image IM.

(Second Embodiment)
Hereinafter, the image processing apparatus 200 according to the second embodiment will be described. The image processing apparatus 200 according to the second embodiment is different from the first embodiment in that, for example, the method disclosed in Non-Patent Document 1 is applied to provide a gap between the detection region Ra and the control region Rb. .. Hereinafter, the differences from the first embodiment will be mainly described, and the description of the parts common to the first embodiment will be omitted.

FIG. 23 is a diagram for explaining an example of a method of setting a control region Rb by providing a gap with the detection region Ra. For example, when the _{control region Rb is set for the OCT image IM j} , the detection region scanning unit 226 provides a gap for one detection region Ra on both sides of the detection region Ra in the x direction to provide a control region Rb. Set Rb. Specifically, when the magnitude of the detection region Ra in the z direction is Δz, the magnitude in the x direction is Δx, and the center coordinate P _d of the detection region Ra is (x _d , z _d ), the detection region scanning unit 226 Sets the control region Rb with the coordinates P _c 1 (x _d -2Δx, z _d ) and the coordinates P _c 2 (x _d + 2Δx, z _{d) as the center coordinates.}

Further, when the illumination region Rb is set in the y direction, the detection region scanning unit 226 _{displays the OCT image IM j-1} and the OCT image IM _{j + 1} arranged in front of and behind the _{OCT image IM j in which the detection region Ra is set.} , Excluded from the target image for which the control region Rb is set, and is adjacent to the OCT image IM _{j of interest such as OCT image IM j-2} and OCT image IM _{j + 2} and OCT image IM _j-3 and OCT image IM _{j + 3.} A control region Rb is set for no image. As a result, a gap can be provided between the detection region Ra and the control region Rb not only in the x direction but also in the y direction.

FIG. 24 is a diagram showing an example of a detection result of a high-luminance portion when no gap is provided between the detection region Ra and the control region Rb. Further, FIG. 25 is a diagram showing an example of a detection result of a high-luminance portion when a gap is provided between the detection region Ra and the control region Rb. For example, the size of the high-luminance portion to be detected in the x-direction may be about the same as the size of both the detection region Ra and the control region Rb in the x-direction. In such a case, as shown in FIG. 24, when no gap is provided between the detection region Ra and the control region Rb, the high-luminance portion to be detected is superimposed on both the detection region Ra and the control region Rb. The value (BC) obtained by subtracting the average luminance value C of the control region Rb from the average luminance value B of the detection region Ra tends to be less than the differential luminance threshold THc. Where it should be determined that is an image region indicating a high-luminance region, it can be determined that the detection region Ra is not an image region indicating a high-luminance region. On the other hand, as shown in FIG. 25, when a gap is provided between the detection region Ra and the control region Rb, the high-luminance portion is large and is superimposed on the region adjacent to the detection region Ra. Even if there is, since the overlapping region is a region provided as a gap, the value (BC) obtained by subtracting the average luminance value C of the control region Rb from the average luminance value B of the detection region Ra is the differential luminance threshold THc. This is likely to occur, and the image region indicating the high-luminance portion can be detected with high accuracy.

26 to 30 are views showing an example of variations in the method of setting the control region Rb when providing a gap. Each figure represents an xy plane with a three-dimensional image. For example, as illustrated in FIG. 26, when the center coordinates of the detection region Ra are (x _d , y _d ) in the xy plane, the detection region scanning unit 226 has the coordinates (x _d , y _d -2Δx). ), (X _d + 2Δx, y _d ), (x _d , y _d + 2Δy), (x _d -2Δx, y _d ) by setting four control regions Rb with each of them as the center coordinate, in the x direction. In, a gap of the width Δx of the detection region Ra can be provided, and a gap of the width Δy of the detection region Ra can be provided in the y direction.

Further, as illustrated in FIG. 27, the detection area scanning unit 226 has the magnitude of the detection area Ra in the x direction with the _{coordinates (x d} , y _d -2Δx) and (x _d , y _{d + 2Δy) as the center coordinates.} A control region Rb having a size (5Δx) about 5 times as large as (Δx) may be set.

Further, as illustrated in FIG. 28, the detection region scanning unit 226 provides a gap in the direction of intersection with respect to the x direction and the y direction (direction of intersection at an angle of 45 ° in the illustrated example) to provide a control region Rb. It may be set.

Further, as illustrated in FIG. 29, the detection region scanning unit 226 may set a plurality of control regions Rb so that the control regions Rbs partially overlap each other. As a result, an apparently one control region Rb in which the region is continuous is set around the detection region Ra.

Further, instead of setting the control region Rb at a position where a gap for one detection region Ra is provided, the detection region scanning unit 226 has, for example, half the size of the detection region Ra, as illustrated in FIG. The control region Rb may be set at a position where the gap is provided, or the control region Rb may be set at a position where a gap having a size equal to twice or three times the detection region Ra is provided.

According to the second embodiment described above, since the control region Rb is set by providing a gap between the detection region Ra and the detection region Ra, the shape of the high-luminance portion such as the HRF is distorted or its size varies. Even if it does, it is possible to detect the high-luminance part with high accuracy. As a result, an event occurring in the eyeball E such as HRF can be detected more accurately.

[Hardware configuration]
The image processing device 200 of the above-described embodiment is realized by, for example, a hardware configuration as shown in FIG. FIG. 31 is a diagram showing an example of the hardware configuration of the image processing device 200 of the embodiment.

The image processing device 200 includes a communication interface 200-1 such as a NIC (Network Interface Card), a CPU 200-2, a RAM 200-3, a ROM 200-4, a secondary storage device 200-5 such as a flash memory or an HDD, and a drive device 200. -6 are connected to each other by an internal bus or a dedicated communication line. A portable storage medium such as an optical disk is mounted on the drive device 200-6. The program 200-5a stored in the secondary storage device 200-5 is expanded into the RAM 200-3 by a DMA controller (not shown) or the like, and executed by the CPU 200-2 to realize the control unit 220. Further, the program referred to by the CPU 200-2 may be stored in a portable storage medium mounted on the drive device 200-6, or may be downloaded from another device via a network.

The above embodiment can be expressed as follows.
Storage to store information and
A processor that executes a program stored in the storage is provided.
The processor executes the program.
A plurality of optical interference tomographic images generated by irradiating an eyeball with light by the optical interference tomography method and having a resolution in the first direction higher than that in the second direction orthogonal to the first direction. A plurality of optical interference tomographic images arranged in a third direction orthogonal to each of the first direction and the second direction are acquired.
In a virtual three-dimensional image formed by a plurality of acquired optical interference tomographic images, the detection region is based on a comparison of pixel values between the detection region and a control region set in the region surrounding the detection region. Is an image processing device configured to determine whether or not a predetermined image region in which a predetermined event occurs in the eyeball.

Although the embodiments for carrying out the present invention have been described above using the embodiments, the present invention is not limited to these embodiments, and various modifications and substitutions are made without departing from the gist of the present invention. Can be added.

1. Fundus imaging system, 100 ... OCT imaging device, 110 ... OCT unit, 120 ... illumination optical system, 130 ... imaging optical system, 200 ... image processing device, 202 ... communication interface, 204 ... display unit, 210 ... storage unit, 212 ... OCT three-dimensional data, 214 ... scanning position information, 220 ... control unit, 222 ... acquisition unit, 224 ... image preprocessing unit, 226 ... detection area scanning unit, 228 ... brightness calculation unit, 230 ... high brightness part determination unit , 232 ... Group generation unit, 234 ... Diagnosis judgment unit, 236 ... Display control unit, E ... Eyeball, Er ... Fundus

Claims (19)

A plurality of optical interference tomographic images generated by irradiating an eyeball with light by the optical interference tomography method and having a resolution in the first direction higher than that in the second direction orthogonal to the first direction. An acquisition unit that acquires a plurality of optical interference tomographic images arranged in a third direction orthogonal to each of the first direction and the second direction.
In a virtual three-dimensional image formed by a plurality of optical interference tomographic images acquired by the acquisition unit, the pixel values of the detection region and the control region set in the region surrounding the detection region are compared. A determination unit for determining whether or not the detection region is a predetermined image region in which a predetermined event occurs in the eyeball.
An image processing device comprising. The first direction is a direction along the irradiation direction of the light irradiated to the eyeball in the process of generating the optical interference tomographic image.
The image processing apparatus according to claim 1. The control region is a region surrounding the detection region around the first direction.
The image processing apparatus according to claim 1 or 2. The longitudinal direction of the detection region is the first direction.
The image processing apparatus according to any one of claims 1 to 3. When the difference between the average value of the pixel values in the detection region and the average value of the pixel values in the control region is equal to or greater than the first threshold value, the determination unit determines that the detection region is a predetermined image region. judge,
The image processing apparatus according to any one of claims 1 to 4. The determination unit further determines whether or not the maximum value of the pixel value in the detection region is equal to or greater than the second threshold value, and when the maximum value of the pixel value in the detection region is not equal to or greater than the second threshold value, the detection unit Determining that the area is not a predetermined image area,
The image processing apparatus according to any one of claims 1 to 5. The determination unit further determines whether or not the average value of the pixel values in the detection region is equal to or greater than the third threshold value, and when the average value of the pixel values in the detection region is not equal to or greater than the third threshold value, the detection unit Determining that the area is not a predetermined image area,
The image processing apparatus according to any one of claims 1 to 6. The control region is set on the optical interference tomographic image in which the detection region is set.
The image processing apparatus according to any one of claims 1 to 7. The control region is set at either or both of the positions adjacent to the detection region in the second direction.
The image processing apparatus according to claim 8. The control region is at least one or more optical interference adjacent to the optical interference tomographic image in which the detection region is set in the third direction among the plurality of optical interference tomographic images acquired by the acquisition unit. Set on the tomographic image,
The image processing apparatus according to claim 8 or 9. The control region is set at a position based on the position of the detection region in the first direction.
The image processing apparatus according to any one of claims 8 to 10. The control region is set to be as large as the detection region at least in the first direction.
The image processing apparatus according to any one of claims 8 to 11. A group generation unit that generates an image area group in which image areas having the same average pixel value among the image areas determined to be a predetermined image area by the determination unit are grouped together.
A display control unit that associates the number of image area groups generated by the group generation unit with the optical interference tomographic image in which the detection area is set and displays them on the display unit is further provided.
The image processing apparatus according to any one of claims 1 to 12. A segmentation processing unit further comprises a segmentation processing unit that divides the optical interference tomographic image to which the detection area is to be set into a prohibited area for prohibiting the setting of the detection area and a permitted area for permitting the setting of the detection area.
The image processing apparatus according to claim 13. It further includes a segmentation processing unit that divides the optical interference tomographic image in which the detection area is set into a prohibited area for prohibiting the setting of the detection area and a permitted area for permitting the setting of the detection area.
The image processing apparatus according to claim 13. A diagnostic unit for diagnosing the pathological condition of the eyeball is further provided based on the number of image region groups generated by the group generation unit.
The display control unit causes the display unit to display an image based on the diagnosis result by the diagnosis unit.
The image processing apparatus according to any one of claims 13 to 15. The image processing apparatus according to any one of claims 1 to 16.
With an optical interference tomographic image imaging device that has a higher resolution in the first direction than the resolution in the second direction and generates the plurality of optical interference tomographic images by irradiating the eyeball with light by the optical interference tomography method. ,
A fundus imaging system equipped with. The computer
A plurality of optical interference tomographic images generated by irradiating an eyeball with light by the optical interference tomography method and having a resolution in the first direction higher than that in the second direction orthogonal to the first direction. A plurality of optical interference tomographic images arranged in a third direction orthogonal to each of the first direction and the second direction are acquired.
In a virtual three-dimensional image formed by the plurality of acquired optical interference tomographic images, the detection is based on a comparison of pixel values between the detection region and the control region set in the region surrounding the detection region. It is determined whether or not the region is a predetermined image region in which a predetermined event occurs in the eyeball.
Image processing method. On the computer
A plurality of optical interference tomographic images generated by irradiating an eyeball with light by the optical interference tomography method and having a resolution in the first direction higher than that in the second direction orthogonal to the first direction. A plurality of optical interference tomographic images arranged in a third direction orthogonal to each of the first direction and the second direction are acquired.
In a virtual three-dimensional image formed by the plurality of acquired optical interference tomographic images, the pixel values of the detection region and the control region set in the region surrounding the detection region are compared. It is made to determine whether or not the detection area is a predetermined image area in which a predetermined event occurs in the eyeball.
program.

Images