WO2014020966A1 - Fundus analysis device, fundus analysis program, and fundus analysis method - Google Patents

Abstract

Provided is a technology that can effectively detect drusen on the basis of a fundus tomogram. This fundus analysis device has a recording unit, a layer region identification unit, a similar curve computation unit, a protruding region identification unit, a joint region identification unit, and a form information generation unit. The recording unit records a tomogram depicting the layered structure of the fundus. On the basis of the pixel values of the pixels of the tomogram, the layer region identification unit identifies a layer region within the tomogram corresponding to the retinal pigment epithelium. The similar curve computation unit determines a similar curve on the basis of the shape of the layer region. The protruding region identification unit identifies a protruding region at which the similar curve is positioned in the direction of depth of the fundus with respect to the layer region and the distance between the layer region and the similar curve in the direction of depth is at least a predetermined threshold. The joint region identification unit identifies a joint region that includes the protruding region and is encircled by the layer region and the similar curve. The form information generation unit generates form information representing the form of the joint region.

Description

Fundus analysis apparatus, fundus analysis program, and fundus analysis method

The present invention relates to a technique for analyzing a fundus image formed by using optical coherence tomography (OCT).

In recent years, OCT that forms an image representing the surface form and internal form of an object to be measured using a light beam from a laser light source or the like has attracted attention. Since OCT has no invasiveness to the human body like X-ray CT, it is expected to be applied particularly in the medical field and the biological field. For example, in the field of ophthalmology, an apparatus for forming an image of the fundus oculi, cornea, etc. has entered a practical stage.

Patent Document 1 discloses an apparatus to which OCT is applied. In this device, the measuring arm scans an object with a rotary turning mirror (galvanomirror), a reference mirror is installed on the reference arm, and the intensity of the interference light of the light beam from the measuring arm and the reference arm is dispersed at the exit. An interferometer is provided for analysis by the instrument. Further, the reference arm is configured to change the phase of the reference light beam stepwise by a discontinuous value.

The apparatus of Patent Document 1 uses a so-called “Fourier Domain OCT (Fourier Domain OCT)” technique. In other words, a low-coherence beam is irradiated onto the object to be measured, the reflected light and the reference light are superimposed to generate interference light, and the spectral intensity distribution of the interference light is acquired and subjected to Fourier transform. Thus, the form of the object to be measured in the depth direction (z direction) is imaged. Note that this type of technique is also called a spectral domain.

Furthermore, the apparatus described in Patent Document 1 includes a galvanometer mirror that scans a light beam (signal light), thereby forming an image of a desired measurement target region of the object to be measured. Since this apparatus is configured to scan the light beam only in one direction (x direction) orthogonal to the z direction, the image formed by this apparatus is in the scanning direction (x direction) of the light beam. It becomes a two-dimensional tomogram in the depth direction (z direction) along.

In Patent Document 2, a plurality of two-dimensional tomographic images in the horizontal direction are formed by scanning (scanning) the signal light in the horizontal direction (x direction) and the vertical direction (y direction), and based on the plurality of tomographic images. A technique for acquiring and imaging three-dimensional tomographic information of a measurement range is disclosed. Examples of the three-dimensional imaging include a method of displaying a plurality of tomographic images side by side in a vertical direction (referred to as stack data), a method of rendering a plurality of tomographic images and forming a three-dimensional tomographic image, and the like. Can be considered.

Patent Documents 3 and 4 disclose other types of OCT apparatuses. Patent Document 3 scans the wavelength of light applied to an object to be measured, acquires a spectral intensity distribution based on interference light obtained by superimposing reflected light of each wavelength and reference light, On the other hand, an OCT apparatus for imaging the form of an object to be measured by performing Fourier transform on the object is described. Such an OCT apparatus is called a swept source type. The swept source type is a kind of Fourier domain type.

In Patent Document 4, the traveling direction of light is obtained by irradiating the object to be measured with light having a predetermined beam diameter, and analyzing the component of interference light obtained by superimposing the reflected light and the reference light. An OCT apparatus for forming an image of an object to be measured in a cross-section orthogonal to is described. Such an OCT apparatus is called a full-field type or an en-face type.

Patent Document 5 discloses a configuration in which OCT is applied to the ophthalmic field. The apparatus described in this document has a function of photographing the fundus and forming a fundus image, and a function of measuring a fundus using OCT and forming a tomographic image. Further, this apparatus analyzes a tomographic image and specifies an image region corresponding to a layer tissue constituting the fundus. Specific target layer tissues include inner boundary membrane, nerve fiber layer, ganglion cell layer, inner reticular layer, inner granular layer, outer reticular layer, outer granular layer, outer boundary membrane, photoreceptor layer, retinal pigment epithelial layer, etc. There is. Since the fundus is formed by overlapping a plurality of layer tissues, obtaining an image area corresponding to the layer tissue is synonymous with obtaining an image area corresponding to a boundary position between adjacent layer tissues. Note that a fundus camera has been widely used as an apparatus for observing the fundus before OCT is applied (see, for example, Patent Document 6).

An apparatus using OCT has an advantage over a fundus camera or the like in that a high-definition image can be acquired and a tomographic image can be acquired.

In recent years, an eye disease called age-related macular degeneration has attracted attention. Age-related macular degeneration is a disease that occurs because the function of the macular portion of the retina is reduced due to aging. Cause symptoms such as invisible.

Age-related macular degeneration (wetting type) is thought to develop by the following mechanism. Normal retinal cells repeat metabolism. Waste products generated by metabolism are normally digested in the retinal pigment epithelium and disappear. However, when the function of the retinal pigment epithelium decreases due to aging, undigested waste products accumulate between the Bruch's membrane and the retinal pigment epithelium layer. When photographing the fundus in this state, the waste is recognized as a white mass called drusen. When waste is accumulated, a weak inflammatory reaction occurs. Then, a specific chemical substance (chemical mediator) is produced and promotes healing of inflammation. However, chemical mediators have factors that promote the generation of blood vessels, and new blood vessels (new blood vessels) grow from the choroid. When new blood vessels break through the Bruch's membrane and invade below or above the retinal pigment epithelial layer and proliferate, blood and blood components are exuded so severely that the macular function decreases.

Presence and distribution of drusen is important in the diagnosis of age-related macular degeneration. Conventionally, a fundus image (an image taken by a fundus camera) has been mainly used to grasp the drusen state (see, for example, Patent Document 7). Further, as a method using a tomographic image, there is Patent Document 8 by the present applicant.

Japanese Patent Laid-Open No. 11-325849 JP 2002-139421 A JP 2007-24677 A JP 2006-153838 A JP 2008-73099 A JP-A-9-276232 JP 2008-295804 A JP 2011-30626 A

An object of the present invention is to provide a technique capable of effectively detecting drusen based on a tomographic image of the fundus.

In order to achieve the above object, the invention according to claim 1 is directed to a retinal pigment epithelium layer based on a storage unit that stores a tomographic image depicting a fundus layer structure and a pixel value of a pixel of the tomographic image. A layer region specifying unit for specifying a corresponding layer region in the tomographic image, an approximate curve calculation unit for obtaining an approximate curve based on the shape of the layer region, and the approximate curve in the depth direction of the fundus than the layer region A protruding region specifying unit that specifies a protruding region that is located and a distance between the approximate curve in the depth direction and the layer region is equal to or greater than a predetermined threshold; the protruding region; and the approximate curve and the layer The fundus analysis apparatus includes a connected region specifying unit that specifies a connected region surrounded by a region and a form information generating unit that generates form information representing the form of the connected region.
The invention according to claim 2 is the fundus analysis apparatus according to claim 1, wherein the approximate curve calculation unit calculates a plurality of characteristic parts in the layer region based on the shape of the layer region. A characteristic part specifying unit to be specified is included, and the approximate curve is obtained based on the plurality of characteristic parts.
The invention according to claim 3 is the fundus analysis apparatus according to claim 2, wherein the characteristic part specifying unit is the deepest part in the layer region in the depth direction based on the shape of the layer region. Is defined as a characteristic part, a straight line passing through the deepest part and in contact with the layer region is obtained, and a contact point between the layer region and the straight line is defined as a further characteristic part.
The invention according to claim 4 is the fundus analysis apparatus according to claim 3, wherein the characteristic part specifying unit rotates a straight line passing through the deepest part around the deepest part. The contacts are sequentially identified by the above.
The invention according to claim 5 is the fundus analysis apparatus according to claim 3, wherein the characteristic part specifying unit rotates a straight line passing through the deepest part around the deepest part to provide a contact point. A further contact is specified by specifying and rotating a straight line passing through the specified contact around the contact.
The invention according to claim 6 is the fundus analysis apparatus according to any one of claims 2 to 5, wherein the approximate curve calculation unit is a distance between two adjacent characteristic parts. And a feature part interpolation unit that adds a new feature part between the two feature parts when the distance is equal to or greater than a predetermined value.
The invention according to claim 7 is the fundus analysis apparatus according to any one of claims 2 to 6, wherein the approximate curve calculation unit calculates a free curve based on the plurality of characteristic parts. And obtaining the approximate curve based on the free curve.
The invention according to claim 8 is the fundus analysis apparatus according to claim 7, wherein the approximate curve calculation unit obtains a spline curve as the free curve.
The invention according to claim 9 is the fundus analysis apparatus according to claim 8, wherein the approximate curve calculation unit obtains a cubic spline curve as the spline curve.
The invention according to claim 10 is the fundus analysis apparatus according to any one of claims 7 to 9, wherein the approximate curve calculation unit is substantially linear in the layer region. When the straight part specifying unit for specifying a part and the free curve are located in the depth direction with respect to the straight part, the free curve is deformed so that the part of the free curve matches the position of the straight part. A first deformation unit, and the approximate curve is obtained based on a deformation result by the first deformation unit.
The invention according to claim 11 is the fundus analysis apparatus according to any one of claims 7 to 10, wherein the approximate curve calculation unit is more in the free curve than the layer region. A curved part specifying part for specifying a part located in the reverse direction of the depth direction; and a second deforming part for deforming the free curve so as to match the specific part with the position of the layer region, The approximate curve is obtained on the basis of the deformation result obtained by the above.
The invention according to claim 12 is the fundus analysis apparatus according to any one of claims 7 to 11, wherein the approximate curve calculation unit is in the vicinity of an end of a frame of the tomographic image. A protrusion determining unit that determines whether the layer region protrudes in a direction opposite to the depth direction, and when it is determined that the layer region protrudes, the free curve portion corresponding to the protruding portion is defined as the frame. A third deforming portion that deforms the free curve by replacing with an extension line of the free curve from the center side, and the approximate curve is obtained based on a deformation result by the third deforming portion. And
The invention according to claim 13 is the fundus analysis apparatus according to any one of claims 1 to 12, wherein the projecting region specifying unit includes each of the approximate curves in the depth direction. A distance between a point and the layer region is calculated, it is determined whether the calculated distance is equal to or greater than the predetermined threshold, and a set of points on the approximate curve determined to be equal to or greater than the predetermined threshold and the layer An image region sandwiched between regions is specified as the protruding region.
The invention according to claim 14 is the fundus analysis apparatus according to any one of claims 1 to 13, wherein the morphological information generation unit analyzes the tomographic image to obtain the fundus Including a nipple region determination unit that determines whether a nipple region corresponding to the optic disc is included in the tomographic image, and the connection region specified by the connection region specifying unit when it is determined that the nipple region is included The shape information is generated by excluding a connected region located in the vicinity of the nipple region.
The invention according to claim 15 is the fundus analysis apparatus according to claim 14, wherein the papillary region determination unit analyzes the tomographic image and corresponds to a predetermined feature layer of the fundus. A region is specified, and it is determined whether the nipple region is included based on the shape of the specified feature layer region.
The invention according to claim 16 is the fundus analysis apparatus according to claim 15, wherein the predetermined feature layer is an inner boundary film that forms a boundary with the vitreous body in the fundus, and the papillary region determination The unit determines whether or not there is a portion depressed in the depth direction in the feature layer region, and determines that the nipple region is included when it is determined that the depressed portion exists.
The invention according to claim 17 is the fundus analysis apparatus according to any one of claims 14 to 16, wherein the papillary region determination unit is configured such that the eye to be examined is the left eye or the right eye. If the subject's eye is the left eye, the determination is made by analyzing at least the vicinity of the left end of the frame of the tomographic image, and the subject's eye is the right eye. In some cases, the determination is performed by analyzing at least the vicinity of the right end of the frame.
The invention according to claim 18 is the fundus analysis apparatus according to any one of claims 1 to 17, wherein the light from the light source is divided into signal light and reference light, and the eye to be inspected. System that generates and detects interference light by superimposing signal light that passes through the fundus of the eye and reference light that passes through the reference optical path, and an image forming unit that forms a tomographic image of the fundus based on the detection result of the interference light The storage unit stores a tomographic image formed by the image forming unit.
The invention according to claim 19 corresponds to a retinal pigment epithelial layer based on a storage unit that stores a three-dimensional tomographic image depicting a layer structure of the fundus and a pixel value of a pixel of the three-dimensional tomographic image. A layer region specifying unit for specifying a layer region in the tomographic image, an approximate curved surface calculating unit for obtaining an approximate curved surface based on the shape of the layer region, and the approximate curved surface being positioned in the depth direction of the fundus than the layer region. And a protruding area specifying unit that specifies a protruding area in which a distance between the approximate curved surface and the layer area in the depth direction is equal to or greater than a predetermined threshold; and the protruding area, and the approximate curved surface and the layer area The fundus analysis apparatus includes a connected region specifying unit that specifies an enclosed connected region, and a morphological information generating unit that generates morphological information representing the form of the connected region.
According to a twentieth aspect of the present invention, there is provided a computer having a storage unit that stores a tomogram depicting a layer structure of the fundus oculi corresponding to a retinal pigment epithelium layer based on a pixel value of a pixel of the tomogram. A layer region specifying unit for specifying a layer region in the tomogram, an approximate curve calculating unit for obtaining an approximate curve based on the shape of the layer region, the approximate curve being positioned in the depth direction of the fundus than the layer region, and A protruding area specifying unit that specifies a protruding area whose distance in the depth direction between the approximate curve and the layer area is equal to or greater than a predetermined threshold, including the protruding area, and a connection surrounded by the approximate curve and the layer area It is a fundus analysis program that functions as a connected region specifying unit that specifies a region and a form information generating unit that generates form information indicating the form of the connected region.
According to a twenty-first aspect of the present invention, there is provided a computer having a storage unit that stores a three-dimensional tomogram depicting a fundus layer structure based on pixel values of pixels of the three-dimensional tomogram. A layer region specifying unit for specifying a layer region in the tomographic image, an approximate curved surface calculation unit for obtaining an approximate curved surface based on the shape of the layer region, and the approximate curved surface being positioned in the depth direction of the fundus than the layer region And a protruding area specifying unit that specifies a protruding area in which the distance between the approximate curved surface and the layer area in the depth direction is equal to or greater than a predetermined threshold, the protruding area, and the approximate curved surface and the layer area. It is a fundus analysis program that functions as a connected region specifying unit that specifies an enclosed connected region and a form information generating unit that generates form information representing the form of the connected region.
The invention according to claim 22 is a fundus analysis method for analyzing a tomographic image depicting a layer structure of the fundus oculi, which corresponds to a retinal pigment epithelial layer based on pixel values of pixels of the tomographic image. Identifying a layer region in a tomogram, obtaining an approximate curve based on the shape of the layer region, the approximate curve being located in the depth direction of the fundus than the layer region, and the approximate curve and the Identifying a protruding region whose distance in the depth direction between the layer region is equal to or greater than a predetermined threshold; and specifying a connected region that includes the protruding region and is surrounded by the approximate curve and the layer region; Generating form information representing the form of the connected area.
The invention according to claim 23 is a fundus analysis method for analyzing a three-dimensional tomographic image depicting a layer structure of the fundus oculi, wherein the retinal pigment epithelial layer is based on pixel values of pixels of the three-dimensional tomographic image. Identifying the layer region in the tomographic image corresponding to the step, obtaining an approximate curved surface based on the shape of the layer region, the approximate curved surface is located in the depth direction of the fundus than the layer region, and Identifying a projecting region in which a distance between the approximate curved surface and the layer region in a depth direction is equal to or greater than a predetermined threshold; and a connecting region including the projecting region and surrounded by the approximate curved surface and the layer region. A step of specifying, and a step of generating form information representing the form of the connected region.

According to the present invention, drusen can be detected effectively based on a tomographic image of the fundus.

It is the schematic which shows an example of a structure of the fundus analysis apparatus which concerns on embodiment. It is the schematic which shows an example of a structure of the fundus analysis apparatus which concerns on embodiment. It is a schematic block diagram which shows an example of a structure of the fundus analysis apparatus which concerns on embodiment. It is a schematic block diagram which shows an example of a structure of the fundus analysis apparatus which concerns on embodiment. It is a schematic explanatory drawing for demonstrating the example of the process which the fundus analyzer which concerns on embodiment performs. It is a schematic explanatory drawing for demonstrating the example of the process which the fundus analyzer which concerns on embodiment performs. It is a schematic explanatory drawing for demonstrating the example of the process which the fundus analyzer which concerns on embodiment performs. It is a schematic explanatory drawing for demonstrating the example of the process which the fundus analyzer which concerns on embodiment performs. It is a schematic explanatory drawing for demonstrating the example of the process which the fundus analyzer which concerns on embodiment performs. It is a schematic explanatory drawing for demonstrating the example of the process which the fundus analyzer which concerns on embodiment performs. It is a schematic explanatory drawing for demonstrating the example of the process which the fundus analyzer which concerns on embodiment performs. It is a schematic explanatory drawing for demonstrating the example of the process which the fundus analyzer which concerns on embodiment performs. It is a schematic explanatory drawing for demonstrating the example of the process which the fundus analyzer which concerns on embodiment performs. It is a schematic explanatory drawing for demonstrating the example of the process which the fundus analyzer which concerns on embodiment performs. It is a schematic explanatory drawing for demonstrating the example of the process which the fundus analyzer which concerns on embodiment performs. It is a schematic explanatory drawing for demonstrating the example of the process which the fundus analyzer which concerns on embodiment performs. It is a schematic explanatory drawing for demonstrating the example of the process which the fundus analyzer which concerns on embodiment performs. It is a flowchart showing the operation example of the fundus analysis apparatus which concerns on embodiment.

An example of an embodiment of a fundus analysis apparatus, a fundus analysis program, and a fundus analysis method according to the present invention will be described in detail with reference to the drawings. In addition, it is possible to use suitably the description content of the literature described in this specification as the content of the following embodiment.

The fundus analysis apparatus according to the present invention may be a computer that analyzes a tomographic image (two-dimensional tomographic image, three-dimensional tomographic image) of the fundus, or forms a tomographic image of the fundus using optical coherence tomography. The OCT apparatus which can do is also possible. The latter OCT apparatus includes the former computer. Therefore, the latter OCT apparatus will be described in detail below.

The fundus analyzer as the OCT apparatus may be of any type as long as it can form a tomographic image of the fundus. In the following embodiment, the spectral domain type will be described in detail. Since the feature of the present invention is centered on the processing of analyzing a tomographic image of the fundus, other types of OCT apparatuses such as a swept source type and an infass type can be similarly configured. A measurement operation for forming a tomographic image using OCT may be referred to as OCT measurement.

In the following embodiment, an apparatus combining an OCT apparatus and a fundus camera will be described. However, a fundus imaging apparatus other than the fundus camera, such as an SLO, a slit lamp, an ophthalmic surgical microscope, or the like, has an OCT configuration according to this embodiment. It is also possible to combine devices. In addition, the configuration according to this embodiment can be incorporated into a single OCT apparatus. The SLO (Scanning Laser Ophthalmoscope) is an apparatus that images the fundus surface by scanning the fundus with laser light and detecting the reflected light with a highly sensitive element such as a photomultiplier tube.

[Constitution]
As shown in FIGS. 1 and 2, the fundus analysis apparatus 1 includes a fundus camera unit 2, an OCT unit 100, and an arithmetic control unit 200. The retinal camera unit 2 has almost the same optical system as a conventional retinal camera. The OCT unit 100 is provided with an optical system for acquiring a fundus tomographic image. The arithmetic control unit 200 includes a computer that executes various arithmetic processes and control processes.

[Fundus camera unit]
The fundus camera unit 2 shown in FIG. 1 is provided with an optical system for obtaining a two-dimensional image (fundus image) representing the surface form of the fundus oculi Ef of the eye E to be examined. The fundus image includes an observation image and a captured image. The observation image is, for example, a monochrome moving image formed at a predetermined frame rate using near infrared light. The captured image is, for example, a color image obtained by flashing visible light, or a monochrome still image using near infrared light or visible light as illumination light. The fundus camera unit 2 may be configured to be able to acquire images other than these, such as a fluorescein fluorescent image, an indocyanine green fluorescent image, a spontaneous fluorescent image, and the like.

The fundus camera unit 2 is provided with a chin rest and a forehead for supporting the subject's face. Further, the fundus camera unit 2 is provided with an illumination optical system 10 and a photographing optical system 30. The illumination optical system 10 irradiates the fundus oculi Ef with illumination light. The photographing optical system 30 guides the fundus reflection light of the illumination light to an imaging device (CCD image sensor (sometimes simply referred to as a CCD) 35, 38). The imaging optical system 30 guides the signal light from the OCT unit 100 to the fundus oculi Ef and guides the signal light passing through the fundus oculi Ef to the OCT unit 100.

The observation light source 11 of the illumination optical system 10 is composed of, for example, a halogen lamp. The light (observation illumination light) output from the observation light source 11 is reflected by the reflection mirror 12 having a curved reflection surface, passes through the condensing lens 13, passes through the visible cut filter 14, and is converted into near infrared light. Become. Further, the observation illumination light is once converged in the vicinity of the photographing light source 15, reflected by the mirror 16, and passes through the relay lenses 17 and 18, the diaphragm 19 and the relay lens 20. Then, the observation illumination light is reflected at the peripheral portion (region around the hole portion) of the aperture mirror 21, passes through the dichroic mirror 46, and is refracted by the objective lens 22 to illuminate the fundus oculi Ef. An LED (Light Emitting Diode) can also be used as the observation light source.

The fundus reflection light of the observation illumination light is refracted by the objective lens 22, passes through the dichroic mirror 46, passes through the hole formed in the central region of the perforated mirror 21, passes through the dichroic mirror 55, and is a focusing lens. It is reflected by the mirror 32 via 31. Further, the fundus reflection light passes through the half mirror 39A, is reflected by the dichroic mirror 33, and forms an image on the light receiving surface of the CCD image sensor 35 by the condenser lens. The CCD image sensor 35 detects fundus reflected light at a predetermined frame rate, for example. On the display device 3, an image (observation image) based on fundus reflection light detected by the CCD image sensor 35 is displayed. When the photographing optical system 30 is focused on the anterior segment, an observation image of the anterior segment of the eye E is displayed.

The photographing light source 15 is constituted by, for example, a xenon lamp. The light (imaging illumination light) output from the imaging light source 15 is applied to the fundus oculi Ef through the same path as the observation illumination light. The fundus reflection light of the imaging illumination light is guided to the dichroic mirror 33 through the same path as that of the observation illumination light, passes through the dichroic mirror 33, is reflected by the mirror 36, and is reflected by the condenser lens 37 of the CCD image sensor 38. An image is formed on the light receiving surface. On the display device 3, an image (captured image) based on fundus reflection light detected by the CCD image sensor 38 is displayed. Note that the display device 3 that displays the observation image and the display device 3 that displays the captured image may be the same or different. In addition, when similar imaging is performed by illuminating the eye E with infrared light, an infrared captured image is displayed. It is also possible to use an LED as a photographing light source.

The LCD (Liquid Crystal Display) 39 displays a fixation target and an eyesight measurement index. The fixation target is an index for fixing the eye E to be examined, and is used at the time of fundus photographing or OCT measurement.

A part of the light output from the LCD 39 is reflected by the half mirror 39A, reflected by the mirror 32, passes through the focusing lens 31 and the dichroic mirror 55, passes through the hole of the perforated mirror 21, and reaches the dichroic. The light passes through the mirror 46, is refracted by the objective lens 22, and is projected onto the fundus oculi Ef.

The fixation position of the eye E can be changed by changing the display position of the fixation target on the screen of the LCD 39. As the fixation position of the eye E, for example, a position for acquiring an image centered on the macular portion of the fundus oculi Ef, or a position for acquiring an image centered on the optic disc as in the case of a conventional fundus camera And a position for acquiring an image centered on the fundus center between the macula and the optic disc. It is also possible to arbitrarily change the display position of the fixation target.

Furthermore, the fundus camera unit 2 is provided with an alignment optical system 50 and a focus optical system 60 as in the conventional fundus camera. The alignment optical system 50 generates an index (alignment index) for performing alignment (alignment) of the apparatus optical system with respect to the eye E. The focus optical system 60 generates an index (split index) for focusing on the fundus oculi Ef.

The light (alignment light) output from the LED 51 of the alignment optical system 50 is reflected by the dichroic mirror 55 via the apertures 52 and 53 and the relay lens 54, passes through the hole of the aperture mirror 21, and reaches the dichroic mirror 46. And is projected onto the cornea of the eye E by the objective lens 22.

The cornea-reflected light of the alignment light passes through the objective lens 22, the dichroic mirror 46, and the hole, part of which passes through the dichroic mirror 55, passes through the focusing lens 31, and is reflected by the mirror 32. The light passes through 39A, is reflected by the dichroic mirror 33, and is projected onto the light receiving surface of the CCD image sensor 35 by the condenser lens. The light reception image (alignment index) by the CCD image sensor 35 is displayed on the display device 3 together with the observation image. The user performs alignment by performing the same operation as that of a conventional fundus camera. Further, the arithmetic control unit 200 may perform alignment by analyzing the position of the alignment index and moving the optical system (auto-alignment function).

When performing the focus adjustment, the reflecting surface of the reflecting rod 67 is obliquely provided on the optical path of the illumination optical system 10. The light (focus light) output from the LED 61 of the focus optical system 60 passes through the relay lens 62, is separated into two light beams by the split indicator plate 63, passes through the two-hole aperture 64, and is reflected by the mirror 65, The light is focused on the reflecting surface of the reflecting bar 67 by the condenser lens 66 and reflected. Further, the focus light passes through the relay lens 20, is reflected by the perforated mirror 21, passes through the dichroic mirror 46, is refracted by the objective lens 22, and is projected onto the fundus oculi Ef.

The fundus reflection light of the focus light is detected by the CCD image sensor 35 through the same path as the corneal reflection light of the alignment light. A light reception image (split index) by the CCD image sensor 35 is displayed on the display device 3 together with the observation image. The arithmetic control unit 200 analyzes the position of the split index and moves the focusing lens 31 and the focus optical system 60 to perform focusing as in the conventional case (autofocus function). Alternatively, focusing may be performed manually while visually checking the split indicator.

The dichroic mirror 46 branches the optical path for OCT measurement from the optical path for fundus imaging. The dichroic mirror 46 reflects light in a wavelength band used for OCT measurement and transmits light for fundus photographing. In this optical path for OCT measurement, a collimator lens unit 40, an optical path length changing unit 41, a galvano scanner 42, a focusing lens 43, a mirror 44, and a relay lens 45 are provided in this order from the OCT unit 100 side. It has been.

The optical path length changing unit 41 is movable in the direction of the arrow shown in FIG. 1, and changes the optical path length of the optical path for OCT measurement. This change in the optical path length is used for correcting the optical path length according to the axial length of the eye E or adjusting the interference state. The optical path length changing unit 41 includes, for example, a corner cube and a mechanism for moving the corner cube.

The galvano scanner 42 changes the traveling direction of light (signal light LS) passing through the optical path for OCT measurement. Thereby, the fundus oculi Ef can be scanned with the signal light LS. The galvano scanner 42 includes, for example, a galvano mirror that scans the signal light LS in the x direction, a galvano mirror that scans in the y direction, and a mechanism that drives these independently. Thereby, the signal light LS can be scanned in an arbitrary direction on the xy plane.

[OCT unit]
An example of the configuration of the OCT unit 100 will be described with reference to FIG. The OCT unit 100 is provided with an optical system for acquiring a tomographic image of the fundus oculi Ef. This optical system has the same configuration as a conventional spectral domain type OCT apparatus. That is, this optical system divides low-coherence light into reference light and signal light, and generates interference light by causing interference between the signal light passing through the fundus oculi Ef and the reference light passing through the reference optical path. It is configured to detect spectral components. This detection result (detection signal) is sent to the arithmetic control unit 200.

In the case of a swept source type OCT apparatus, a wavelength swept light source is provided instead of a light source that outputs a low coherence light source, and an optical member that spectrally decomposes interference light is not provided. In general, for the configuration of the OCT unit 100, a known technique according to the type of optical coherence tomography can be arbitrarily applied.

The light source unit 101 outputs a broadband low-coherence light L0. The low coherence light L0 includes, for example, a near-infrared wavelength band (about 800 nm to 900 nm) and has a temporal coherence length of about several tens of micrometers. Note that near-infrared light having a wavelength band invisible to the human eye, for example, a center wavelength of about 1040 to 1060 nm, may be used as the low-coherence light L0.

The light source unit 101 includes a super luminescent diode (Super Luminescent Diode: SLD), an LED, and an optical output device such as an SOA (Semiconductor Optical Amplifier).

The low coherence light L0 output from the light source unit 101 is guided to the fiber coupler 103 by the optical fiber 102, and is divided into the signal light LS and the reference light LR.

The reference light LR is guided by the optical fiber 104 and reaches an optical attenuator (attenuator) 105. The optical attenuator 105 automatically adjusts the amount of the reference light LR guided to the optical fiber 104 under the control of the arithmetic control unit 200 using a known technique. The reference light LR whose light amount has been adjusted by the optical attenuator 105 is guided by the optical fiber 104 and reaches the polarization adjuster (polarization controller) 106. The polarization adjuster 106 is, for example, a device that adjusts the polarization state of the reference light LR guided in the optical fiber 104 by applying a stress from the outside to the optical fiber 104 in a loop shape. The configuration of the polarization adjuster 106 is not limited to this, and any known technique can be used. The reference light LR whose polarization state is adjusted by the polarization adjuster 106 reaches the fiber coupler 109.

The signal light LS generated by the fiber coupler 103 is guided by the optical fiber 107 and converted into a parallel light beam by the collimator lens unit 40. Further, the signal light LS reaches the dichroic mirror 46 via the optical path length changing unit 41, the galvano scanner 42, the focusing lens 43, the mirror 44, and the relay lens 45. The signal light LS is reflected by the dichroic mirror 46, is refracted by the objective lens 22, and is applied to the fundus oculi Ef. The signal light LS is scattered (including reflection) at various depth positions of the fundus oculi Ef. The backscattered light of the signal light LS from the fundus oculi Ef travels in the same direction as the forward path in the reverse direction, is guided to the fiber coupler 103, and reaches the fiber coupler 109 via the optical fiber 108.

The fiber coupler 109 causes the backscattered light of the signal light LS and the reference light LR that has passed through the optical fiber 104 to interfere with each other. The interference light LC generated thereby is guided by the optical fiber 110 and emitted from the emission end 111. Further, the interference light LC is converted into a parallel light beam by the collimator lens 112, dispersed (spectral decomposition) by the diffraction grating 113, condensed by the condenser lens 114, and projected onto the light receiving surface of the CCD image sensor 115. Although the diffraction grating 113 shown in FIG. 2 is a transmission type, other types of spectroscopic elements such as a reflection type diffraction grating may be used.

The CCD image sensor 115 is a line sensor, for example, and detects each spectral component of the split interference light LC and converts it into electric charges. The CCD image sensor 115 accumulates this electric charge, generates a detection signal, and sends it to the arithmetic control unit 200.

In this embodiment, a Michelson type interferometer is used, but any type of interferometer such as a Mach-Zehnder type can be appropriately used. Further, in place of the CCD image sensor, another form of image sensor, for example, a CMOS (Complementary Metal Oxide Semiconductor) image sensor or the like can be used.

[Calculation control unit]
The configuration of the arithmetic control unit 200 will be described. The arithmetic control unit 200 analyzes the detection signal input from the CCD image sensor 115 and forms a tomographic image of the fundus oculi Ef. The arithmetic processing for this is the same as that of a conventional spectral domain type OCT apparatus.

The arithmetic control unit 200 controls each part of the fundus camera unit 2, the display device 3, and the OCT unit 100. For example, the arithmetic control unit 200 displays a tomographic image of the fundus oculi Ef on the display device 3.

As the control of the fundus camera unit 2, the arithmetic control unit 200 controls the operation of the observation light source 11, the imaging light source 15 and the LEDs 51 and 61, the operation control of the LCD 39, the movement control of the focusing lenses 31 and 43, and the reflector 67. Movement control, movement control of the focus optical system 60, movement control of the optical path length changing unit 41, operation control of the galvano scanner 42, and the like are performed.

Further, as control of the OCT unit 100, the arithmetic control unit 200 performs operation control of the light source unit 101, operation control of the optical attenuator 105, operation control of the polarization adjuster 106, operation control of the CCD image sensor 115, and the like.

The arithmetic control unit 200 includes, for example, a microprocessor, a RAM, a ROM, a hard disk drive, a communication interface, and the like, as in a conventional computer. A computer program for controlling the fundus analyzer 1 is stored in a storage device such as a hard disk drive. The arithmetic control unit 200 may include various circuit boards, for example, a circuit board for forming a tomographic image. The arithmetic control unit 200 may include an operation device (input device) such as a keyboard and a mouse, and a display device such as an LCD.

The fundus camera unit 2, the display device 3, the OCT unit 100, and the calculation control unit 200 may be configured integrally (that is, in a single housing) or separated into two or more housings. It may be.

[Control system]
The configuration of the control system of the fundus analysis apparatus 1 will be described with reference to FIGS. 3 and 4.

(Control part)
The control system of the fundus analysis apparatus 1 is configured around the control unit 210. The control unit 210 includes, for example, the aforementioned microprocessor, RAM, ROM, hard disk drive, communication interface, and the like. The control unit 210 is provided with a main control unit 211 and a storage unit 212.

(Main control unit)
The main control unit 211 performs the various controls described above. In particular, the main control unit 211 controls the focusing drive unit 31A, the optical path length changing unit 41, and the galvano scanner 42 of the fundus camera unit 2, and further the light source unit 101, the optical attenuator 105, and the polarization adjuster 106 of the OCT unit 100. To do.

The focusing drive unit 31A moves the focusing lens 31 in the optical axis direction. Thereby, the focus position of the photographic optical system 30 is changed. The main control unit 211 can also move an optical system provided in the fundus camera unit 2 in a three-dimensional manner by controlling an optical system drive unit (not shown). This control is used in alignment and tracking. Tracking is to move the apparatus optical system in accordance with the eye movement of the eye E. When tracking is performed, alignment and focusing are performed in advance. Tracking is a function of maintaining a suitable positional relationship in which the alignment and focus are achieved by causing the position of the apparatus optical system to follow the eye movement.

Further, the main control unit 211 performs a process of writing data to the storage unit 212 and a process of reading data from the storage unit 212.

(Memory part)
The storage unit 212 stores various data. Examples of data stored in the storage unit 212 include tomographic image data, fundus image data, and eye information to be examined. The eye information includes information about the subject such as patient ID and name, and information about the eye such as left and right eye information indicating whether the eye is the left eye or the right eye. The storage unit 212 stores various programs and data for operating the fundus analysis apparatus 1.

(Image forming part)
The image forming unit 220 forms image data of a two-dimensional tomographic image depicting the layer structure of the fundus oculi Ef based on the detection signal from the CCD image sensor 115. This process includes processes such as noise removal (noise reduction), filter processing, dispersion compensation, and FFT (Fast Fourier Transform) as in the conventional spectral domain type optical coherence tomography. In the case of another type of OCT apparatus, the image forming unit 220 executes a known process corresponding to the type. The control unit 211 causes the storage unit 212 to store image data of the two-dimensional tomographic image formed by the image forming unit 220.

The image forming unit 220 includes, for example, the circuit board described above. In this specification, “image data” and “image” based thereon may be identified.

(Image processing unit)
The image processing unit 230 performs various types of image processing and analysis processing on the tomographic image of the fundus oculi Ef. For example, the image processing unit 230 executes various correction processes such as image brightness correction. The image processing unit 230 performs various types of image processing and analysis processing on the image (fundus image, anterior eye image, etc.) obtained by the fundus camera unit 2.

The image processing unit 230 performs known image processing such as interpolation processing for interpolating pixels between two-dimensional tomographic images to form a three-dimensional tomographic image of the fundus oculi Ef. Note that the image data of a three-dimensional tomographic image means image data in which pixel positions are defined by a three-dimensional coordinate system. As image data of a three-dimensional tomographic image, there is image data composed of voxels arranged three-dimensionally. This image data is called volume data or voxel data. When displaying an image based on volume data, the image processing unit 230 performs a rendering process (such as volume rendering or MIP (Maximum Intensity Projection)) on the volume data, and views the image from a specific line-of-sight direction. A pseudo three-dimensional tomographic image is formed. This pseudo three-dimensional tomographic image is displayed on a display device such as the display unit 240A.

It is also possible to form stack data of a plurality of two-dimensional tomograms as image data of a three-dimensional tomogram. The stack data is image data obtained by three-dimensionally arranging a plurality of two-dimensional tomographic images obtained along a plurality of scanning lines based on the positional relationship of the scanning lines. That is, stack data is image data obtained by expressing a plurality of tomographic images originally defined by individual two-dimensional coordinate systems by one three-dimensional coordinate system (that is, by embedding them in one three-dimensional space). is there.

The control unit 211 causes the storage unit 212 to store the three-dimensional tomogram (volume data, pseudo three-dimensional tomogram, stack data, etc.) formed as described above.

The image processing unit 230 performs an analysis process for obtaining a drusen state by analyzing a tomographic image depicting the macular of the fundus oculi Ef and its surrounding region. As a configuration for that, the image processing unit 230 includes a layer region specifying unit 231, an approximate curve calculating unit 232, a protruding region specifying unit 233, a connected region specifying unit 234, and a form information generating unit 235.

(Layer region specific part)
The layer region specifying unit 231 specifies an image region corresponding to the retinal pigment epithelium layer in the tomographic image based on the pixel value of the pixel of the tomographic image of the fundus oculi Ef. This image area is called a layer area.

The layer region specifying unit 231 specifies the layer region by executing, for example, the same process as in Patent Document 5. This process will be briefly described. The layer area specifying unit 231 first performs preprocessing such as tone conversion processing, image enhancement processing, threshold processing, contrast conversion processing, binarization processing, edge detection processing, image averaging processing, image smoothing processing, and filter processing. Is applied to the tomographic image to clarify the layer structure depicted by the tomographic image.

Next, the layer region specifying unit 231 analyzes pixel values (for example, luminance values) of pixels constituting the pre-processed tomographic image one by one along the depth direction (z-axis direction) of the fundus oculi Ef, A pixel corresponding to a boundary position between adjacent layers is specified. At this time, a pixel corresponding to the boundary position of the layer can be specified using a filter (for example, a differential filter) having a spread only in the depth direction. Note that pixel edge detection may be performed using an area filter that extends in two directions, the depth direction and the direction orthogonal thereto.

The layer region specifying unit 231 specifies image regions corresponding to several layers of the fundus oculi Ef through such processing. Furthermore, the layer area specifying unit 231 specifies an image corresponding to the retinal pigment epithelium layer from among the specified image areas. An example of this processing will be described. In the tomographic image, it is known from a number of clinically acquired tomographic images of the fundus how many bright layers counted from the retinal surface side correspond to the retinal pigment epithelium layer. Therefore, the tomographic image to be analyzed first identifies the retina surface, counts the number of bright layers from the retina surface side, and the layer corresponding to the predetermined count value is the target layer region.

As another method for specifying the layer region, the layer region in the tomographic image to be analyzed may be specified based on the standard distance from the retina surface to the retinal pigment epithelium layer in the depth direction. In addition, since there is a difference in the brightness of each layer of the fundus oculi Ef in the tomographic image, the layer region can be specified in consideration of the difference. For example, when the retinal pigment epithelium layer is depicted Nth brightly among the brightly depicted layers, the Nth brightest image region corresponding to the layer identified in the tomographic image to be analyzed is specified. It can be a layer region. Note that the method of specifying the layer region is not limited to the one exemplified here, and any method may be used as long as the target layer region can be specified.

The tomographic image to be analyzed is a two-dimensional or three-dimensional tomographic image. When analyzing a two-dimensional tomographic image, the layer region is specified as a substantially curved image region (ignoring the thickness of the layer region). On the other hand, when analyzing a three-dimensional tomographic image, the layer region is specified as a substantially curved image region (ignoring the thickness of the layer region). Here, the case where a two-dimensional tomographic image is analyzed will be described in detail. The case of analyzing a three-dimensional tomographic image will be described later as a modified example.

The layer region specifying unit 231 generates information on the specified layer region, for example, position information (coordinate values) of the layer region in the tomographic image. Note that the layer region may be extracted from the tomographic image. Moreover, you may produce | generate the image information (for example, wire model etc.) showing the shape of the specified layer area | region. In any case, the layer region specifying unit 231 only needs to specify at least a layer region corresponding to the retinal pigment epithelium layer in the tomographic image.

(Approximate curve calculation part)
The identification result of the layer region (curved image region) in the tomographic image is input to the approximate curve calculation unit 232. Based on the shape of this layer region, the approximate curve calculation unit 232 obtains a curve that approximates this shape. This curve is called an approximate curve. The approximate curve represents the estimated shape of the retinal pigment epithelium layer when it is assumed that drusen does not exist in the cross section indicated by the tomographic image.

When there is no drusen in the cross section, the specified layer region is depicted in the tomographic image as a curve convex in the depth direction at least globally. On the other hand, when drusen exists in the cross section, irregularities corresponding to drusen are drawn in the specified layer region. The approximate curve represents the global shape of the layer region ignoring such irregularities.

In order to obtain such an approximate curve, the approximate curve calculation unit 232 is provided with a feature site specifying unit 232a, a feature site interpolation unit 232b, a free curve calculation unit 232c, and a correction unit 232d. Further, the correction unit 232d includes a set of the straight part specifying unit 232e and the first deforming unit 232f, a set of the curved part specifying unit 232g and the second deforming unit 232h, and a set of the protrusion determining unit 232i and the third deforming unit 232j. And are provided.

(Characteristic specific part)
The feature part specifying unit 232a specifies a plurality of feature parts based on the shape of the layer region based on the pixel values of the pixels in the specified layer region. An example of this processing will be described with reference to FIGS. 5A to 5C.

First, as shown in FIG. 5A, the characteristic part specifying unit 232 a specifies the deepest part P0 in the layer region 300 in the depth direction (+ z direction) based on the shape of the layer region 300. This process can be executed, for example, by referring to the coordinate value of each pixel in the layer region 300, specifying the pixel having the maximum z coordinate value, and setting it to the deepest part P0. As a different method, in the tomographic image to be analyzed, a straight line orthogonal to the depth direction is moved from the + z direction to the −z direction, and the position in the layer region that first contacts the straight line is set as the deepest part. Also good. The deepest part P0 specified in this way is a characteristic part of the layer region 300.

Next, the characteristic part specifying unit 232a obtains a straight line passing through the deepest part P0 and in contact with the layer region 300, and a contact point between the straight line and the layer region 300 is set as a characteristic part. A specific example of this process will be described. As shown in FIG. 5B, the straight line L passing through the deepest part P0 is rotated around the deepest part P0. FIG. 5B shows a case where the straight line L is rotated clockwise r.

When the straight line L is rotated in this way, the straight line L contacts the layer region 300 at a certain stage as shown in FIG. 5C. The straight line L at this time corresponds to the above-mentioned “straight line passing through the deepest part P0 and in contact with the layer region 300”. The contact P1 is a characteristic part of the layer region 300. Since all the other characteristic parts are located on the −z side with respect to the deepest part P0, for example, it is sufficient to rotate the straight line L from a position that passes through the deepest part P0 and is orthogonal to the z coordinate axis. In addition, by rotating the straight line L in the reverse direction (counterclockwise), it is possible to specify a feature part located on the opposite side of the feature part P1 with respect to the deepest part P0.

By repeating such processing, a plurality of characteristic portions Pj (j = 0, 1, 2,..., J) of the layer region 300 are specified. Note that, for example, the following two methods are conceivable as a method of repeating the above processing. Of course, it is possible to specify a plurality of characteristic portions Pj by other methods.

As a first iterative method, the straight line L that always passes through the deepest part P0 can be considered, and the contact point between the straight line L and the layer region 300 can be specified sequentially. In that case, the first contact point, the second contact point, the third contact point,... According to the rotation of the straight line L are sequentially specified as the contact point (characteristic part).

As a second iteration method, the rotation center of the straight line L can be changed sequentially. That is, first, the first contact point is specified by rotating the straight line L around the deepest part P0. Next, the second contact point is specified by rotating the straight line L similarly around the first contact point. Subsequently, the straight line L is similarly rotated around the second contact point to specify the third contact point. In this way, a plurality of contact points (characteristic portions) are specified sequentially.

The number of characteristic parts specified as described above is arbitrary, but the accuracy of the following processing improves as the number increases. On the other hand, the resource required for processing increases as the specific number of feature parts increases.

(Feature interpolation unit)
The feature part interpolation unit 232b performs a process of adding a feature part of the layer region. This process is not always executed, for example, but is executed as necessary. Hereinafter, two types of interpolation processing will be described.

The first interpolation process follows the request for the free curve calculation process in the subsequent stage. That is, in order to obtain a free curve based on a feature part, there is a minimum number of feature parts necessary for solving the equation. This interpolation process is executed when the number of feature parts specified by the feature part specifying unit 232a is less than the minimum number. Note that the minimum number of characteristic portions necessary for the calculation of the free curve is set in advance according to the type of free curve to be obtained. As a specific example, when the free curve is a cubic spline curve, the minimum number is set to 4. With the above preparation, the first interpolation process is performed as follows, for example.

First, the feature part interpolation unit 232b determines whether the number of feature parts specified by the feature part specifying unit 232a is less than a predetermined minimum number. When the specified number is equal to or greater than the minimum number, the first interpolation process is not executed.

When the specified number is less than the minimum number, the feature part interpolation unit 232b adds new feature parts by the number obtained as a difference between the minimum number and the specified number. As the new feature portion, for example, a point closest to the layer region (the closest point in the depth direction, that is, the z direction) is selected on a broken line formed by connecting the feature portions obtained up to the present time. . That is, the first feature part added is the point closest to the layer region on the polygonal line formed by connecting the feature parts specified by the feature part specifying unit 232a. When two or more feature parts are added, the i (≧ 2) th feature part is added to the feature part specified by the feature part specifying unit 232a and the feature part added up to the (i−1) th part. It is the point closest to the layer region on the polygonal line formed by connecting.

In addition, when only one feature part is specified by the feature part specifying unit 232a, a broken line as described above cannot be formed. In this case, the feature part interpolation unit 232b adds an arbitrary point on the layer region, for example, an intersection of the end (edge) of the frame (drawing frame) of the tomographic image and the layer region as a new feature part. be able to. This process can also be applied when the layer region protrudes at the end of the frame. The above is an example of the first interpolation processing.

The second interpolation process will be described. This interpolation processing complies with a request for accuracy (accuracy) of approximation of a free curve. Specifically, if the interval between two adjacent characteristic parts is too wide, an error between the layer region and the approximate curve between the characteristic parts becomes large. The second interpolation processing is to add a new feature portion between the feature portions when the interval between the feature portions is wide. An example of this processing will be described below. If only one feature part is specified by the feature part specifying unit 232a, an arbitrary point on the layer area (for example, the intersection of the frame end and the layer area) is newly added as in the first interpolation process. First added as a special feature.

First, the feature part interpolation unit 232b obtains the distance between two adjacent feature parts for the feature part specified by the feature part specifying unit 232a. This distance is, for example, a distance in a cross-sectional direction (that is, the scanning direction of the signal light LS) orthogonal to the depth direction (z direction). Note that it may be a spatial distance between two characteristic parts in the cross section indicated by the tomographic image.

Next, the characteristic part interpolation unit 232b determines whether the obtained distance is equal to or greater than a predetermined value. If the distance is less than the predetermined value, the second interpolation process for the pair of feature parts is not executed, and the process proceeds to a process for another pair as necessary.

On the other hand, when the distance between the two feature parts is equal to or greater than the predetermined value, the feature part interpolation unit 232b adds a new feature part between the two feature parts. The position where the new feature part is added is, for example, an intermediate position between the two feature parts. Further, the additional position may be determined in consideration of factors such as the relative positions of the two characteristic parts in the z direction and the positions of other characteristic parts. In addition, when the distance between two feature parts is twice or more the predetermined value, two or more new feature parts may be added between these feature parts. The feature part interpolation unit 232b repeatedly performs the above-described interpolation processing until the distance between all adjacent feature part pairs becomes less than a predetermined value. The above is an example of the second interpolation processing.

(Free curve calculation part)
The free curve calculation unit 232c obtains a free curve based on a plurality of feature parts. The plurality of feature parts are a feature part specified by the feature part specifying unit 232a and a feature part added by the feature part interpolation unit 232b as necessary.

A free curve is generally a smooth curve defined to pass through several points on a plane in a predetermined order. Examples of free curves are spline curves and Bezier curves. In this embodiment, a spline curve, particularly a cubic spline curve is used as the free curve. Note that a spline curve is generally a smooth curve that passes through a plurality of given control points, and is a curve obtained using individual polynomials for sections (segments) having two adjacent control points at both ends. It is. The nth order spline curve uses an nth order polynomial. The n-th order Bezier curve is generally an n-1th order curve obtained from n control points. In this embodiment, the calculation of the free curve is performed using each characteristic part as a control point.

(Correction part)
The correction unit 232d corrects the free curve obtained by the free curve calculation unit 232c. There are various types of correction processing. Here, three types of correction processing will be described. The first correction process is performed by the straight part specifying unit 232e and the first deforming unit 232f. The second correction process is performed by the curved part specifying unit 232g and the second deforming unit 232h. The third correction process is performed by the protrusion determination unit 232i and the third deformation unit 232j. These correction processes can be said to correct mathematically obtained free curves based on medical knowledge.

It is assumed that the free curve obtained by the free curve calculation unit 232c or the curve obtained by performing at least one of the first to third correction processes as necessary does not include drusen in the cross section. In this case, the approximate curve represents the estimated shape of the retinal pigment epithelium layer.

(First correction process: straight part specifying unit, first deforming unit)
The first correction process will be described. In the first correction process, when a part of the layer region is (substantially) linear, the portion of the free curve is corrected. Due to the characteristics of the calculation of the free curve, the free curve is arranged in the depth direction (+ z direction) and convex in the depth direction (+ z direction) in the region where the layer region is linear. There is. When such a free curve is adopted as an approximate curve, there is a risk that this linear portion will be detected as drusen. The first correction process is for avoiding such a situation. Hereinafter, an example of this correction processing will be described.

The linear part specifying unit 232e specifies a substantially linear part in the layer region specified by the layer region specifying unit 231. This process can be performed, for example, by calculating a slope (differential value) at each point in the layer region and searching for a section where the slope is substantially constant. Note that “the slope is substantially constant” includes not only a section where the slope is completely constant but also a case where the change in the slope is less than a predetermined threshold. The part of the layer region specified in this way is called a straight part.

The first deformation unit 232f determines whether or not the free curve is located in the depth direction (+ z direction) from the straight line portion. This process is performed, for example, by comparing the z-coordinate value of the straight line portion with the z-coordinate value of the free curve portion corresponding to the straight line portion. When it is determined that the free curve is located in the reverse direction (−z direction) of the depth direction with respect to the straight line portion, the first correction process is not executed.

When it is determined that the free curve is located in the depth direction from the straight line part, the first deforming unit 232f deforms the free curve so that the corresponding part of the free curve matches the position of the straight line part. As the first processing example, the corresponding part and its vicinity can be modified so that the corresponding part of the free straight line is replaced with the straight part. Specifically, for example, a new control point is set at both end positions of the straight part, and a new free curve on one or both sides of the corresponding part is calculated taking this new control point into account, and the straight part is obtained. Adopted as part of approximate curve. According to this processing, an approximate curve including a part (substantially) a straight line is obtained.

As a second processing example, one or more control points are newly set on the straight line portion, and a new free curve is obtained by taking these control points into consideration. According to this process, the straight part is approximated by a free curve. The number of newly added control points can be arbitrarily set based on, for example, the length of the straight line part.

(Second correction process: curve part specifying part, second deformation part)
The second correction process will be described. In the second correction process, when the free curve is positioned in the reverse direction (−z direction) of the depth direction with respect to the layer region, the relevant part of the free curve is corrected. As described above, the approximate curve obtained based on the free curve is for estimating the position of the layer region when it is assumed that drusen does not exist. Therefore, it is preferable that the approximate curve is located at the same position as the layer region or in the depth direction (+ z direction) from the layer region. In the second correction process, a portion of a free curve that does not satisfy this condition is transformed so as to satisfy this condition. Hereinafter, an example of this correction processing will be described.

The curved part specifying unit 232g specifies a part located in the reverse direction (−z direction) of the depth direction with respect to the layer region in the free curve. This process can be easily performed, for example, by comparing the z coordinate value of the free curve and the z coordinate value of the layer region.

The second deforming unit 232h deforms the free curve so that the part of the free curve specified by the curve part specifying unit 232g matches the position of the layer region. Similar to the first correction process, this process may be a replacement of the deformation with a target (layer region) or a free curve calculation that takes into account a new control point based on the target.

(Third correction processing: protrusion determination unit, third deformation unit)
The third correction process will be described. In the third correction process, when the layer region protrudes at the frame end of the tomographic image, the free curve of the protruding portion is corrected.

FIG. 6A shows an example where the layer region protrudes at the end of the frame. The layer region 300 protrudes in the direction opposite to the depth direction (−z direction) at the right end of the frame F of the tomographic image. Furthermore, it is assumed that points 310 and 320 are obtained as characteristic portions of the layer region 300. Here, the characteristic part 320 is specified by the characteristic part specifying unit 232a. Also, the feature part 310 that is the intersection of the layer region 300 and the end of the frame F is added by the feature part interpolation unit 232b.

6B indicates a free curve based on these characteristic portions 310 and 320 and the like. Since the free curve 400 passes through the two characteristic portions 310 and 320, as shown in FIG. 6B, the free curve 400 is inclined in the protruding direction (−z direction) of the protruding portion. That is, the feature part 310 set (for convenience) at the end of the frame F affects the shape of the free curve 400, and as a result, the protrusion amount of the protrusion part cannot be measured accurately. In order to cope with such a situation, a third correction process is executed. Hereinafter, an example of the third correction process will be described.

The protrusion determining unit 232i determines whether or not the layer region protrudes in the reverse direction (−z direction) of the depth direction in the vicinity of the end of the tomographic frame. This processing can be executed, for example, by calculating the slope (differential value) at each point of the layer region or the free curve (at least in the vicinity of the end of the frame) and obtaining its shape.

As another process, when the feature part interpolation unit 232b adds a feature part at the intersection of the layer region and the frame end, the new feature part (310) is more than the feature part (320) adjacent thereto. When set in the −z direction, it is also possible to determine that the layer region protrudes in the direction opposite to the depth direction (−z direction) in the vicinity of the frame end of the tomographic image.

When it is determined that the layer region protrudes in the vicinity of the frame end, the third deforming portion 232j replaces the portion of the free curve corresponding to the protruding portion with an extension line of the free curve from the center side of the frame. To deform the free curve. An example of this processing will be described below.

Refer to FIG. 6C. First, the third deforming portion 232j sets a control point (reference control point) 410 at a predetermined position on the center side of the frame with respect to the feature portion 320 adjacent to the feature portion 310 adjacent to the feature portion 310 set at the intersection of the layer region and the frame end. Set. As the reference control point 410, for example, an intermediate point in the horizontal direction of the frame is used.

Next, the third deforming unit 232j sets a predetermined number of control points between the reference control point 410 and the feature part 320 so that the reference control point 410 and the feature part 320 are equally divided. Thereby, a set of points including a plurality of control points including the reference control point 410 and the characteristic part 320 is obtained. The number of points included in this set is equal to or greater than the minimum number of characteristic parts necessary for the calculation of the free curve. Further, the interval between adjacent points can be set relatively wide. In the example illustrated in FIG. 6C, a set including three control points 410, 420, and 430 and a characteristic portion 320 is set.

Subsequently, the third deformation unit 232j obtains a free curve having a plurality of points included in the obtained set as control points. By obtaining a cubic spline curve that passes through the four control points 320, 410, 420, and 430 shown in FIG. 6C and reaches the end of the frame, an estimated curve 500 shown in FIG. 6D is obtained. The estimated curve 500 is a free curve defined at and near the protruding portion of the layer region 300, and indicates the estimated position of the baseline for measuring the protruding amount of the protruding portion.

Next, the third deforming unit 232j includes a portion of the free curve 400 on the frame center side from the feature portion 320 (interpolation curve) 400a and a portion of the estimated curve 500 on the frame end side of the feature portion 320 (extrapolation). Curve) 500a is connected at the position of the characteristic part 320 (see FIG. 6E). The curve thus obtained is used as a deformation result of the free curve 400.

Other processing examples will be described. First, the third deforming portion 232j is a frame that is a predetermined distance (for example, very close to the adjacent feature portion) from the feature portion (320) adjacent to the feature portion (310) set at the intersection of the layer region and the frame end. The inclination of the layer area at the center position (reference position) is calculated. Next, the third deforming unit 232j obtains a line segment connecting the reference position and the frame end and having the calculated inclination. And the 3rd deformation | transformation part 232j substitutes the site | part of the free curve corresponding to a protrusion site | part, ie, the site | part between the characteristic site | part (310) equivalent to an intersection, and a reference position with this line segment. The correction line segment 510 shown in FIG. 6F corresponds to this.

As another process, it is also possible to set a new feature part at a position on the end of the frame or an arbitrary position in the projecting part and obtain a new free curve by taking this new feature part into consideration. is there.

(Projection area specific part)
The protruding area specifying unit 233 specifies the protruding area in the tomographic image based on the approximate curve obtained by the approximate curve calculating unit 232 and the layer area. The protruding region is an image region in which the approximate curve is located in the depth direction (+ z direction) of the fundus oculi Ef with respect to the layer region, and the distance between the approximate curve and the layer region in the depth direction is equal to or greater than a predetermined threshold. . In other words, the protruding region indicates a region where the layer region is greatly protruded in the −z direction with respect to the approximate curve.

Note that the entire image region protruding in the −z direction with respect to the approximate curve can be specified as the protruding region. However, in this embodiment, in order to avoid natural unevenness and noise of the retinal pigment epithelium layer, approximation is performed. By detecting only the portion protruding from the curve by a predetermined distance or more, the specified accuracy of the protruding region is improved. For this purpose, the protruding area specifying unit 233 is provided with a distance calculating unit 233a, a distance determining unit 233b, and an image area specifying unit 233c.

(Distance calculation unit)
The distance calculation unit 233a calculates the distance in the depth direction between each point on the approximate curve and the layer region. This process does not need to be performed for all points (pixels) on the approximate curve, and may be performed at predetermined pixel intervals (for example, every 5 pixels). In the distance calculation process, for example, the number of pixels between a point (pixel) on the approximate curve and a corresponding point (pixel) on the layer area is counted, and the interval between adjacent pixels is set as a unit distance and the count result. Can be done on the basis. Alternatively, it may be obtained based on the measurement magnification of the image and the distance in the image between the pixels of the distance measurement target. The distance calculated by the distance calculation unit 233a may be a distance obtained by converting a distance in the image (a distance defined in the xyz coordinate system or a pixel interval) into a distance in real space. The distance may be used as it is.

(Distance judgment part)
The distance determination unit 233b determines whether each distance calculated by the distance calculation unit 233a is equal to or greater than a predetermined threshold. This threshold is set in advance based on, for example, many clinical cases. Further, the threshold value can be set in consideration of the measurement accuracy of the apparatus.

The distance determination unit 233b gives identification information (for example, a flag or a tag) to a point (pixel) on the approximate curve where the distance is determined to be greater than or equal to a predetermined threshold.

(Image area identification part)
The image region specifying unit 233c is sandwiched between a layer region and a set of pixels on the approximate curve to which identification information is given by the distance determination unit 233b, that is, a set of points on the approximate curve whose distance is determined to be equal to or greater than a predetermined threshold. The specified image area is specified as a target protruding area.

FIG. 7 shows an example of the protruding area specified in this way. The protruding region 600 is an image region sandwiched between the layer region 300 and the approximate curve 400, and is an image region in which the distance between the layer region 300 and the approximate curve 400 is equal to or greater than a predetermined threshold value. As shown in FIG. 7, at this stage, in the image region sandwiched between the layer region 300 and the approximate curve 400, the portion of the base close to the feature parts 330 and 340 that are the common points (the distance is less than a predetermined threshold value). Is not determined as a protruding region. In the range shown in FIG. 7, there is only one peak in the layer region, but when there are two or more peaks, there may be a portion that is not determined as a protruding region other than the vicinity of the characteristic part. is there.

(Linked area identification part)
The connection area specifying unit 234 specifies the connection area including the protruding area specified by the protruding area specifying part 233 and surrounded by the approximate curve and the layer area. This process is executed by, for example, a labeling process for pixels. This labeling process is, for example, a labeling process of 4 connections (near 4) or 8 connections (near 8).

FIG. 8 shows a connected area specified when the above processing is applied to the example of FIG. The protruding region 600 shown in FIG. 7 is an image region obtained by excluding a portion where the distance between the layer region 300 and the approximate curve 400 is less than a predetermined threshold from the image region sandwiched between the layer region 300 and the approximate curve 400. is there. The connection area specifying unit 234 specifies the connection area including the protruding area 600 and surrounded by the approximate curve 400 and the layer area 300, that is, the connection area indicated by reference numeral 700 in FIG.

In the stage shown in FIG. 7, the protruding region 600 excluding the skirt portion close to the feature parts 330 and 340 is specified, but in the step shown in FIG. 8, the connecting region 700 including the skirt portion is specified. Is done. By performing such stepwise processing, the entire image region considered to correspond to drusen is preferably detected.

In the above example, after specifying a protruding region having a large protruding amount, a connected region including each protruding region is specified. However, similar results can be obtained by other processes. For example, each of the connected regions sandwiched between the layer region and the approximate curve is specified, and a portion with a large protrusion amount for each connected region, that is, a portion where the distance between the layer region and the approximate curve in the depth direction is equal to or greater than a predetermined threshold By determining whether or not exists, it is possible to specify the target connected region. Such modifications are also included in the gist of the present invention.

(Form information generator)
The form information generation unit 235 generates form information representing the form of the connected area specified by the connected area specifying unit 234. The form information includes, for example, the number, size, distribution state, and the like of the identified connected areas. The form information generation unit 235 includes a nipple region determination unit 235a, a distribution image formation unit 235b, a count unit 235c, and a size calculation unit 235d.

(Nipple area determination unit)
The nipple region determination unit 235a analyzes the tomographic image and determines whether the tomographic image includes a nipple region corresponding to the optic nerve head of the fundus oculi Ef. The optic disc is depicted in a tomographic image as a dent in the depth direction (+ z direction) in the fundus oculi Ef. The nipple region determination unit 235a determines whether or not such a shape is depicted in a tomographic image. Further, when analyzing a tomographic image in which the deep part (choroid or sclera) of the fundus oculi Ef is depicted, it is determined whether or not the characteristic shape of the tissue located in the deep part of the optic nerve head is depicted in the tomographic image. You may do it. An example of such determination processing will be described below.

The nipple region determination unit 235a analyzes the tomographic image, identifies a feature layer region corresponding to a predetermined feature layer of the fundus oculi Ef, and determines whether the nipple region is included based on the shape of the feature layer region. The characteristic layer to be identified is an arbitrary layer tissue constituting the fundus oculi Ef, that is, an arbitrary layer tissue constituting the retina, a choroid, or a sclera. The layer structure constituting the retina includes the inner boundary membrane, nerve fiber layer, ganglion cell layer, inner reticular layer, inner granular layer, outer reticular layer, outer granular layer, outer boundary membrane, photoreceptor layer, retinal pigment epithelial layer There is. In addition, it is desirable to employ | adopt as a characteristic layer the layer structure | tissue in which the characteristic shape of an optic disc is reflected clearly. In addition, it is desirable to employ a layer structure that is clearly depicted in a tomographic image as a feature layer. As such a layered structure, there is an inner boundary film that forms a boundary with the vitreous body in the fundus oculi Ef. An image area corresponding to the inner boundary film is called an inner boundary film area.

FIG. 9 shows an example of a tomographic image in which a part of the optic nerve head is depicted. In the tomographic image G, the inner boundary film region 800 is shown together with the layer region 300 and the approximate curve 400. It is assumed that the depressed portion 810 in the + z direction at the right end portion of the inner boundary membrane region 800 is caused by the depressed shape of the optic nerve head. On the other hand, as shown in FIG. 9, since the retinal pigment epithelium layer is curved in the −z direction in the vicinity of the optic disc, this portion may be detected as the connection region 700.

The nipple region determination unit 235a determines whether or not there is a portion depressed in the depth direction (+ z direction) in the inner boundary membrane region, and determines that the nipple region is included when it is determined that the depressed portion exists. As an example of this processing, the nipple region determination unit 235a obtains the amount of depression in the + z direction of the inner boundary membrane region 800 at the frame end of the tomographic image G. This amount of depression is calculated, for example, as the difference between the point located most in the −z direction and the point located most in the + z direction in the inner boundary film region 800. When the amount of displacement is greater than or equal to a predetermined threshold, the nipple region determination unit 235a determines that the tomogram G includes a nipple region. As another process, it is determined whether or not the inner boundary membrane region 800 has a curved portion (for example, a portion curved with a curvature equal to or greater than a predetermined value), and when the curved portion exists, it is determined that the nipple region is included. Is also possible.

In the determination of the nipple region, it is possible to perform processing by considering whether the eye E is the left eye or the right eye. Generally, the measurement target for OCT measurement of the fundus oculi Ef is the optic nerve head or the macula and its vicinity. It is not particularly necessary to determine the nipple area in the tomographic image in which the optic nerve head is a measurement target. On the other hand, in the tomographic image whose measurement target is the macula and its vicinity, if the eye to be examined is the left eye, the optic nerve head may be depicted near the left end of the frame, and the eye to be examined may be the right eye. For example, the optic disc may be depicted near the right edge of the frame. In consideration of such matters, the following configuration can be applied.

It is assumed that the storage unit 212 stores left and right eye information indicating whether the eye E is the left eye or the right eye. The left and right eye information may be manually input by the user or may be automatically acquired from an electronic medical record or the like. Further, when the OCT measurement is performed, it is automatically determined whether the eye E is the left eye or the right eye based on the positional relationship between the device optical system and the chin rest (forehead), and the determination result is The left and right eye information can also be stored in association with the tomographic image.

The nipple region determination unit 235a recognizes whether the eye E is the left eye or the right eye based on the left and right eye information. When the eye E is the left eye, the nipple area determination unit 235a determines whether or not the nipple area is included by analyzing at least the vicinity of the left end of the frame of the tomographic image. On the other hand, when the eye E is the right eye, the nipple region determination unit 235a determines whether or not the nipple region is included by analyzing at least the vicinity of the right end of the frame of the tomographic image.

In this way, by switching the processing depending on whether the eye E is the left eye or the right eye, the amount of data provided for the processing can be reduced, so that the processing time is shortened and the processing resources are reduced. Can be achieved.

Another example of processing for determining whether or not a nipple region is included in a tomographic image will be described. In the OCT measurement, information (scanning position information) indicating a region (scanning line) scanned with the signal light LS is obtained. In addition, a fundus image is obtained in real time during measurement. Based on the scanning position information and the fundus image, the nipple region determination unit 235a determines whether the scanning line corresponding to the tomographic image passes through at least a part of the optic nerve head, that is, at least a part of the optic nerve head is depicted in the tomographic image. Can be determined. By such determination processing, it is possible to determine whether the nipple region is included in the tomographic image.

When the nipple region determination unit 235a determines that the tomographic image includes the nipple region, the morphological information generation unit 235 excludes the connected region located in the vicinity of the nipple region from the connected regions specified by the connected region specifying unit. Then, form information is generated. Here, the excluded connection region is, for example, a connection region located closest to the nipple region. Moreover, you may make it exclude the connection area | region included in the range away only predetermined distance from the nipple area | region. Thereby, it is possible to prevent erroneous detection of the curved portion of the layer region in the vicinity of the optic nerve head as drusen.

(Distribution image forming unit)
The distribution image forming unit 235b forms a distribution image representing the distribution state of the connected area specified by the connected area specifying unit 234. For example, a distribution image representing the distribution of connected regions in a single tomographic image can be formed. In this process, for example, the connected area is presented in a mode (display color, display brightness, etc.) different from other image areas.

In addition, when a connected region is specified for each of a plurality of tomographic images, a distribution image representing the distribution state of the connected region in the xy plane orthogonal to the depth direction can be formed. Hereinafter, an example of processing for forming a distribution image in the xy plane will be described.

A plurality of tomographic images are obtained, for example, by executing a three-dimensional scan described later. The three-dimensional scan is a scan form in which the irradiation position of the signal light LS is scanned along a plurality of linear scanning lines arranged in the x direction and in the y direction, for example. A plurality of tomographic images in a cross section along each scanning line are obtained by the three-dimensional scanning.

The distribution image forming unit 235b forms a distribution image of the connected area in the xy plane based on the connected area specified for each of these tomographic images. In each tomographic image, each connected region is an image region that extends in the x direction (scan line direction) and the z direction. The plurality of tomographic images are arranged in the y direction. When a plurality of tomographic images are arranged in the y direction, the connected regions in each tomographic image are combined to obtain a two-dimensional distribution (distribution in the xy plane) of the connected regions.

At this time, if the connected regions in the adjacent tomographic images are adjacent in the y direction, the pixels between these connected regions may be set as the connected regions. This processing is particularly effective when the interval between adjacent tomographic images (scan line interval) is sufficiently narrow.

The distribution image forming unit 235b forms a distribution image by expressing the pixel values of the pixels corresponding to the connected region and the other pixels, for example, differently. As an example, a binary image can be formed by distinguishing and expressing connected regions and other regions by binary values, which can be used as a distribution image.

An example of a distribution image formed in this way is shown in FIG. The distribution image 900 represents the distribution state of the connected region T when the fundus oculi Ef is viewed from the incident direction (−z direction) of the signal light LS. The connection region T includes a plurality of connection regions Tk (k = 1 to K). The distribution image 900 is formed based on a plurality of tomographic images having a plurality of scanning lines Ri (i = 1 to m) as cross sections.

(Counting part)
The counting unit 235c counts the number of connected areas specified by the connected area specifying unit 234. In this process, for example, the numbers 1, 2,. And the maximum number assigned is used as the number of connected regions. In the labeling process executed in the process for specifying the connected area, the process for counting the connected areas may be performed in parallel.

(Size calculator)
The size calculating unit 235d calculates the size of each connected area specified by the connected area specifying unit 234. Examples of the index representing the size of the connected region include area, diameter (diameter, radius, etc.), volume, and the like. Hereinafter, an example of the size calculation process of the connected area will be described.

First, a processing example for obtaining the area of the connected region will be described. Each connected region is a set of a plurality of pixels determined to be connected. An area (unit area) is set in advance for each pixel. This unit area may be arbitrarily set for the distribution image or tomographic image. For example, in consideration of the measurement magnification, the area in the real space corresponding to one pixel can be set as the unit area. The size calculation unit 235d calculates the product of the number of pixels included in each connected region and the unit area to obtain the area of the connected region.

Next, an example of processing for obtaining the diameter of the connected region will be described. The size calculator 235d first calculates the area as described above. The size calculation unit 235d sets the diameter (or radius) of the circle having this area as the diameter of the connection region. It is also possible to search for the longest line segment included in the connection area and adopt the length of this line segment as the diameter of the connection area. In addition to these, any distance that can characterize the connection region can be adopted as the diameter.

Next, an example of processing for obtaining the volume of the connected area will be described. As described above, the distance in the depth direction between each point on the approximate curve and the layer region has already been calculated by the distance calculation unit 233a. The size calculator 235d calculates the volume of the connected region by integrating the distance over each connected region.

Note that the size calculation method is not limited to the above. Further, the index (dimension) indicating the size is not limited to the above.

The image processing unit 230 that functions as described above includes, for example, the aforementioned microprocessor, RAM, ROM, hard disk drive, circuit board, and the like. In a storage device such as a hard disk drive, a computer program for causing the microprocessor to execute the above functions is stored in advance.

(User interface)
The user interface 240 includes a display unit 240A and an operation unit 240B. The display unit 240A includes the display device of the arithmetic control unit 200 and the display device 3 described above. The operation unit 240B includes the operation device of the arithmetic control unit 200 described above. The operation unit 240B may include various buttons and keys provided on the housing of the fundus analysis apparatus 1 or outside. For example, when the fundus camera unit 2 has a housing similar to that of a conventional fundus camera, the operation unit 240B may include a joystick, an operation panel, or the like provided on the housing. The display unit 240 </ b> A may include various display devices such as a touch panel provided on the housing of the fundus camera unit 2.

Note that the display unit 240A and the operation unit 240B do not need to be configured as individual devices. For example, a device in which a display function and an operation function are integrated, such as a touch panel, can be used. In that case, the operation unit 240B includes the touch panel and a computer program. The operation content for the operation unit 240B is input to the control unit 210 as an electrical signal. Further, operations and information input may be performed using a graphical user interface (GUI) displayed on the display unit 240A and the operation unit 240B.

[Signal light scanning and tomographic images]
Here, scanning of the signal light LS and a tomographic image will be described.

Examples of the scanning mode of the signal light LS by the fundus analyzing apparatus 1 include a horizontal scan, a vertical scan, a cross scan, a radiation scan, a circle scan, a concentric scan, and a spiral (vortex) scan. These scanning modes are selectively used as appropriate in consideration of the observation site of the fundus, the analysis target (such as retinal thickness), the time required for scanning, the precision of scanning, and the like.

The horizontal scan is to scan the signal light LS in the horizontal direction (x direction). The horizontal scan also includes an aspect in which the signal light LS is scanned along a plurality of horizontal scanning lines arranged in the vertical direction (y direction). In this aspect, it is possible to arbitrarily set the scanning line interval. In addition, the aforementioned three-dimensional tomographic image can be formed by sufficiently narrowing the interval between adjacent scanning lines (three-dimensional scanning). The same applies to the vertical scan.

The cross scan scans the signal light LS along a cross-shaped trajectory composed of two linear trajectories (straight trajectories) orthogonal to each other. In the radiation scan, the signal light LS is scanned along a radial trajectory composed of a plurality of linear trajectories arranged at a predetermined angle. The cross scan is an example of a radiation scan.

The circle scan scans the signal light LS along a circular locus. In the concentric scan, the signal light LS is scanned along a plurality of circular trajectories arranged concentrically around a predetermined center position. A circle scan is an example of a concentric scan. In the spiral scan, the signal light LS is scanned along a spiral (spiral) locus while the radius of rotation is gradually reduced (or increased).

Since the galvano scanner 42 is configured to scan the signal light LS in directions orthogonal to each other, the signal light LS can be scanned independently in the x direction and the y direction, respectively. Further, by simultaneously controlling the directions of the two galvanometer mirrors included in the galvano scanner 42, the signal light LS can be scanned along an arbitrary locus on the xy plane. Thereby, various scanning modes as described above can be realized.

By scanning the signal light LS in the above-described manner, a tomographic image on a plane stretched by the direction along the scanning line (scanning locus) and the fundus depth direction (z direction) can be acquired. In particular, when the interval between scanning lines is narrow, the above-described three-dimensional tomographic image can be acquired.

The region on the fundus oculi Ef to be scanned with the signal light LS as described above, that is, the region on the fundus oculi Ef to be subjected to OCT measurement is called a scanning region. The scanning area in the three-dimensional scan is a rectangular area in which a plurality of horizontal scans are arranged. The scanning area in the concentric scan is a disk-shaped area surrounded by the locus of the circular scan with the maximum diameter. In addition, the scanning area in the radial scan is a disk-shaped (or polygonal) area connecting both end positions of each scan line.

[Operation]
The operation of the fundus analysis apparatus 1 will be described. FIG. 11 illustrates an example of the operation of the fundus analysis apparatus 1.

(S1: OCT measurement)
A tomographic image of the fundus oculi Ef is obtained by performing OCT measurement of the eye E.

(S2: Identification of layer region)
The layer region specifying unit 231 specifies an image region (layer region) corresponding to the retinal pigment epithelium layer in the tomographic image based on the pixel value of the pixel of the tomographic image of the fundus oculi Ef. The information obtained by the layer region specifying unit 231 is sent to the approximate curve calculation unit 232.

(S3: Identification of characteristic part)
Based on the pixel values of the pixels in the layer area specified in step 2, the characteristic part specifying unit 232a specifies a plurality of characteristic parts based on the shape of the layer area.

(S4: Feature part interpolation)
The feature part interpolation unit 232b performs a process of adding a feature part of the layer region as necessary.

(S5: Free curve calculation)
The free curve calculation unit 232c obtains a free curve based on the feature part specified in step 3 and the feature part added in step 4.

(S6: Correction of free curve)
The correction unit 232d corrects the free curve obtained in step 5 as necessary. Accordingly, an approximate curve representing the estimated shape of the retinal pigment epithelium layer when it is assumed that drusen does not exist in the cross section indicated by the tomogram is obtained.

(S7: Calculation of distance)
The distance calculation unit 233a calculates the distance in the depth direction between each point on the approximate curve obtained in Step 6 (Step 5 when correction is not performed) and the layer region.

(S8: Judgment of distance)
The distance determination unit 233b determines whether each distance calculated in step 7 is equal to or greater than a predetermined threshold.

(S9: Identification of protruding region)
The image area specifying unit 233c specifies an image area sandwiched between a set of points on the approximate curve whose distance is determined to be greater than or equal to a predetermined threshold in step 8 and the layer area. This image area becomes a protruding area.

(S10: Identification of connected area)
The connection area specifying unit 234 specifies the connection area including the protruding area specified in step 9 and surrounded by the approximate curve and the layer area.

(S11: Determination of nipple area)
The nipple region determination unit 235a analyzes the tomographic image and determines whether the tomographic image includes a nipple region corresponding to the optic nerve head of the fundus oculi Ef. When it is determined that the nipple region is included, the form information generation unit 235 excludes the connected region located in the vicinity of the nipple region from the connected regions specified in Step 10.

(S12: Generation of form information)
The form information generation unit 235 generates form information indicating the form of the connected area specified in step 10 (excluding the area excluded in step 11).

(S13: Output of analysis result)
The image processing unit 230 generates analysis result presentation information including the form information generated in step 12. The main control unit 211 causes the display unit 240A to display the analysis result based on the analysis result presentation information. This analysis result includes information indicating the presence / absence of drusen in the fundus oculi Ef and information indicating the size and distribution of drusen present in the fundus oculi Ef. An analysis report can be printed out based on the analysis result presentation information. In addition, analysis result presentation information, information obtained by the above processing, and information on a patient and an eye to be examined can be transmitted to an external apparatus or recorded on a recording medium. Thus, the process according to this operation example ends.

[effect]
The effect of the fundus analyzer 1 will be described.

The fundus analysis apparatus 1 includes a storage unit 212, a layer region specifying unit 231, an approximate curve calculating unit 232, a protruding region specifying unit 233, a connected region specifying unit 234, and a form information generating unit 235. The storage unit 212 stores a tomographic image depicting the layer structure of the fundus oculi Ef. The layer region specifying unit 231 specifies a layer region in the tomographic image corresponding to the retinal pigment epithelium layer based on the pixel value of the pixel of the tomographic image. The approximate curve calculation unit 232 obtains an approximate curve based on the shape of the layer region. The protruding region specifying unit 233 specifies a protruding region in which the approximate curve is located in the depth direction of the fundus oculi Ef with respect to the layer region, and the distance between the approximate curve and the layer region in the depth direction is equal to or greater than a predetermined threshold. The connection area specifying unit 234 specifies the connection area including the protruding area and surrounded by the approximate curve and the layer area. The form information generation unit 235 generates form information representing the form of the connected area.

According to such a fundus analysis apparatus 1, it is possible to effectively detect an image region considered to correspond to drusen. More specifically, by specifying a protruding region that protrudes greatly, an image region that is considered to be drusen can be suitably detected by removing small irregularities caused by noise or the like. Further, by detecting the whole connected region including such a protruding region, an image region that is considered to correspond to drusen can be detected without omission. Therefore, according to this embodiment, it is possible to effectively detect drusen based on the tomographic image of the fundus oculi Ef.

The approximate curve calculation unit 232 may include a feature part specifying unit 232a that specifies a plurality of feature parts in the layer region based on the shape of the layer region. In that case, the approximate curve calculation unit 232 obtains an approximate curve based on the plurality of identified characteristic parts. By considering a plurality of characteristic parts, an approximate curve can be obtained with higher accuracy and accuracy.

The following is an example of the configuration of the characteristic part specifying unit 232a. The characteristic part specifying unit 232a specifies the deepest part in the layer area in the depth direction based on the shape of the layer area as a characteristic part, obtains a straight line that passes through the deepest part and touches the layer area, It is possible to configure the contact point with the straight line as a further characteristic part. Further, the feature part specifying unit 232a can be configured to sequentially specify the contact points by rotating a straight line passing through the deepest part around the deepest part. Further, the characteristic part specifying unit 232a specifies a contact by rotating a straight line passing through the deepest part around the deepest part, and further rotates a straight line passing through the specified contact around the contact. It can be configured to be specific.

The approximate curve calculation unit 232 may include a feature part interpolation unit 232b. The feature part interpolation unit 232b obtains a distance between two adjacent feature parts among the feature parts specified by the feature part specifying unit 232a. Furthermore, the feature part interpolation unit 232b adds a new feature part between the two feature parts when the distance is equal to or greater than a predetermined value. By performing such an interpolation process, an approximate curve can be obtained with higher accuracy and accuracy.

The approximate curve calculation unit 232 can obtain a free curve based on a plurality of characteristic parts, and can obtain an approximate curve based on the free curve. At this time, the free curve may be a spline curve, particularly a cubic spline curve. By obtaining a free curve, an approximate curve can be obtained with high accuracy and accuracy.

When obtaining a free curve, the following process can be performed to correct the free curve. As a first example, the approximate curve calculation unit 232 is provided with a straight line part specifying unit 232e and a first deformation unit 232f. The straight part specifying unit 232e specifies a substantially straight part in the layer region. When the free curve is located in the depth direction with respect to the straight line part, the first deforming unit 232f deforms the free curve so that the part of the free curve matches the position of the straight line part. In this case, the approximate curve calculation unit 232 obtains an approximate curve based on the deformation result by the first deformation unit 232f.

As a second example, the approximate curve calculation unit 232 is provided with a curve part specifying unit 232g and a second deformation unit 232h. The curved part specifying unit 232g specifies a part located in the reverse direction of the depth direction with respect to the layer region in the free curve. The second deforming unit 232h deforms the free curve so that the specific part is matched with the position of the layer region. In this case, the approximate curve calculation unit 232 obtains an approximate curve based on the deformation result by the second deformation unit 232h.

As a third example, the approximate curve calculation unit 232 includes a protrusion determination unit 232i and a third deformation unit 232j. The protrusion determination unit 232i determines whether the layer region protrudes in the direction opposite to the depth direction in the vicinity of the end of the frame of the tomographic image. When it is determined that the layer region protrudes, the third deforming portion 232j replaces the portion of the free curve corresponding to the protruding portion with an extension of the free curve from the center side of the frame. Deform the curve. In this case, the approximate curve calculation unit 232 obtains an approximate curve based on the deformation result by the third deformation unit 232j.

It is possible to improve the accuracy and accuracy of the approximate curve by correcting the free curve by the processing as described above.

The protruding area specifying unit 233 can specify the protruding area by performing the following processing, for example. First, the protruding area specifying unit 233 calculates the distance between each point on the approximate curve in the depth direction of the fundus oculi Ef and the layer area, and determines whether the calculated distance is equal to or greater than a predetermined threshold. Then, the protruding area specifying unit 233 specifies an image area sandwiched between a set of points on the approximate curve determined to have a distance greater than or equal to a predetermined threshold and the layer area, and sets this image area as the protruding area. By performing such processing, it is possible to suitably specify the protruding region.

The form information generation unit 235 may include a nipple region determination unit 235a. The nipple region determination unit 235a analyzes the tomographic image and determines whether or not the nipple region corresponding to the optic nerve head of the fundus oculi Ef is included in the tomographic image. When it is determined that the nipple region is included, the shape information generation unit 235 generates the shape information by excluding the connected region located in the vicinity of the nipple region among the connected regions specified by the connected region specifying unit 234. This process can prevent erroneous detection due to the curved shape of the retinal pigment epithelium layer in the vicinity of the optic nerve head, so that it is possible to more effectively detect an image region considered to correspond to drusen.

For example, the nipple region determination unit 235a analyzes a tomographic image to identify a feature layer region corresponding to a predetermined feature layer of the fundus oculi Ef, and determines whether the nipple region is included based on the shape of the feature layer region. Configured. At this time, the predetermined feature layer may be an inner boundary film that forms a boundary with the vitreous body in the fundus oculi Ef. In that case, the nipple region determination unit 235a determines whether there is a portion that is depressed in the depth direction of the fundus oculi Ef in the feature layer region (inner boundary membrane region), and when it is determined that there is a depressed portion, the nipple region Is determined to be included. By this process, the nipple region can be detected effectively.

The nipple region determination unit 235a can execute different processes upon receiving input of left and right eye information indicating whether the eye E is the left eye or the right eye. That is, when the eye E is the left eye, the nipple region determination unit 235a performs the above determination by analyzing at least the vicinity of the left end of the frame of the tomographic image. On the other hand, when the eye E is the right eye, the nipple region determination unit 235a performs the above determination by analyzing at least the vicinity of the right end of the frame of the tomographic image. By this process, it is possible to shorten the time required for the analysis process and reduce resources.

The fundus analyzer 1 divides the light from the light source unit 101 into the signal light LS and the reference light LR, and superimposes the signal light LS passing through the fundus oculi Ef of the eye E and the reference light LR passing through the reference optical path. An optical system that generates and detects the interference light LC, and an image forming unit (image forming unit 220, image processing unit 230) that forms a tomographic image of the fundus oculi Ef based on the detection result of the interference light LC. Also good. The storage unit 212 stores the tomographic image formed by the image forming unit.

Here, the tomographic image formed by the image forming unit 220 is a two-dimensional tomographic image, and the tomographic image formed by the image processing unit 230 is a three-dimensional tomographic image. In the above example, the processing for the two-dimensional tomographic image has been described in detail, but the processing for the three-dimensional tomographic image can be executed in the same manner. At this time, “line” in the process for the two-dimensional tomographic image is read as “surface”. For example, a curved line is read as a curved surface, and a straight line is read as a flat surface. Since the difference in processing based on the difference in the dimensions of the tomographic images is merely such a convenience, the processing for both tomographic images can be said to be substantially the same in concept.

An example of processing a three-dimensional tomographic image using the above configuration will be described. The fundus analysis apparatus 1 includes a storage unit 212, a layer region specification unit 231, an approximate curve calculation unit 232, a protruding region specification unit 233, a connection region specification unit 234, and a form information generation unit 235. The storage unit 212 stores a three-dimensional tomogram depicting the layer structure of the fundus oculi Ef. The layer region specifying unit 231 specifies a layer region in the tomographic image corresponding to the retinal pigment epithelium layer based on the pixel value of the pixel of the three-dimensional tomographic image. This layer region is generally a curved surface (which may include singular points). The approximate curve calculation unit 232 obtains an approximate curved surface based on the shape of the layer region. The protruding region specifying unit 233 specifies a protruding region in which the approximate curved surface is located in the depth direction of the fundus oculi Ef with respect to the layer region, and the distance between the approximate curved surface and the layer region in the depth direction is equal to or greater than a predetermined threshold. The protruding region is generally a three-dimensional region. The connection area specifying unit 234 specifies the connection area including the protruding area and surrounded by the approximate curved surface and the layer area. The connected region is generally a three-dimensional region. The form information generation unit 235 generates form information representing the form of the connected area. According to such a fundus analysis apparatus 1, it is possible to effectively detect drusen based on a three-dimensional tomographic image of the fundus oculi Ef.

[Modification]
The configuration described above is merely an example for favorably implementing the present invention. Therefore, arbitrary modifications within the scope of the present invention can be made as appropriate.

In the above embodiment, drusen (image area considered) is detected based on the distance between the layer area corresponding to the retinal pigment epithelium layer and the approximate curve (approximate curved surface), but the sensitivity of OCT measurement is improved. For example, an image region corresponding to a Bruch's film (referred to as a film region) may be detected by improving the detection, and drusen may be detected based on a distance between the layer region and the film region. Since drusen occurs between the Bruch's membrane and the retinal pigment epithelial layer, it is possible to grasp drusen's morphology with higher accuracy and accuracy by executing the processing according to this modification. .

In the above-described embodiment, instead of the Bruch's film that is difficult to detect from the OCT image, an approximate curve that approximates the morphology of the retinal pigment epithelium layer in a state where there is no drusen (protrusion) is used.

As a further modification, it is possible to specify a layer region corresponding to the retinal pigment epithelium layer from the OCT image and to specify a membrane region corresponding to the Bruch's membrane. When the film region is specified, the connected region is specified based on the distance between the film region and the layer region, and the form information is generated. On the other hand, if the identification of the membrane region fails, an approximate curve (approximate curved surface) is obtained as in the above embodiment, and the connected region is specified based on the layer region and the approximate curve (approximate curved surface) to obtain the form information. Generate.

According to this modification, when the membrane region is specified, the drusen form can be grasped with high accuracy and high accuracy, and when the membrane region is not specified, an approximate curve (or approximate curved surface) is used. You can grasp the form of drusen.

In the above embodiment, the position of the reference mirror 114 is changed to change the optical path length difference between the optical path of the signal light LS and the optical path of the reference light LR, but the method of changing the optical path length difference is limited to this. Is not to be done. For example, the optical path length difference can be changed by moving the fundus camera unit 2 or the OCT unit 100 with respect to the eye E to change the optical path length of the signal light LS. It is also effective to change the optical path length difference by moving the measurement object in the depth direction (z-axis direction), especially when the measurement object is not a living body part.

[Fundus analysis program]
A fundus analysis program according to the present invention will be described. The fundus analysis program causes a computer having a storage unit that stores a tomographic image depicting the layer structure of the fundus to execute an operation described later. An example of this computer is the arithmetic control unit of the above embodiment. This fundus analysis program may be stored in the computer itself, or may be stored in a server or the like connected to be communicable with the computer.

The operation performed by the computer based on this fundus analysis program will be described. First, the computer (layer region specifying unit) specifies a layer region in the tomographic image corresponding to the retinal pigment epithelium layer based on the pixel value of the pixel of the tomographic image. Next, the computer (approximate curve calculation unit) obtains an approximate curve based on the shape of the layer region. Subsequently, the computer (projection region specifying unit) determines a projection region in which the approximate curve is located in the depth direction of the fundus than the layer region, and the distance in the depth direction between the approximate curve and the layer region is equal to or greater than a predetermined threshold. Identify. Further, the computer (connected area specifying unit) specifies the connected area including the protruding area and surrounded by the approximate curve and the layer area. And a computer (form information generation part) produces | generates the form information showing the form of a connection area | region. The computer can display, print, and transmit the generated form information.

According to such a fundus analysis program, drusen can be detected effectively based on a tomographic image of the fundus as in the above embodiment. Note that the fundus analysis program according to this embodiment may cause a computer to execute any function that the fundus analysis apparatus 1 of the above embodiment has.

Next, another fundus analysis program according to the present invention will be described. This fundus analysis program causes a computer having a storage unit that stores a three-dimensional tomographic image that describes the layer structure of the fundus to perform an operation described later. An example of this computer is the arithmetic control unit of the above embodiment.

The operation performed by the computer based on this fundus analysis program will be described. First, the computer (layer region specifying unit) specifies a layer region in the tomographic image corresponding to the retinal pigment epithelial layer based on the pixel values of the pixels of the three-dimensional tomographic image. Next, the computer (approximate curved surface calculation unit) obtains an approximate curved surface based on the shape of the layer region. Subsequently, the computer (projection region specifying unit) determines a projection region in which the approximate curved surface is located in the depth direction of the fundus than the layer region, and the distance between the approximate curved surface and the layer region in the depth direction is equal to or greater than a predetermined threshold. Identify. The computer (connected area specifying unit) specifies the connected area including the protruding area and surrounded by the approximate curved surface and the layer area. A computer (form information generation part) produces | generates the form information showing the form of a connection area | region. The computer can display, print, and transmit the generated form information.

According to such a fundus analysis program, drusen can be detected effectively based on a three-dimensional tomographic image of the fundus as in the above embodiment. Note that the fundus analysis program according to this embodiment may cause a computer to execute any function that the fundus analysis apparatus 1 of the above embodiment has.

The fundus analysis program according to the embodiment can be stored in any recording medium readable by a computer. As this recording medium, for example, an optical disk, a magneto-optical disk (CD-ROM / DVD-RAM / DVD-ROM / MO, etc.), a magnetic storage medium (hard disk / floppy (registered trademark) disk / ZIP, etc.), etc. are used. Is possible. It can also be stored in a storage device such as a hard disk drive or memory.

It is also possible to send and receive this program through a network such as the Internet or a LAN.

[Fundamental analysis method]
A fundus analysis method according to the present invention will be described. This fundus analysis method analyzes a tomographic image describing the layer structure of the fundus and includes the following steps. This fundus analysis method can also be grasped as an apparatus control method for causing the fundus analysis apparatus (OCT apparatus or the like) to execute the following steps.

(First step)
Based on the pixel value of the pixel of the tomographic image, a layer region in the tomographic image corresponding to the retinal pigment epithelium layer is specified.
(Second step)
An approximate curve based on the shape of the layer region is obtained.
(Third step)
A protruding region in which the approximate curve is located in the depth direction of the fundus than the layer region and the distance in the depth direction between the approximate curve and the layer region is greater than or equal to a predetermined threshold is specified.
(Fourth step)
A connected region including the protruding region and surrounded by the approximate curve and the layer region is specified.
(Fifth step)
Form information representing the form of the connected area is generated.

According to such a fundus analysis method, drusen can be detected effectively based on a tomographic image of the fundus as in the above embodiment. Note that the fundus analysis method (or device control method) according to this embodiment may include any process that can be executed by the fundus analysis device 1 of the above embodiment.

Another fundus analysis method according to the present invention will be described. This fundus analysis method analyzes a three-dimensional tomographic image that describes the layer structure of the fundus, and includes the following steps.

(First step)
A layer region in the tomographic image corresponding to the retinal pigment epithelium layer is specified based on the pixel value of the pixel of the three-dimensional tomographic image.
(Second step)
An approximate curved surface based on the shape of the layer region is obtained.
(Third step)
A protruding region in which the approximate curved surface is located in the depth direction of the fundus occupying the layer region and the distance in the depth direction between the approximate curved surface and the layer region is greater than or equal to a predetermined threshold is specified.
(Fourth step)
A connected area including the protruding area and surrounded by the approximate curved surface and the layer area is specified.
(Fifth step)
Form information representing the form of the connected area is generated.

According to such a fundus analysis method, drusen can be detected effectively based on a three-dimensional tomographic image of the fundus as in the above embodiment. Note that the fundus analysis method (or device control method) according to this embodiment may include any process that can be executed by the fundus analysis device 1 of the above embodiment.

DESCRIPTION OF SYMBOLS 1 Fundus analyzer 2 Fundus camera unit 41 Optical path length change part 42 Galvano scanner 100 OCT unit 101 Light source unit 115 CCD image sensor 200 Arithmetic control unit 210 Control part 211 Main control part 212 Storage part 220 Image formation part 230 Image processing part 231 Layer Region specifying unit 232 Approximate curve calculating unit 232a Feature site specifying unit 232b Feature site interpolating unit 232c Free curve calculating unit 232d Correction unit 232e Straight site specifying unit 232f First deforming unit 232g Curved site specifying unit 232h Second deforming unit 232i Protrusion determining unit 232j 3rd deformation | transformation part 233 Protrusion area | region specific | specification part 233a Distance calculation part 233b Distance determination part 233c Image area | region specific | specification part 234 Connection area | region specific | specification part 235 Shape information generation part 235a Papilla area | region determination part 235b Distribution image formation part 235c Count part 23 5d Size calculation unit 240A Display unit 240B Operation unit 300 Layer region 310, 320, 330, 340 Characteristic part 400 Free curve 400a Interpolation curve 410, 420, 430 Control point 500 Estimation curve 500a Extrapolation curve 510 Correction line segment 600 Protrusion region 700 Connection region 800 Inner boundary membrane region 900 Distribution image E Eye to be examined Ef Fundus LS Signal light LR Reference light LC Interference light G Tomographic image F Tomographic image frame

Claims (23)

1. A storage unit for storing a tomographic image depicting the layer structure of the fundus;
   Based on the pixel value of the pixel of the tomographic image, a layer region specifying unit that specifies a layer region in the tomographic image corresponding to the retinal pigment epithelium layer;
   An approximate curve calculation unit for obtaining an approximate curve based on the shape of the layer region;
   A protruding region specifying unit that specifies a protruding region in which the approximate curve is located in the depth direction of the fundus than the layer region, and the distance between the approximate curve and the layer region in the depth direction is equal to or greater than a predetermined threshold. When,
   A connected region specifying unit that specifies the connected region that includes the protruding region and is surrounded by the approximate curve and the layer region;
   A fundus analysis apparatus comprising: a form information generation unit that generates form information representing the form of the connected region.
2. The approximate curve calculation unit includes:
   Based on the shape of the layer region, including a feature site identification unit that identifies a plurality of feature sites in the layer region,
   The fundus analysis apparatus according to claim 1, wherein the approximate curve is obtained based on the plurality of characteristic portions.
3. The characteristic site specifying part is:
   Identify the deepest part in the layer area in the depth direction based on the shape of the layer area as a characteristic part,
   Find a straight line that passes through the deepest part and touches the layer region,
   The fundus analysis apparatus according to claim 2, wherein a contact point between the layer region and the straight line is a further characteristic part.
4. The fundus analysis apparatus according to claim 3, wherein the characteristic part specifying unit sequentially specifies a contact point by rotating a straight line passing through the deepest part around the deepest part.
5. The characteristic site specifying part is:
   Rotate a straight line passing through the deepest part around the deepest part to identify a contact point,
   The fundus analysis apparatus according to claim 3, wherein a further contact is specified by rotating a straight line passing through the specified contact around the contact.
6. The approximate curve calculation unit obtains a distance between two adjacent feature parts, and adds a new feature part between the two feature parts when the distance is a predetermined value or more. The fundus analysis apparatus according to any one of claims 2 to 5, further comprising:
7. The approximate curve calculation unit obtains a free curve based on the plurality of characteristic parts, and obtains the approximate curve based on the free curve. Fundus analyzer.
8. The fundus analysis apparatus according to claim 7, wherein the approximate curve calculation unit obtains a spline curve as the free curve.
9. The fundus analysis apparatus according to claim 8, wherein the approximate curve calculation unit obtains a cubic spline curve as the spline curve.
10. The approximate curve calculation unit includes:
    A linear part specifying part for specifying a substantially linear part in the layer region;
    A first deforming portion that deforms the free curve so as to match the position of the free curve with the position of the straight line when the free curve is located in the depth direction relative to the straight line; and
    The fundus analysis apparatus according to any one of claims 7 to 9, wherein the approximate curve is obtained based on a deformation result by the first deformation unit.
11. The approximate curve calculation unit includes:
    A curve part specifying part for specifying a part located in a direction opposite to the depth direction from the layer region in the free curve;
    A second deforming part that deforms the free curve so as to align the specific part with the position of the layer region,
    The fundus analysis apparatus according to any one of claims 7 to 10, wherein the approximate curve is obtained based on a deformation result by the second deformation unit.
12. The approximate curve calculation unit includes:
    A protrusion determination unit that determines whether the layer region protrudes in the direction opposite to the depth direction in the vicinity of the end of the frame of the tomographic image;
    When it is determined that the layer region protrudes, the free curve portion is replaced with an extension line of the free curve from the center side of the frame by replacing the free curve portion corresponding to the protruding portion. A third deforming portion that deforms, and
    The fundus analysis apparatus according to any one of claims 7 to 11, wherein the approximate curve is obtained based on a deformation result by the third deformation unit.
13. The protruding region specifying part is:
    Calculating the distance between each point on the approximate curve in the depth direction and the layer region;
    Determining whether the calculated distance is greater than or equal to the predetermined threshold;
    13. The image region sandwiched between a set of points on the approximate curve determined to be equal to or greater than the predetermined threshold and the layer region is specified as the projecting region. The fundus analysis apparatus according to any one of the above.
14. The form information generation unit
    Analyzing the tomographic image, including a nipple region determination unit that determines whether a nipple region corresponding to the optic nerve head of the fundus is included in the tomographic image,
    When it is determined that the nipple region is included, the morphological information is generated by excluding a connected region located in the vicinity of the nipple region among the connected regions specified by the connected region specifying unit. The fundus analysis apparatus according to any one of claims 1 to 13.
15. The nipple region determination unit
    Analyzing the tomographic image to identify a feature layer region corresponding to a predetermined feature layer of the fundus;
    The fundus analysis apparatus according to claim 14, wherein it is determined whether the nipple region is included based on the shape of the identified feature layer region.
16. The predetermined characteristic layer is an inner boundary film that forms a boundary with the vitreous body at the fundus,
    The nipple region determination unit
    It is determined whether there is a portion depressed in the depth direction in the feature layer region,
    The fundus analysis apparatus according to claim 15, wherein it is determined that the nipple region is included when it is determined that the depressed portion exists.
17. The nipple region determination unit receives input of left and right eye information indicating whether the eye to be examined is the left eye or the right eye,
    When the eye to be examined is the left eye, the determination is performed by analyzing at least the left end vicinity of the frame of the tomographic image,
    The fundus analysis apparatus according to any one of claims 14 to 16, wherein when the eye to be examined is a right eye, the determination is performed by analyzing at least the vicinity of the right end of the frame.
18. An optical system that generates and detects interference light by dividing light from a light source into signal light and reference light, and superimposing signal light passing through the fundus of the eye to be examined and reference light passing through the reference optical path;
    An image forming unit that forms a tomographic image of the fundus based on the detection result of the interference light,
    The fundus analysis apparatus according to any one of claims 1 to 17, wherein the storage unit stores a tomographic image formed by the image forming unit.
19. A storage unit for storing a three-dimensional tomographic image depicting the layer structure of the fundus;
    A layer region specifying unit for specifying a layer region in the tomographic image corresponding to the retinal pigment epithelium layer based on the pixel value of the pixel of the three-dimensional tomographic image;
    An approximate curved surface calculation unit for obtaining an approximate curved surface based on the shape of the layer region;
    A protruding region specifying unit that specifies a protruding region in which the approximate curved surface is located in the depth direction of the fundus than the layer region, and the distance between the approximate curved surface and the layer region in the depth direction is equal to or greater than a predetermined threshold. When,
    A connected region specifying unit that specifies the connected region that includes the protruding region and is surrounded by the approximate curved surface and the layer region;
    A fundus analysis apparatus comprising: a form information generation unit that generates form information representing the form of the connected region.
20. A computer having a storage unit for storing a tomographic image depicting the layer structure of the fundus;
    A layer region specifying unit for specifying a layer region in the tomographic image corresponding to the retinal pigment epithelium layer based on the pixel value of the pixel of the tomographic image;
    An approximate curve calculation unit for obtaining an approximate curve based on the shape of the layer region,
    A protruding region specifying unit that specifies a protruding region in which the approximate curve is located in the depth direction of the fundus than the layer region, and a distance in the depth direction between the approximate curve and the layer region is a predetermined threshold or more. ,
    A connected region specifying unit that specifies the connected region that includes the protruding region and is surrounded by the approximate curve and the layer region; and
    A fundus analysis program that functions as a form information generation unit that generates form information representing the form of the connected region.
21. A computer having a storage unit for storing a three-dimensional tomographic image depicting a layer structure of the fundus;
    A layer region specifying unit that specifies a layer region in the tomographic image corresponding to the retinal pigment epithelium layer based on the pixel value of the pixel of the three-dimensional tomographic image;
    An approximate curved surface calculation unit for obtaining an approximate curved surface based on the shape of the layer region;
    A protruding region specifying unit that specifies a protruding region in which the approximate curved surface is located in the depth direction of the fundus than the layer region, and the distance between the approximate curved surface and the layer region in the depth direction is equal to or greater than a predetermined threshold. ,
    A connected region specifying part that includes the protruding region and specifies a connected region surrounded by the approximate curved surface and the layer region; and
    A fundus analysis program that functions as a form information generation unit that generates form information representing the form of the connected region.
22. A fundus analysis method for analyzing a tomographic image depicting a layer structure of the fundus,
    Identifying a layer region in the tomographic image corresponding to the retinal pigment epithelial layer based on the pixel value of the pixel of the tomographic image;
    Obtaining an approximate curve based on the shape of the layer region;
    Identifying the protruding region in which the approximate curve is positioned in the depth direction of the fundus than the layer region, and the distance in the depth direction between the approximate curve and the layer region is a predetermined threshold or more;
    Identifying a connected region that includes the protruding region and is surrounded by the approximate curve and the layer region;
    Generating fundus information representing the form of the connected region.
23. A fundus analysis method for analyzing a three-dimensional tomographic image depicting a layer structure of the fundus,
    Identifying a layer region in the tomographic image corresponding to the retinal pigment epithelial layer based on the pixel values of the pixels of the three-dimensional tomographic image;
    Obtaining an approximate curved surface based on the shape of the layer region;
    Identifying the protruding region in which the approximate curved surface is located in the depth direction of the fundus than the layer region, and the distance between the approximate curved surface and the layer region in the depth direction is equal to or greater than a predetermined threshold;
    Identifying a connected region including the protruding region and surrounded by the approximate curved surface and the layer region;
    Generating fundus information representing the form of the connected region.

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