JP2018000687A - Image processing device, image processing method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a mechanism to acquire an excellent front image in which image information of each layer is reflected even when a plurality of layers are included in a predetermined depth range of an object to be inspected, for which the front image is generated.SOLUTION: An image processing device includes a layer image extraction part 433 for extracting a layer image of each layer of a plurality of layers included in a predetermined depth range in the depth direction of an object to be inspected from a tomographic image of the object to be inspected having a layer structure, a first representative value calculation part 434 for calculating a first representative value which is a representative value in the depth direction for each layer based on the layer image of each layer extracted by the layer image extraction part 433, a second representative value calculation part 435 for calculating a second representative value which is a representative value in the predetermined depth range using the first representative value of each layer calculated by the first representative value calculation part 434, and a front generation part 436 for generating a front image of the object to be inspected using the second representative value calculated by the second representative value calculation part 435.SELECTED DRAWING: Figure 4

Description

  The present invention relates to an image processing apparatus and an image processing method for processing a tomographic image of an inspection object having a layer structure, and a program for causing a computer to function as the image processing apparatus.

  Currently, an imaging device based on optical coherence tomography (OCT) using multiwavelength lightwave interference has been applied to the human body in order to obtain, for example, internal organ information in an endoscope and retina information in an ophthalmic device. It is spreading. An imaging device for examining an eye is becoming an indispensable device in a specialized retina outpatient as an ophthalmic device.

  Such an imaging apparatus is configured to irradiate the inspection object with measurement light, which is low-coherent light, and to measure the backscattered light from the inspection object using an interference system. . In addition, since an imaging apparatus that uses an eye as an inspection target can capture a tomographic image of the subject's eye with high resolution by scanning the subject's eye with measurement light, for example, in ophthalmic diagnosis of the retina Widely used.

  Patent Document 1 describes an imaging apparatus configured to acquire an image of the surface of the fundus, which is an object to be imaged, in order to confirm the imaging range of a tomographic image. On the other hand, there is a demand for more accurately confirming which position on the surface of the fundus that is the object to be imaged.

  Therefore, as described in Patent Document 2, a two-dimensional image (hereinafter referred to as “front image”) in which the fundus, which is the object to be imaged, is viewed from the front is generated from a plurality of tomographic images. The technology to do is known. In this technique, pixel values are selected based on the order of pixel values from a pixel value sequence in the depth direction of an object to be examined (fundus) obtained by one A scan. Then, by obtaining the selected pixel values for all the A scans, it is possible to generate a front image (Projection image) similar to the planar image of the retina from only the tomographic image. Patent Document 2 also describes a method of generating a front image by selecting a predetermined layer of the retina, selecting pixel values based on the order of pixel values from the pixel value sequence in the predetermined layer. . In this method, an EnFace image based on information within a predetermined depth range can be generated as a front image.

JP 2011-36431 A JP 2014-45869 A

  It is known that the retina of the eye to be examined is composed of a plurality of layers. In the technique described in Patent Document 2 described above, when a plurality of layers are included in a predetermined depth range of an inspection object for generating a front image, the pixel value in the depth direction in the tomographic image of the inspection object When the pixel values are selected based on the order, only the image information of a specific layer is reflected on the front image and the image information of other layers is not reflected depending on the distribution of the tomographic image. This phenomenon often occurs particularly when pixel values of each layer included in a predetermined depth range are dispersed.

  The present invention has been made in view of such problems, and image information of each layer is reflected even when a plurality of layers are included in a predetermined depth range of an inspection object for generating a front image. An object is to provide a mechanism capable of acquiring a good front image.

The image processing apparatus according to the present invention is an extraction unit that extracts a layer image for each of a plurality of layers included in a predetermined depth range in the depth direction of the inspection object from a tomographic image of the inspection object having a layer structure. And a first representative value calculating means for calculating a first representative value that is a representative value in the depth direction for each layer based on the layer image of each layer extracted by the extracting means; Second representative value calculating means for calculating a second representative value that is a representative value in the predetermined depth range by using the first representative value of each layer calculated by the first representative value calculating means; And generating means for generating a front image of the inspection object using the second representative value.
The present invention also includes an image processing method by the above-described image processing apparatus and a program for causing a computer to function as the above-described image processing apparatus.

  According to the present invention, even when a plurality of layers are included in a predetermined depth range of an inspection object for generating a front image, a good front image reflecting image information of each layer can be acquired.

It is a figure which shows an example of schematic structure of the imaging | photography system containing the image processing apparatus which concerns on the 1st Embodiment of this invention. It is a figure which shows an example of the external appearance of the image processing apparatus and imaging device shown in FIG. It is a figure which shows an example of the internal structure of the optical head and base part which are shown in FIG. It is a figure which shows an example of a function structure of the image processing apparatus which concerns on the 1st Embodiment of this invention. It is a flowchart which shows an example of the process sequence in the image processing method by the image processing apparatus which concerns on the 1st Embodiment of this invention. It is a figure which shows the example of a setting of the predetermined depth range in step S502 of FIG. It is the figure which graphed the change of the luminance value (pixel value) of the depth direction (A scan direction) in A (x, y) of the tomographic image shown in FIG. It is a figure which shows the example of extraction of the layer image of each layer in step S503 of FIG. It is a figure for demonstrating the EnFace image produced | generated by the process of the flowchart shown in FIG. It is a figure which shows the example of an image display in the monitor of the image processing apparatus which concerns on the 1st Embodiment of this invention. It is a figure which shows the example of an image display in the monitor of the image processing apparatus which concerns on the 1st Embodiment of this invention. It is a figure which shows the 4th Embodiment of this invention and shows an example of the adjustment screen in the display intensity | strength of each layer for weighting the 1st representative value of each layer.

  Hereinafter, embodiments (embodiments) for carrying out the present invention will be described with reference to the drawings. In each embodiment of the present invention described below, an example in which the fundus of the eye to be examined is applied as an object to be examined will be described. However, the present invention is not limited to this and has a layer structure. Other objects can be applied to the present invention as long as they are inspected.

(First embodiment)
First, a first embodiment of the present invention will be described.

FIG. 1 is a diagram illustrating an example of a schematic configuration of an imaging system 100 including an image processing apparatus 110 according to the first embodiment of the present invention.
As shown in FIG. 1, the imaging system 100 includes an image processing device 110, an imaging device 120, and an external device 130.

  As shown in FIG. 1, the image processing apparatus 110 includes a computer 116, a monitor 117, and an operation input unit 118. As shown in FIG. 1, the computer 116 includes a central processing unit (CPU) 111, a main memory 112, a magnetic disk 113, a display memory 114, and a common bus 115.

  Specifically, the CPU 111 mainly controls the operation of each component of the image processing apparatus 110 and performs various processes. The main memory 112 stores a program used when the CPU 111 executes processing and various kinds of information, and provides a work area when the CPU 111 executes the program. The magnetic disk 113 stores, for example, an operating system (OS), device drivers for peripheral devices, and the like, and is configured to store various types of information. The display memory 114 temporarily stores display data to be displayed on the monitor 117. The common bus 115 connects the CPU 111, the main memory 112, the magnetic disk 113, the display memory 114, the operation input unit 118, the imaging device 120, and the external device 130 so that they can communicate with each other.

  The monitor 117 is, for example, a CRT monitor or a liquid crystal monitor, and displays various images and various information based on display data from the display memory 114.

  The operation input unit 118 includes a mouse 118-1 for a pointing input by the user and a keyboard 118-2 for a character input by the user.

  The image processing apparatus 110 is connected to the imaging apparatus 120 via, for example, a local area network (LAN), and can acquire image data such as a tomographic image from the imaging apparatus 120. Note that the present embodiment is not limited to this connection format, and may be connected by another connection format such as USB or IEEE1394. Further, the image processing apparatus 110 may be configured to read necessary data (for example, image data such as the above-described tomographic image) from an external apparatus 130 such as a data server that manages various data via a LAN or the like. Good. Further, for example, an FDD, a CD-RW drive, an MO drive, a ZIP drive, or the like may be connected to the image processing apparatus 110 as a storage device, and necessary data may be read from these drives.

  FIG. 2 is a diagram illustrating an example of the external appearance of the image processing apparatus 110 and the imaging apparatus 120 illustrated in FIG. In FIG. 2, the same components as those shown in FIG.

  FIG. 1 shows an image processing apparatus 110 having the computer 116, the monitor 117, and the operation input unit 118 shown in FIG.

  The imaging apparatus 120 is, for example, an optical coherence tomography apparatus. As shown in FIG. 2, the photographing apparatus 120 includes an optical head 121, a stage unit 122, a base unit 123, a chin rest 124, and an external fixation lamp 125. The optical head 121 is a measurement optical system for capturing an anterior ocular segment image, a fundus surface image, and a tomographic image. The stage unit 122 is a moving mechanism that enables the optical head 121 to move in the x, y, and z directions shown in FIG. 2 using a motor (not shown). The base portion 123 is for supporting the optical head 121, the stage portion 122, the chin rest 124, and the external fixation lamp 125. The chin rest 124 is configured to fix the subject's chin and forehead, and is for urging fixation of the subject's eyes (test eye). The external fixation lamp 125 is for fixing the eye to be examined. In the present embodiment, the image processing apparatus 110 may be incorporated in the optical head 121 or the stage unit 122. In this case, the photographing device 120 and the image processing device 110 are integrally configured as a photographing device.

  FIG. 3 is a diagram illustrating an example of the internal configuration of the optical head 121 and the base portion 123 illustrated in FIG. FIG. 3 also shows the fundus oculi Er of the eye E to be inspected.

First, the internal configuration of the optical head 121 will be described.
Opposite to the eye E, an objective lens 335-1 is installed. On the optical axis, by the first dichroic mirror 332-1 and the second dichroic mirror 332-2, the optical path L1 of the OCT optical system, the optical path L2 for fundus observation and fixation lamp, and the optical path L3 for anterior ocular segment observation Branches for each wavelength band.

  Lenses 335-3 and 335-4 are arranged in the optical path L2. The lens 335-3 is driven by a motor (not shown) for adjusting the focus of the fixation lamp 321 and the fundus observation CCD 323. A perforated mirror 322 is disposed between the lens 335-4 and the third dichroic mirror 332-3, and the optical path L2 is branched into an optical path L2 and an optical path L4 by the perforated mirror 322.

  The optical path L4 constitutes an illumination optical system that illuminates the fundus Er of the eye E. In the optical path L4, an LED light source 341, a condenser lens 342, a strobe tube 343, a condenser lens 344, a mirror 345, a ring slit 346, and lenses 347 and 348 are installed. The LED light source 341 is a fundus observation illumination light source used for alignment of the eye E, and outputs light having a center wavelength of, for example, around 780 nm. The strobe tube 343 is used for photographing the fundus oculi Er of the eye E. The illumination light from the LED light source 341 and the strobe tube 343 becomes a ring-shaped light beam by the ring slit 346, is reflected by the perforated mirror 322, and illuminates the fundus Er of the eye E to be examined.

  After the holed mirror 322 in the optical path L2, the third dichroic mirror 332-3 branches to the optical path to the fundus observation CCD 323 and the fixation lamp 321 for each wavelength band as described above. The CCD 323 has sensitivity at the center wavelength of the LED light source 341 that is illumination light for fundus observation, specifically, around 780 nm, and is connected to the CCD controller 362. On the other hand, the fixation lamp 321 generates visible light and promotes fixation of the eye E, and is connected to the fixation lamp controller 361. The fixation lamp control unit 361 and the CCD control unit 362 are connected to a calculation unit 360 provided in the base unit 123, and various types of data are input to and output from the computer 116 through the calculation unit 360.

  In the optical path L3, a lens 335-2 and an infrared CCD 331 for anterior eye observation are provided. The infrared CCD 331 has sensitivity at a wavelength of illumination light for anterior eye observation (not shown), specifically, around 970 nm. In addition, an image split prism (not shown) is disposed in the optical path L3, and the distance in the z direction of the optical head 121 with respect to the eye E can be detected as a split image in the anterior ocular segment observation image.

  As described above, the optical path L1 constitutes an OCT optical system, and is used to capture a tomographic image of the retina on the fundus Er of the eye E to be examined. More specifically, an interference signal for forming a tomographic image is obtained. In the optical path L1, a light source 311, an optical coupler 312, optical fibers 313-1 to 313-4, polarization adjusting units 314-1 to 314-2, lenses 335-5 to 335-7, an XY scanner 315, and dispersion compensation glass are provided. 316 and a reference mirror 332-4 are provided. A spectroscope 350 built in the base unit 123 is connected to the optical fiber 313-2. In this embodiment, a Michelson interferometer is configured by these configurations.

  The light source 311 is, for example, a super luminescent diode (SLD) that is a typical low-coherent light source. The light emitted from the light source 311 has a center wavelength of about 855 nm and a wavelength bandwidth of about 100 nm. Here, the bandwidth is an important parameter because it affects the resolution of the obtained tomographic image in the optical axis direction. Here, an example in which an SLD is used as the light source 311 has been shown. However, the light source 311 only needs to emit low-coherent light, and may be, for example, ASE (Amplified Spontaneous Emission). The light emitted from the light source 311 is preferably near infrared light in view of the fact that the center wavelength measures the eye to be examined Er. Further, the center wavelength affects the lateral resolution of the obtained tomographic image, and therefore it is desirable that the center wavelength be as short as possible. For this reason, in this embodiment, the center wavelength is set to about 855 nm for both reasons.

  The light emitted from the light source 311 passes through the optical fiber 313-1 and is split by the optical coupler 312 into measurement light on the optical fiber 313-2 side and reference light on the optical fiber 313-3 side. The measurement light is irradiated onto the fundus Er of the eye E through the XY scanner 315, the second dichroic mirror 332-2, and the like, and reaches the optical coupler 312 through the same optical path due to reflection and scattering by the retina of the fundus Er. On the other hand, the reference light reaches the reference mirror 332-4 and is reflected through the optical fiber 313-3, the lens 335-7, and the dispersion compensation glass 316 inserted to match the dispersion of the measurement light and the reference light. The optical coupler 312 is reached through the same optical path. Then, the measurement light and the reference light reaching the optical coupler 312 are combined to become interference light. Here, interference occurs when the optical path length of the measurement light and the optical path length of the reference light are substantially the same. The reference mirror 332-4 is held so as to be adjustable in the optical axis direction by a motor and a driving mechanism (not shown), and the optical path length of the reference light can be adjusted to the optical path length of the measurement light that changes depending on the eye E to be examined. It has become. The interference light obtained by the optical coupler 312 is guided to the spectroscope 350 through the optical fiber 313-4.

  The polarization adjustment unit 314-1 is a measurement light side polarization adjustment unit provided in the optical fiber 313-2, and the polarization adjustment unit 314-2 is provided on the reference light side provided in the optical fiber 313-3. It is a polarization adjustment unit. These polarization adjusting units 314-1 and 314-2 have some portions where the optical fiber 313 is routed in a loop. Then, the polarization adjusting units 314-1 and 314-2 rotate the loop-shaped portion around the longitudinal direction of the optical fiber 313, and twist the optical fiber 313, thereby polarizing the measurement light and the reference light. Each state can be adjusted and adjusted. In this embodiment, it is assumed that the polarization states of the measurement light and the reference light are adjusted and fixed in advance.

  The lens 335-5 is driven by a motor (not shown) to adjust the focus of light from the light source 311 emitted from the optical fiber 313-2 connected to the optical coupler 312 onto the fundus Er. With this focusing adjustment, the light from the fundus Er is simultaneously incident on the tip of the optical fiber 313-2 in the form of a spot.

  The XY scanner 315 is a scanner for scanning the measurement light on the fundus Er. In FIG. 3, the XY scanner 315 is illustrated as a single mirror, but scanning in two directions, the x direction and the y direction, is performed.

  In this embodiment, a Michelson interferometer is used as the interferometer. However, for example, a Mach-Zehnder interferometer may be used. At this time, these interferometers may be used properly in accordance with the light amount difference between the measurement light and the reference light. For example, it is desirable to use a Mach-Zehnder interferometer when the light amount difference between the measurement light and the reference light is large. When the light amount difference between the measurement light and the reference light is relatively small, a Michelson interferometer is used. desirable.

Next, the internal configuration of the base portion 123 will be described.
As shown in FIG. 3, the base portion 123 includes a spectroscope 350 that includes lenses 335-8 and 335-9, a diffraction grating 351, and a line sensor 352. The interference light emitted from the optical fiber 313-4 becomes substantially parallel light via the lens 335-8, is then split by the diffraction grating 351, and is imaged on the line sensor 352 by the imaging lens 335-9. The line sensor 352 includes a plurality of sensors that detect incident interference light as image signals, and outputs the detected image signals to the image processing apparatus 110 (computer 116).

  Next, a method for imaging the fundus oculi Er of the eye E to be examined by the imaging apparatus 120 will be described with reference to FIG.

  First, the examiner seats a subject who is a patient in front of the photographing apparatus 120 and starts photographing a surface image of the fundus Er of the subject eye E.

  Specifically, light is emitted from the LED light source 341, converted into a ring-shaped light beam by the ring slit 346, and then reflected by the perforated mirror 322 to illuminate the fundus Er of the eye E to be examined. Then, the reflected light from the fundus Er passes through the perforated mirror 322 and forms an image on the CCD 323. The reflected light of the fundus Er imaged on the CCD 323 is imaged as a surface image of the fundus Er in the CCD controller 362 and transmitted to the image processing apparatus 110 (computer 116) via the arithmetic unit 360. Here, the CCD control unit 362 performs imaging of the surface image, but the image processing apparatus 110 receives the image signal related to the surface image detected by the CCD 323 via the CCD control unit 362 and the calculation unit 360. The image processing apparatus 110 may image the surface image.

  Next, the imaging apparatus 120 captures a tomographic image of a desired site on the fundus of the eye E by controlling the XY scanner 315.

  Specifically, light is emitted from the light source 311, and is divided into measurement light toward the eye E and reference light toward the reference mirror 332-4 by the optical coupler 312 via the optical fiber 313-1. The measurement light traveling toward the eye E passes through the optical fiber 313-2, exits from the end of the fiber, and enters the XY scanner 315. The measurement light deflected by the XY scanner 315 irradiates the fundus Er of the eye E through the objective lens 335-1. Then, the reflected light reflected by the fundus Er of the eye E is returned to the optical coupler 312 along the reverse path. On the other hand, the reference light traveling toward the reference mirror 332-4 passes through the optical fiber 313-3, exits from the fiber end, and reaches the reference mirror 332-4 via the lens 335-7 and the dispersion compensation glass 316. The reference light reflected by the reference mirror 332-4 follows the reverse path and is returned to the optical coupler 312.

  The measurement light and the reference light that have returned to the optical coupler 312 interfere with each other, become interference light, enter the optical fiber 313-4, are substantially collimated by the lens 335-8, and enter the diffraction grating 351. The interference light input to the diffraction grating 351 is imaged on the line sensor 352 by the imaging lens 335-9, and an interference signal at one point on the fundus Er of the eye E can be obtained. The line sensor 352 outputs image signals detected by a plurality of sensors to the image processing apparatus 110 (computer 116). In addition, although the example which acquires the surface image of the fundus Er at once by the light emission of the strobe tube 343 has been described with reference to FIG. Good.

Next, the functional configuration of the image processing apparatus 110 will be described.
FIG. 4 is a diagram illustrating an example of a functional configuration of the image processing apparatus 110 according to the first embodiment of the present invention. More specifically, FIG. 4 shows an example of the functional configuration of the computer 116 included in the image processing apparatus 110. 4 shows a function of generating a front image that is a two-dimensional image of the fundus Er of the eye E viewed from the front, from the tomographic image of the fundus Er of the eye E, among the functions of the image processing apparatus 110. Only the configuration related to is described.

  As illustrated in FIG. 4, the image processing apparatus 110 (computer 116) includes a reconstruction unit 410, a layer recognition unit 420, and an image generation processing unit 430.

  The reconstruction unit 410 configures a tomographic image of the fundus Er of the eye E based on the image signal output from the line sensor 352. Detailed processing of the reconstruction unit 410 will be described below.

Specifically, the reconstruction unit 410 performs a wave number conversion process and a fast Fourier transform (FFT) process on the image signal output from the line sensor 352, and performs a depth-direction measurement at one point on the fundus Er of the eye E to be examined. A tomographic image (A scan image) is constructed (formed).
Thereafter, in the imaging device 120, the XY scanner 315 is driven in the x direction to generate another point of interference light on the fundus Er of the eye E, and when this is detected by the line sensor 352, the reconstruction unit 410 An image signal based on the detection is acquired from the line sensor 352. Then, the reconstruction unit 410 configures (forms) a tomographic image (A scan image) in the depth direction at another point on the fundus Er of the eye E to be examined. It is assumed that the position of the XY scanner 315 that captured each A scan image and the coordinates of each A scan image are stored in association with each other.
Then, by continuously driving the XY scanner 315 in the x direction, the reconstruction unit 410 reconstructs (forms a single tomographic image (B scan image) in the horizontal direction of the fundus Er of the eye E to be examined). )
Thereafter, in the imaging apparatus 120, the XY scanner 315 is driven in the y direction by a certain amount, and then the x direction scan described above is performed again, whereby a tomographic image (B scan) at another y direction position on the fundus Er of the eye E to be examined. Image) is reconstructed (formed).
Then, by repeatedly driving the XY scanner 315 in the y direction, the reconstruction unit 410 reconstructs (forms) a plurality of tomographic images (B-scan images) that cover a predetermined range of the fundus Er. Specifically, in this embodiment, the reconstruction unit 410 reconstructs 128 tomographic images (B-scan images) by repeatedly performing B-scan while performing a certain amount of micro-drive 128 times in the y-direction. (Form.
Further, the reconstruction unit 410 reconstructs (forms) a three-dimensional tomographic image from the 128 tomographic images (B-scan images).

  The layer recognizing unit 420 performs recognition processing of the layer structure in the depth direction of the fundus Er (here, the layer structure of the retina) from the tomographic image of the fundus Er formed by the reconstructing unit 410, and Identify the shape.

  The image generation processing unit 430 performs processing for generating a front image that is a two-dimensional image of the fundus Er of the eye E to be examined viewed from the front from the tomographic image of the fundus Er formed by the reconstruction unit 410. For example, the image generation processing unit 430 selects a predetermined pixel from each pixel value sequence in the depth direction of the tomographic image of the fundus oculi Er for each pixel value sequence and generates a front image. As shown in FIG. 4, the image generation processing unit 430 includes a tomographic image input unit 431, a depth range setting unit 432, a layer image extraction unit 433, a first representative value calculation unit 434, and a second representative value calculation unit 435. , And a front image generation unit 436.

  The tomographic image input unit 431 performs processing for inputting the tomographic image of the fundus oculi Er formed by the reconstruction unit 410 to the image generation processing unit 430.

  The depth range setting unit 432 is a target for generating a front image from a range in the depth direction of the tomographic image of the fundus Er formed by the reconstruction unit 410 based on, for example, information input from the operation input unit 118. A process of setting a predetermined depth range which is a range is performed.

  Based on the result of layer recognition by the layer recognition unit 420, the layer image extraction unit 433 includes a plurality of layers included in a predetermined depth range in the depth direction of the fundus Er from the tomographic image of the fundus Er formed by the reconstruction unit 410. The layer image is extracted for each layer. Specifically, the layer image extraction unit 433 extracts a layer image of each layer included in the predetermined depth range set by the depth range setting unit 432 from the tomographic image of the fundus oculi Er formed by the reconstruction unit 410. I do.

  Based on the layer image of each layer extracted by the layer image extraction unit 433, the first representative value calculation unit 434 performs a process of calculating a first representative value that is a representative value in the depth direction for each layer. .

  The second representative value calculation unit 435 uses the first representative value of each layer calculated by the first representative value calculation unit 434 as a representative value in a predetermined depth range set by the depth range setting unit 432. A process of calculating a second representative value is performed.

  The front image generation unit 436 uses the second representative value calculated by the second representative value calculation unit 435 to generate a front image that is a two-dimensional image when the fundus Er of the eye E is viewed from the front. I do.

Next, a processing procedure in the image processing method performed by the image processing apparatus 110 will be described.
FIG. 5 is a flowchart illustrating an example of a processing procedure in the image processing method by the image processing apparatus 110 according to the first embodiment of the present invention.

  The flowchart shown in FIG. 5 specifically shows the processing procedure of the processing in the image generation processing unit 430 shown in FIG. In this embodiment, as the operation mode of the image generation processing unit 430, a front image is generated from the entire depth range in the depth direction (A scan direction) of the tomographic image of the fundus oculi Er formed by the reconstruction unit 410. And a second mode in which a front image is generated from a partial depth range in the depth direction (A scan direction) of the tomographic image of the fundus oculi Er formed by the reconstruction unit 410. . In the first mode, a Projection image is generated as a front image, which is also called an intensity image, and is similar to the surface image of the fundus oculi Er. In the second mode, an EnFace image is generated as a front image, which is used to visualize changes in the layer structure of the retina due to an eye disease. In the following description of FIG. 5, the case where the image generation processing unit 430 is driven in the second mode to generate an EnFace image as a front image will be described.

  First, in step S <b> 501, the tomographic image input unit 431 performs processing for inputting the tomographic image of the fundus Er formed by the reconstruction unit 410 to the image generation processing unit 430.

  Subsequently, in step S502, the depth range setting unit 432 generates an EnFace image from the range in the depth direction of the tomographic image input in step S501 based on, for example, information input from the operation input unit 118. The process which sets the predetermined depth range which is the range which becomes becomes is performed.

  FIG. 6 is a diagram illustrating a setting example of the predetermined depth range in step S502 of FIG. FIG. 6 shows a tomographic image (B-scan image) 600 of the fundus oculi Er formed by the reconstruction unit 410. In FIG. 6, the depth range setting unit 432 generates an EnFace image from the range in the depth direction (z direction) of the tomographic image, as indicated by the arrow between the boundary line Z1 and the boundary line Z2. An example is shown in which the predetermined depth range is set. This predetermined depth range includes two retinal layers L1 and L2.

  In the example illustrated in FIG. 6, a case where two layers (L1 and L2) are included in the predetermined depth range is illustrated, but a plurality of layers may be included in the predetermined depth range. . Further, in the example shown in FIG. 6, the positions of the boundary lines Z1 and Z2 coincide with the boundary of each layer. However, in the present embodiment, the position is not limited to this, and for example, a certain distance from any layer boundary It may be a shifted position or the like. In this case, it is convenient that the boundary lines Z1 and Z2 can be moved up and down with the mouse 118-1. Furthermore, the shape of the layer boundary may not be used as the boundary line. For example, two straight lines can be set at arbitrary depth positions in the tomographic image, and a predetermined depth range can be set between the two straight lines.

  FIG. 7 is a graph showing changes in luminance values (pixel values) in the depth direction (A scan direction) at A (x, y) in the tomographic image 600 shown in FIG. In FIG. 7, the same reference numerals are given to the portions corresponding to the configuration shown in FIG. In FIG. 7, the horizontal axis indicates the position in the depth direction (A scan direction), and the vertical axis indicates the luminance value (pixel value).

  The tomographic image 600 shown in FIG. 6 takes a value in which the luminance value (pixel value) changes greatly according to each layer L1 and L2, as shown in FIG. In the example shown in FIG. 7, the layer L1 shows a highly reflective luminance value, and the layer L2 shows a low reflective luminance value compared to the layer L1.

Here, it returns to description of FIG. 5 again.
When the process of step S502 ends, the process proceeds to step S503. In step S503, the layer image extraction unit 433 determines the predetermined depth set in step S502 from the tomographic image of the fundus Er formed by the reconstruction unit 410 based on the result of layer recognition by the layer recognition unit 420. A process of extracting a layer image for each of a plurality of layers included in the range is performed.

  FIG. 8 is a diagram illustrating an example of extracting the layer image of each layer in step S503 in FIG. Specifically, FIG. 8A illustrates an example in which the layer image 810 of the layer L1 is extracted from the tomographic image 600 illustrated in FIG. 6, and is a range where the hatched portion is specifically extracted. Further, FIG. 8B shows an example in which the layer image 820 of the layer L2 is extracted from the tomographic image 600 shown in FIG. 6, and is a range where the hatched portion is specifically extracted. Further, FIG. 8 (a) shows the thickness d1 of the layer L1, and FIG. 8 (b) shows the thickness d2 of the layer L2.

Here, it returns to description of FIG. 5 again.
When the process of step S503 ends, the process proceeds to step S504. In step S504, the first representative value calculation unit 434 calculates a first representative value that is a representative value in the depth direction for each layer, based on the layer image of each layer extracted in step S503. Process.

A specific processing example of step S504 will be described below.
When the layer image of each layer is extracted in step S503, the first representative value calculation unit 434, for each (x, y) coordinate, the first representative value Mi that is the representative value in the depth direction for each layer. Calculate (x, y). Here, i indicates a number for identifying a layer included in a predetermined depth range, and i = 1 or 2 in the example shown in FIG. Further, here, the first representative value Mi (x, y) in the depth direction of each layer is the center in the luminance value (pixel value) in the depth direction (z direction) of each layer at each (x, y) coordinate. A value (for example, a median value in a histogram distribution of luminance values (pixel values)) is adopted. Here, as the first representative value Mi (x, y) in the depth direction of each layer, the median value in the luminance value (pixel value) in the depth direction of each layer is adopted. For example, an average value of luminance values (pixel values) in the depth direction of each layer may be used.

  Subsequently, in step S505, the second representative value calculation unit 435 uses the first representative value of each layer calculated in step S504 and is the representative value in the predetermined depth range set in step S502. A process of calculating a representative value of 2 is performed.

A specific processing example of step S505 will be described below.
When the first representative value Mi (x, y) in the depth direction of each layer is calculated in step S504, the second representative value calculation unit 435 uses a predetermined depth, for example, using the following equation (1). A second representative value V (x, y) representing the range is calculated.

  In this equation (1), d1 (x, y) is the thickness of the layer L1 at the coordinates (x, y), and d2 (x, y) is the thickness of the layer L2 at the coordinates (x, y). In this calculation, the denominator may be zero depending on how the predetermined depth range is set. In this case, zero may be used as the second representative value V (x, y).

  For example, in the fovea, layers such as the inner limiting membrane layer, nerve fiber layer, and ganglion cell layer usually have zero thickness. When these layers are selected as the predetermined depth range, the denominator may become zero in the fovea. In such a case, zero may be used as the second representative value V (x, y). Also, other than the fovea, for example, in the optic papilla, these layers themselves disappear, so the layer thickness may be zero. In this case, the second representative value V (x, y) is Use zero.

  The above formula (1) shows an example of calculation when two layers are included in a predetermined depth range. For example, when n layers (n is an integer of 3 or more) are included in a predetermined depth range. The second representative value V (x, y) representing the predetermined depth range is calculated using the following equation (2).

  In the present embodiment, as shown in the above-described formulas (1) and (2), the second representative value calculation unit 435 determines whether the second representative value calculation unit 435 corresponds to the thickness di (x, y) of each layer in the depth direction. The first representative value Mi (x, y) is weighted to calculate the second representative value V (x, y). As a result of the calculation as described above, it is possible to obtain a good EnFace image reflecting the image information of each layer. Further, in the present embodiment, as the thickness in the depth direction of each layer weighted to the first representative value Mi (x, y) of each layer, as shown in the equations (1) and (2), The thickness di (x, y) in the depth direction at the position ((x, y) coordinate) is used.

  Subsequently, in step S506, the front image generation unit 436 performs a process of generating an EnFace image as a front image using the second representative value calculated in step S506. For example, in the present embodiment, as described above in the description of the reconstruction unit 410, since there are 128 tomographic images (B-scan images) 600 in FIG. 6, the image generation processing unit 430 determines each tomographic image. The process of steps S501 to S505 is performed to generate an EnFace image. Here, since it is a well-known technique to generate an EnFace image that is a front image from a representative value, description thereof is omitted.

  When the process of step S506 ends, the process of the flowchart shown in FIG. 5 ends.

FIG. 9 is a diagram for explaining an EnFace image generated by the process of the flowchart shown in FIG.
Specifically, FIG. 9A is a diagram illustrating an example of the distribution of the first representative value M1 (x, y) in the depth direction of the layer L1. FIG. 9B is a diagram illustrating an example of a distribution in the first representative value M2 (x, y) in the depth direction of the layer L2. FIG. 9C is a diagram illustrating an example of an EnFace image generated using the second representative value V (x, y) obtained by the above-described equation (1).

  In the process of the flowchart shown in FIG. 5 described above, a partial depth range in the depth direction of the tomographic image is set as a predetermined depth range in step S502, and an EnFace image is generated as a front image in step S506. there were. Here, in this embodiment, it is not limited to the aspect which produces | generates an EnFace image as a front image, For example, the aspect which produces | generates a Projection image as a front image is applicable. In this case, the image generation processing unit 430 is driven in the first mode, and the entire depth range in the depth direction of the tomographic image is set as a predetermined depth range in step S502, and the projection image is set as the front image in step S506. Will be generated.

  Further, in the processing of the flowchart shown in FIG. 5 described above, in the calculation of the second representative value V (x, y) in step S505, as shown in the equations (1) and (2), the first of each layer The thickness in the depth direction of each layer is weighted to the representative value Mi (x, y). The present embodiment is not limited to this mode. For example, in step S505, the average value of the first representative values Mi (x, y) of each layer is simply calculated, and the average value is set to the second value. A mode in which the representative value V (x, y) is used is also applicable. Further, for example, in step S504 in FIG. 5, for example, layer images and the like may be sorted in order of size, and a layer image or the like having a predetermined order may be selected from the sorted images.

Next, an image display example of the image processing apparatus 110 according to the present embodiment will be described.
10 and 11 are diagrams showing examples of image display on the monitor 117 of the image processing apparatus 110 according to the first embodiment of the present invention.

  FIG. 10 shows a state in which the fundus surface image S, the tomographic image (B scan image) Ti, and the projection image P generated in the imaging system 100 are displayed side by side on the monitor 117. In FIG. 10, the acquisition position Li of the tomographic image Ti is superimposed on the Projection image P and the surface image S. Further, the Projection image P can be switched to the EnFace image E and displayed by switching means (not shown).

  In addition, as shown in FIG. 11, the tomographic image (B scan image) Ti, the projection image P, and the EnFace image E generated by the imaging system 100 can be displayed side by side on the monitor 117.

  In the present embodiment, as described above when describing the reconstruction unit 410, 128 tomographic images (B-scan images) are generated. In this case, for example, the monitor 117 shown in FIG. 10 and FIG. 11 has a tomographic image Ti (i = 0 to 128) as one selected cross section, or a cross section of a tomographic image reconstructed in three dimensions. An image Ti (in this case, an arbitrary number i is assigned) is displayed. At this time, it is assumed that the examiner can switch the tomographic image Ti to be displayed by operating the operation input unit 118.

  When the tomographic image Ti is switched, the display position of the acquisition position Li of the tomographic image Ti displayed on the Projection image P, the EnFace image E, and the surface image S is also updated. Thereby, the examiner can easily grasp the position of the displayed tomographic image Ti on the fundus Er of the eye E to be examined. When the acquisition position Li is placed on the EnFace image E, it is also possible to observe while comparing the structural change of the inspection object in the predetermined depth range and the tomographic image Ti.

  In this embodiment, the fundus Er of the eye E is applied as the object to be inspected, and an EnFace image and a Projection image are generated using the tomographic image of the fundus Er. The form is not limited. For example, a form in which the anterior eye part of the eye E to be examined is applied as the object to be inspected, and the EnFace image and the projection image are generated using the tomographic image of the anterior eye part is also applicable to the present invention.

In the first embodiment, a first representative value that is a representative value in the depth direction is calculated for each layer included in a predetermined depth range of the tomographic image of the fundus Er, and the calculated first representative value of each layer is calculated. Based on this, a front image of the fundus oculi Er is generated.
According to such a configuration, even when a plurality of layers are included in a predetermined depth range of the fundus Er for generating the front image, a good front image reflecting the image information of each layer can be acquired.

(Second Embodiment)
Next, a second embodiment of the present invention will be described.

  In the first embodiment described above, as shown in the equations (1) and (2), the thickness in the depth direction of each layer weighted to the first representative value Mi (x, y) of each layer is as follows. The thickness di (x, y) in the depth direction at each position ((x, y) coordinate) was used. In the present invention, the present invention is not limited to this form, and the second embodiment shown below can also be applied.

  The schematic configuration of the imaging system according to the second embodiment is the same as the schematic configuration of the imaging system 100 according to the first embodiment shown in FIG. The external configuration of the image processing apparatus 110 and the imaging apparatus 120 shown in FIG. 1 according to the second embodiment and the internal configuration of the imaging apparatus 120 are the same as those of the image processing according to the first embodiment shown in FIG. The external configuration of the apparatus 110 and the imaging apparatus 120 and the internal configuration of the imaging apparatus 120 according to the first embodiment shown in FIG. 3 are the same. The functional configuration of the image processing apparatus 110 according to the second embodiment is the same as the functional configuration of the image processing apparatus 110 according to the first embodiment shown in FIG. The processing procedure in the image processing method by the image processing apparatus 110 according to the second embodiment is the same as the flowchart showing the processing procedure in the image processing method by the image processing apparatus 110 according to the first embodiment shown in FIG. is there.

  In the second embodiment, the detailed processing contents when calculating the second representative value V (x, y) in step S505 in FIG. 5 are different from those in the first embodiment. In the description of the embodiment, only portions different from the first embodiment will be described.

  In the second embodiment, in step S505 of FIG. 5, the second representative value calculation unit 435 calculates the depth at each position ((x, y) coordinate) of each layer as in the first embodiment. First, an average thickness that is an average thickness in the depth direction of each layer is obtained without using the thickness di (x, y) in the direction. Then, the second representative value calculation unit 435 weights the first representative value Mi (x, y) of each layer according to the average thickness in the depth direction of each layer, and obtains the second representative value V (x , Y). Specifically, the second representative value calculation unit 435 in the second embodiment calculates the second representative value V (x, y) that represents a predetermined depth range using, for example, the following expression (3). calculate.

  In the formula (3), davg1, davg2,..., Davn is an average thickness in the depth direction of each layer (L1, L2,..., Ln) included in a predetermined depth range. In this calculation, the denominator may be zero depending on how the predetermined depth range is set. In this case, zero may be used as the second representative value V (x, y). In addition, weighting the first representative value Mi (x, y) of each layer according to the average thickness in the depth direction of each layer corresponds to generating a front image (such as an EnFace image) for each layer. In other words.

In the second embodiment, the first representative value calculated for each layer included in the predetermined depth range of the tomographic image of the fundus Er is weighted according to the average thickness in the depth direction of each layer, and the fundus Er A front image is generated.
According to such a configuration, even when a plurality of layers are included in a predetermined depth range of the fundus Er for generating the front image, a good front image reflecting the image information of each layer can be acquired.

(Third embodiment)
Next, a third embodiment of the present invention will be described.

  In the first embodiment described above, as shown in the equations (1) and (2), the thickness in the depth direction of each layer weighted to the first representative value Mi (x, y) of each layer is as follows. The thickness di (x, y) in the depth direction at each position ((x, y) coordinate) was used. In the present invention, the present invention is not limited to this form, and the third embodiment shown below can also be applied.

  The schematic configuration of the imaging system according to the third embodiment is the same as the schematic configuration of the imaging system 100 according to the first embodiment shown in FIG. The external configuration of the image processing apparatus 110 and the imaging apparatus 120 shown in FIG. 1 according to the third embodiment and the internal configuration of the imaging apparatus 120 are the same as those of the image processing according to the first embodiment shown in FIG. The external configuration of the apparatus 110 and the imaging apparatus 120 and the internal configuration of the imaging apparatus 120 according to the first embodiment shown in FIG. 3 are the same. The functional configuration of the image processing apparatus 110 according to the third embodiment is the same as the functional configuration of the image processing apparatus 110 according to the first embodiment shown in FIG. The processing procedure in the image processing method by the image processing apparatus 110 according to the third embodiment is the same as the flowchart showing the processing procedure in the image processing method by the image processing apparatus 110 according to the first embodiment shown in FIG. is there.

  In the third embodiment, the detailed processing contents when calculating the second representative value V (x, y) in step S505 in FIG. 5 are different from those in the first embodiment. In the description of the embodiment, only portions different from the first embodiment will be described.

  In the third embodiment, in step S505 of FIG. 5, the second representative value calculation unit 435 calculates the depth at each position ((x, y) coordinate) of each layer as in the first embodiment. Without using the thickness di (x, y) in the direction, first, the standard deviation of the luminance value (pixel value) in the depth direction of each layer (each layer image) and its average value are obtained. Then, the second representative value calculation unit 435 divides the standard deviation of the pixel values in the depth direction of each layer (each layer image) by the average value of the pixel values according to the first representative value Mi ( x, y) is weighted to calculate a second representative value V (x, y). Specifically, the second representative value calculation unit 435 in the third embodiment calculates the second representative value V (x, y) representing a predetermined depth range using, for example, the following equation (4). calculate.

  In this equation (4), σi is the standard deviation of the pixel values in the depth direction of the i-th layer (layer image) included in the predetermined depth range, and Avgi is the i-th included in the predetermined depth range. This is the average value of the pixel values in the depth direction of the layer (layer image). Further, in the expression (4), as described in the expression (5), si represents the standard deviation σi of the pixel value in the depth direction of the i-th layer (layer image) as the i-th layer (layer image). The pixel value is divided by the average value Avgi of the pixel values in the depth direction.

In the third embodiment, when calculating the second representative value V (x, y), the first representative value Mi (x, y) of each layer is weighted according to the pixel value in the depth direction of each layer. Like to do. Specifically, the first representative value Mi (x, y) of each layer is weighted according to the result of dividing the standard deviation of the pixel values in the depth direction of each layer by the average value of the pixel values, and the second The representative value V (x, y) is calculated.
According to such a configuration, in addition to the effects in the first and second embodiments, by performing the process of increasing the weight of the layer having a relatively large standard deviation of the pixel value as compared with each other, A front image with enhanced image information can be generated.

(Fourth embodiment)
Next, a fourth embodiment of the present invention will be described.

  In the first embodiment described above, as shown in the equations (1) and (2), the thickness in the depth direction of each layer weighted to the first representative value Mi (x, y) of each layer is as follows. The thickness di (x, y) in the depth direction at each position ((x, y) coordinate) was used. In the present invention, the present invention is not limited to this form, and the following fourth embodiment is also applicable. Specifically, in the fourth embodiment, the examiner can selectively adjust information on a desired layer, and the first representative value Mi (x, y) of each layer is weighted in consideration of the adjustment content. Is what you do.

  The schematic configuration of the imaging system according to the fourth embodiment is the same as the schematic configuration of the imaging system 100 according to the first embodiment shown in FIG. The external configuration of the image processing apparatus 110 and the imaging apparatus 120 shown in FIG. 1 according to the fourth embodiment and the internal configuration of the imaging apparatus 120 are the same as those of the image processing according to the first embodiment shown in FIG. The external configuration of the apparatus 110 and the imaging apparatus 120 and the internal configuration of the imaging apparatus 120 according to the first embodiment shown in FIG. 3 are the same. The functional configuration of the image processing apparatus 110 according to the fourth embodiment is the same as the functional configuration of the image processing apparatus 110 according to the first embodiment shown in FIG. The processing procedure in the image processing method by the image processing apparatus 110 according to the fourth embodiment is the same as the flowchart showing the processing procedure in the image processing method by the image processing apparatus 110 according to the first embodiment shown in FIG. is there.

  In the fourth embodiment, the detailed processing contents when calculating the second representative value V (x, y) in step S505 in FIG. 5 are different from those in the first embodiment. In the description of the embodiment, only portions different from the first embodiment will be described.

  Specifically, in the present embodiment, in step S505 in FIG. 5, the second representative value calculation unit 435 calculates the second representative value that is the representative value in the predetermined depth range set in step S502. In addition to the thickness in the depth direction of each layer, the first representative value of each layer is weighted according to the display intensity adjusted for each layer.

  FIG. 12 is a diagram showing an example of an adjustment screen 1200 for display intensity of each layer for weighting the first representative value of each layer according to the fourth embodiment of the present invention. This adjustment screen 1200 is displayed on the monitor 117.

  In the adjustment screen 1200 of FIG. 12, the name of each layer in the retina of the eye E is shown in the layer name display area 1210. Next to the name of each layer displayed in the layer name display area 1210, a slider 1220 representing an upper limit 1221 and a lower limit 1222 in a predetermined depth range that is currently set, and a slider 1230 representing the display intensity of each layer. Is provided.

  In the example shown in FIG. 12, the upper limit 1221 of the predetermined depth range defined by the slider 1220 is located between the inner limiting membrane and the nerve fiber layer, and the lower limit 1222 is the difference between the inner reticulated layer and the inner granular layer. Located between. Correspondingly, the slider 1230 positioned outside the predetermined depth range defined by the slider 1220 is not operable by the examiner (displayed in gray in FIG. 12). The example shown in FIG. 12 shows that the examiner can only operate the slider 1230 of the nerve fiber layer, ganglion cell layer, and inner reticulated layer (shown in black in FIG. 12). The slider 1230 has a center of 0% (meaning that the display intensity is not changed), and can be adjusted by changing the display intensity within a range of ± 30%. The setting shown in FIG. 12 may be set on the initial setting screen as a setting shared by all the examinees, or from a display screen that displays each examinee's examination. It may be settable.

  In the present embodiment, specifically, in step S505 of FIG. 5, the second representative value calculation unit 435 sets the first representative value Mi (x, y) in the depth direction of each layer calculated in step S504. On the other hand, the weight value ei (x, y) shown in the following equation (6) is weighted, and the second representative value V (x, y) representing the predetermined depth range shown in the following equation (7). Is calculated.

  Here, in the equation (6), ai represents the display intensity adjusted with respect to the layer i (for example, 0.3 in the case of + 30% in FIG. 12).

In the fourth embodiment, when calculating the second representative value V (x, y), in addition to the thickness di (x, y) in the depth direction of each layer, the display further adjusted for each layer The first representative value Mi (x, y) of each layer is weighted according to the strength ai.
According to such a configuration, in addition to the effects in the first embodiment, the examiner can selectively increase or decrease the information of a specific layer, so that a front image desired by the examiner is generated. be able to.

(Other embodiments)
In the first embodiment described above, as shown in the equations (1) and (2), the thickness in the depth direction of each layer weighted to the first representative value Mi (x, y) of each layer is as follows. The thickness di (x, y) in the depth direction at each position ((x, y) coordinate) was used. In the present invention, not limited to this form, for example, the thickness in the depth direction of each layer weighted to the first representative value Mi (x, y) of each layer is the depth direction in the local position of each layer. A form using thickness is also applicable to the present invention. At this time, the local position of each layer can be selected by an arbitrary method, for example.

The present invention supplies a program that realizes one or more functions of the above-described embodiments to a system or apparatus via a network or a storage medium, and one or more processors in a computer of the system or apparatus read and execute the program This process can be realized. It can also be realized by a circuit (for example, ASIC) that realizes one or more functions.
This program and a computer-readable storage medium storing the program are included in the present invention.

  Note that the above-described embodiments of the present invention are merely examples of implementation in practicing the present invention, and the technical scope of the present invention should not be construed as being limited thereto. It is. That is, the present invention can be implemented in various forms without departing from the technical idea or the main features thereof.

430 image generation processing unit, 431 tomographic image input unit, 432 depth range setting unit, 433 layer image extraction unit, 434 first representative value calculation unit, 435 second representative value calculation unit, 436 front image generation unit

Claims (16)

Extraction means for extracting a layer image for each layer of a plurality of layers included in a predetermined depth range in the depth direction of the inspection object from a tomographic image of the inspection object having a layer structure;
First representative value calculating means for calculating a first representative value that is a representative value in the depth direction for each of the layers, based on the layer image of the layers extracted by the extracting means;
Second representative value calculating means for calculating a second representative value, which is a representative value in the predetermined depth range, using the first representative value of each layer calculated by the first representative value calculating means. When,
An image processing apparatus comprising: a generating unit configured to generate a front image of the inspection object using the second representative value. The predetermined depth range is a partial depth range in the depth direction of the tomographic image,
The image processing apparatus according to claim 1, wherein the generation unit generates an EnFace image as the front image. The predetermined depth range is the entire depth range in the depth direction of the tomographic image,
The image processing apparatus according to claim 1, wherein the generation unit generates a Projection image as the front image. From the range in the depth direction of the tomographic image, further comprising setting means for setting the predetermined depth range,
The said extraction means extracts the said layer image of each said layer included in the said predetermined depth range set by the said setting means from the said tomographic image, The any one of Claim 1 thru | or 3 characterized by the above-mentioned. The image processing apparatus described. A layer recognition means for recognizing a layer in the depth direction of the inspection object from the tomographic image;
5. The extraction unit according to claim 1, wherein the extraction unit extracts the layer image of each layer included in the predetermined depth range based on a result of layer recognition by the layer recognition unit. An image processing apparatus according to 1.   6. The first representative value calculating means calculates a median value or an average value of pixel values in the depth direction of each layer as the first representative value of each layer. The image processing apparatus according to any one of the above.   The said 2nd representative value calculation means calculates the average value in the said 1st representative value of each said layer as said 2nd representative value, The any one of Claim 1 thru | or 6 characterized by the above-mentioned. Image processing apparatus.   The second representative value calculating means weights the first representative value of each layer according to the thickness of each layer in the depth direction when calculating the second representative value. The image processing apparatus according to any one of claims 1 to 6.   The image processing apparatus according to claim 8, wherein a thickness of each layer in the depth direction is a thickness in the depth direction at each position of the layers.   The image processing apparatus according to claim 8, wherein the thickness of each layer in the depth direction is an average thickness of the layers in the depth direction.   The image processing apparatus according to claim 8, wherein a thickness of each layer in the depth direction is a thickness in the depth direction at a local position of each layer.   When calculating the second representative value, the second representative value calculating means further adds the thickness of each layer according to the display intensity adjusted for each layer in addition to the thickness of each layer in the depth direction. The image processing apparatus according to claim 8, wherein the first representative value is weighted.   The second representative value calculating means weights the first representative value of each layer according to a pixel value in the depth direction of each layer when calculating the second representative value. The image processing apparatus according to claim 1, wherein the image processing apparatus is an image processing apparatus.   The second representative value calculating means weights the first representative value of each layer according to a result obtained by dividing a standard deviation of the pixel value by an average value of the pixel value. The image processing apparatus according to 13. An extraction step of extracting a layer image for each layer of a plurality of layers included in a predetermined depth range in the depth direction of the inspection object from a tomographic image of the inspection object having a layer structure;
A first representative value calculating step of calculating a first representative value that is a representative value in the depth direction for each layer based on the layer image of each layer extracted in the extracting step;
A second representative value calculating step of calculating a second representative value that is a representative value in the predetermined depth range by using the first representative value of each layer calculated in the first representative value calculating step. When,
An image processing method comprising: generating a front image of the inspection object using the second representative value.   The program for functioning a computer as each means of the image processing apparatus of any one of Claims 1 thru | or 14.