JP6992030B2 - Image generator, image generation method and program - Google Patents

Description

The disclosed technique relates to an image generator, an image generation method and a program.

Optical coherence tomography (hereinafter referred to as OCT) has been put into practical use as a method for acquiring a tomographic image of a measurement target such as a living body in a non-destructive and non-invasive manner. OCT is widely used in ophthalmic diagnosis of the retina because a tomographic image of the retina in the fundus of the eye to be inspected is acquired, especially in the field of ophthalmology.

OCT obtains a tomographic image by interfering the light reflected from the measurement target with the light reflected from the reference mirror and analyzing the time dependence or wave number dependence of the interfering light intensity. As such an optical coherence tomographic image acquisition device, a time domain OCT that obtains depth information of a measurement target by changing the position of a reference mirror is known. Further, a spectral domain OCT (SD-OCT: Spectral Domain Optical Coherence Tomography) using a wide band light source is known. Further, a wavelength sweeping optical coherence tomography (SS-OCT) device using a wavelength variable light source device capable of changing the oscillation wavelength as a light source is known. In addition, SD-OCT and SS-OCT are collectively referred to as (FD-OCT: Fourier Optic Coherence Tomography).

In recent years, a pseudo-angiography method using this FD-OCT has been proposed and is called OCT angiography (OCTA).

Fluorescence, a common angiography technique in modern clinical medicine, requires the injection of a fluorescent dye (eg, fluorescein or indocyanine green) into the body. While the blood vessels that serve as the path of the fluorescent dye are displayed two-dimensionally, OCT angiography enables non-invasive and pseudo-angiography, and it is possible to display the network of blood flow sites three-dimensionally. Furthermore, it is attracting attention because it has a higher resolution than fluorescence contrast and can visualize microvessels or blood flow in the fundus.

A plurality of methods have been proposed for OCT angiography depending on the difference in blood flow detection method. A method (Non-Patent Document 1) has been proposed in which an OCT signal from a bloodstream is separated by extracting only a signal in which time modulation occurs from the OCT signal. Further, a method utilizing a variation in phase due to blood flow (Non-Patent Document 2), a method utilizing a variation in intensity due to blood flow (Non-Patent Document 3 and Patent Document 1), and the like have been proposed. In the present specification, a signal obtained by time modulation from an OCT signal may be referred to as a motion contrast image, a pixel value thereof may be referred to as a motion contrast, and a data set thereof may be referred to as a motion contrast data.

U.S. Patent Application Publication No. 2014/221827

Fingerr et al. "Mobility and transition flow visualization using contrast contrast with spectral coherence tomography" Optics Express. Vol. 15, No. 20. pp 12637-126553 (2007) Optics Letters Vol. 33, Iss. 13, pp. 1530-1532 (2008) "Speckle variance detection of optical coherence tomography" Mariamplai et al. , "Optimized speckle value OCT imaging of optics culture," Optics Letters 35, 1257-1259 (2010).

However, in the above-mentioned OCT angiography, the depiction of the blood flow site is not sufficiently clear or buried in the noise due to the influence of strong reflected light from the retinal pigment epithelium (RPE) and various noises, and the diagnosis is made. It was difficult to easily obtain a motion contrast image suitable for.

The disclosed technology aims at rapid and appropriate depiction of motion contrast images. Specifically, it is an object of the present invention to provide an image forming method and an apparatus for removing unnecessary noise from a motion contrast image by using structural information of a retinal region and drawing a motion contrast image useful for diagnosis.

The disclosed technique has been made in view of the above problems, and one of the purposes is to generate an appropriate motion contrast image.

Not limited to the above-mentioned purpose, it is also an action and effect derived by each configuration shown in the embodiment for carrying out the invention described later, and it is also another purpose of the present invention to exert an action and effect which cannot be obtained by the conventional technique. It can be positioned as one.

One of the disclosed image generation methods is
A step of calculating a motion contrast value using the corresponding pixel data between a plurality of tomographic image data of the eye to be inspected obtained by scanning substantially the same position of the eye to be inspected multiple times with measurement light.
Based on the comparison result obtained by comparing the motion contrast value and the threshold value, the step of invalidating the motion contrast value below the threshold value and the step of invalidating the motion contrast value.
The step of aligning the plurality of tomographic image data before the motion contrast value is calculated, and
A step of detecting a plurality of layer boundaries by performing a segmentation process using the averaged images of the plurality of tomographic image data, and
After the invalidation is performed, the motion contrast front image of the eye to be inspected is based on at least one of the plurality of layers classified based on the detected plurality of layer boundaries and the motion contrast value. And the process of generating
It is an initial value automatically set according to the distribution of noise and the distribution of the blood flow region in the histogram of the motion contrast value in the at least one layer, and determines at least one of the plurality of layers. The process of changing the threshold value according to the instruction from the examiner from the initial value automatically changed according to the instruction from the examiner.
A step of regenerating the motion contrast front image of the eye to be inspected based on the at least one determined layer and the comparison result obtained by comparing again using the threshold value obtained by the change. And have.

According to the disclosed technique, it is possible to generate an appropriate motion contrast image.

The figure which shows the outline of an example of the whole structure of the apparatus in this embodiment. The figure which shows an example of the scan pattern in this embodiment. The figure which shows an example of the whole processing procedure in this embodiment. The figure which shows an example of the interference signal acquisition procedure in this embodiment. The figure which shows an example of the signal processing procedure in this embodiment. The figure which shows an example of the 3D blood flow part information acquisition procedure in this embodiment. The figure which shows an example of the method of converting a motion contrast pixel value in this embodiment into a pixel for display. The figure for demonstrating an example of GUI in this embodiment. The figure which shows an example of the motion contrast image when the threshold value in this embodiment is changed. The figure which shows an example of the histogram of the motion region and the non-motion region in this embodiment. The figure which shows an example of the segmentation result in this embodiment. The figure which shows an example of the display information generation procedure in this embodiment. The figure which shows an example of GUI in this embodiment. The figure which shows the outline of an example of the whole structure of the apparatus in this embodiment.

Hereinafter, the image pickup apparatus according to the present embodiment will be described with reference to the attached drawings. The configuration shown in the following embodiments is only an example, and the present invention is not limited to the following embodiments. In the present embodiment, the subject is the human eye (fundus), but the present invention is not limited to this, and the subject may be used, for example, on the skin or the like. Further, although the image pickup target is the fundus of the eye in the present embodiment, the anterior eye may be the image pickup target.

[First Embodiment]
In the present embodiment, the control unit 143, which will be described later, generates a tomographic image from the captured three-dimensional optical interference signal and calculates the motion contrast. Then, the control unit 143 shows an example of adjusting the noise threshold value using the structural information of the site and acquiring the clarified three-dimensional blood flow site information.

[Structure of the entire image forming apparatus]
FIG. 1 is a diagram showing a configuration example of an image forming apparatus using the optical coherence tomography method in the present embodiment. The device shown in FIG. 1 includes an optical interference tomographic acquisition unit 100 and a control unit 143 to acquire an optical interference tomographic signal. The control unit 143 includes a signal processing unit 144, a signal acquisition control unit 145, a display unit 146, and a display control unit 149. The signal processing unit 144 further includes an image generation unit 147 and a map generation unit 148. Here, the control unit 143 is, for example, a computer, and the CPU provided in the computer executes a program stored in a storage device (not shown) to execute a signal processing unit 144, a signal acquisition control unit 145, and an image generation unit 147. It functions as a map generation unit 148 and a display control unit 149.

The CPU and the storage device included in the control unit 143 may be one or a plurality. That is, at least one processing device (CPU) and at least one storage device (RAM and ROM) are connected, and at least one processing device executes a program stored in at least one storage device. In some cases, the control unit 143 functions as each of the above means. The processing device is not limited to the CPU, and may be an FPGA or the like.

First, the configuration of the optical interference fault acquisition unit 100 will be described. FIG. 1 is a diagram showing a configuration example of an OCT device as an example of an optical coherence tomography acquisition unit in the present embodiment. The OCT apparatus is, for example, SD-OCT or SS-OCT. In this embodiment, the configuration when the OCT device is SS-OCT is shown.

<Configuration of OCT device 100>
The configuration of the OCT device 100 will be described.

The light source 101 is a wavelength sweep type (Swept Source: SS) light source, and emits light while sweeping at a sweep center wavelength of 1050 nm and a sweep width of 100 nm, for example. Here, the wavelength and the sweep width are examples, and the present invention is not limited to the above values. Similarly, in the following embodiments, the described numerical values are examples, and the present invention is not limited to the described numerical values.

The light emitted from the light source 101 is guided to the beam splitter 110 via the optical fiber 102 and branched into measurement light (also referred to as OCT measurement light) and reference light (also referred to as reference light corresponding to OCT measurement light). .. The branching ratio of the beam splitter 110 is 90 (reference light): 10 (measurement light). The branched measurement light is emitted via the optical fiber 111 and is converted into parallel light by the collimator 112. The measured light that has become parallel light is incident on the eye to be inspected 118 via the galvano scanner 114, the scan lens 115, and the focus lens 116 that scan the measured light in the fundus Er of the eye to be inspected 118. Here, the galvano scanner 114 is described as a single mirror, but is actually composed of two galvano scanners (X-axis scanner 114a and Y-axis scanner 114b) (not shown) so as to raster scan the fundus Er of the eye 118 to be inspected. is doing. Further, the focus lens 116 is fixed on the stage 117, and the focus can be adjusted by moving in the optical axis direction. The galvano scanner 114 and the stage 117 are controlled by the signal acquisition control unit 145, and the measurement light is measured in a desired range (also referred to as a tomographic image acquisition range, a tomographic image acquisition position, and a measurement light irradiation position) of the fundus Er of the eye to be inspected 118. Can be scanned.

Although not described in detail in this embodiment, it is desirable that a tracking function for detecting the movement of the fundus Er and scanning the mirror of the galvano scanner 114 by following the movement of the fundus Er is provided. The tracking method can be performed by using a general technique, and can be performed in real time or by post-processing. For example, there is a method using a scanning laser ophthalmoscope (SLO). For the fundus Er, a two-dimensional image (fundus surface image) in a plane perpendicular to the optical axis is acquired over time using SLO, and characteristic points such as blood vessel branches in the image are extracted. Real-time tracking can be performed by calculating how the feature points in the acquired two-dimensional image move as the movement amount of the fundus Er, and feeding back the calculated movement amount to the galvano scanner 114.

The measurement light is incident on the eye to be inspected 118 by the focus lens 116 mounted on the stage 117, and is focused on the fundus Er. The measurement light irradiating the fundus Er is reflected and scattered in each retinal layer, and returns to the beam splitter 110 in the above-mentioned optical path. The return light of the measurement light incident on the beam splitter 110 passes through the optical fiber 126 and is incident on the beam splitter 128.

On the other hand, the reference light branched by the beam splitter 106 is emitted via the optical fiber 119a, the polarization controller 150, and the optical fiber 119b, and is converted into parallel light by the collimator 120. The polarization controller 150 can change the polarization of the reference light to a desired polarization state. The reference light enters the optical fiber 127 via the dispersion compensating glass 122, the ND filter 123, and the collimator 124. One end of the collimator lens 124 and the optical fiber 127 is fixed on the coherence gate stage 125, and the signal acquisition control unit 145 is driven in the optical axis direction in response to a difference in the axial length of the subject. Is controlled by. Although the optical path length of the reference light is changed in this embodiment, it is sufficient that the optical path length difference between the optical path of the measurement light and the optical path of the reference light can be changed.

The reference light that has passed through the optical fiber 127 is incident on the beam splitter 128. In the beam splitter 128, the return light of the reference light and the reference light are combined to form interference light, and then split into two. The divided interference light is interference light having phases that are inverted from each other (hereinafter, referred to as a positive component and a negative component). The positive component of the split interference light enters one input port of the detector 141 via the optical fiber 129. On the other hand, the negative component of the interference light is incident on the other side of the detector 141 via the optical fiber 130. The detector 141 is a differential detector, and when two interference lights whose phases are inverted by 180 ° are input, the DC component is removed and the interference signal of only the interference component is output.

The interference light detected by the detector 141 is output as an electric signal (interference signal) according to the intensity of the light, and is input to the signal processing unit 144, which is an example of the tomographic image generation unit.

<Control unit 143>
A control unit 143 for controlling the entire apparatus will be described.

The control unit 143 is composed of a signal processing unit 144, a signal acquisition control unit 145, a display unit 146, and a display control unit 149. Further, the signal processing unit 144 is further configured to have an image generation unit 147 and a map generation unit 148. The image generation unit 147 has a function of generating a luminance image and a motion contrast image from an electric signal (interference signal) sent from the detector 141, and the map generator 148 has a function of generating layer information (retina segmentation) from the luminance image. Have.

The signal acquisition control unit 145 controls each unit as described above. The signal processing unit 144 generates an image, analyzes the generated image, and generates visible information of the analysis result based on the interference signal output from the detector 141.

The image and analysis result generated by the signal processing unit 144 are sent to the display control unit 149, and the display control unit 149 displays the image and the analysis result on the display screen of the display unit 146. Here, the display unit 146 is a display such as a liquid crystal display. The image data generated by the signal processing unit 144 may be transmitted to the display control unit 149 and then to the display unit 146 by wire or wirelessly. Further, in the present embodiment, the display unit 146 and the like are included in the control unit 143, but the present invention is not limited to this, and may be provided separately from the control unit 143, for example, an example of a device that can be carried by a user. It may be a tablet that is. In this case, it is preferable to mount a touch panel function on the display unit so that the display position of the image can be moved, enlarged / reduced, and the displayed image can be changed on the touch panel.

The above is the description of the process of acquiring information about the tomography at one point of the subject 118. Acquiring information about the tomographic fault in the depth direction of the subject 118 in this way is called A-scan. Further, the information about the tomography of the subject in the direction orthogonal to the A-scan, that is, the scanning direction for acquiring the two-dimensional image is scanned in the direction orthogonal to the tomographic image obtained by the B-scan and the B-scan. This is called C-scan. This is because when two-dimensional raster scanning is performed in the bottom of the eye when acquiring a three-dimensional tomographic image, the high-speed scanning direction is B-scan, and the low-speed scanning direction in which B-scan is arranged in the orthogonal direction is C-. Called scan. A two-dimensional tomographic image can be obtained by performing A-scan and B-scan, and a three-dimensional tomographic image can be obtained by performing A-scan, B-scan and C-scan. B-scan and C-scan are performed by the above-mentioned galvano scanner 114.

The X-axis scanner 114a and the Y-axis scanner 114b (not shown) are each composed of deflection mirrors arranged so that their rotation axes are orthogonal to each other. The X-axis scanner 114a scans in the X-axis direction, and the Y-axis scanner 114b scans in the Y-axis direction. Each of the X-axis direction and the Y-axis direction is a direction perpendicular to the eye axis direction of the eyeball and is a direction perpendicular to each other. Further, the line scanning direction such as B-scan and C-scan does not have to coincide with the X-axis direction or the Y-axis direction. Therefore, the line scanning direction of B-scan and C-scan can be appropriately determined according to the two-dimensional tomographic image or the three-dimensional tomographic image to be imaged.

[Scan pattern]
Next, an example of the scan pattern of the present embodiment will be described with reference to FIG.

In OCT angiography, the time change of the OCT interference signal due to blood flow is measured, so that multiple measurements are required at the same place (or substantially the same place). In the present embodiment, the OCT device repeats the B scan at the same place m times and performs a scan that moves to the y position at n locations.

A specific scan pattern is shown in FIG. B scan is repeated m times for each of n positions of y1 to yn on the fundus plane.

When m is large, the number of measurements at the same place increases, so that the accuracy of blood flow detection improves. On the other hand, the scanning time becomes long, and there arises a problem that motion artifacts occur in the image due to eye movements (fixed vision fine movements) during scanning and a problem that the burden on the subject increases. In this embodiment, m = 4 is carried out in consideration of the balance between the two. The control unit 143 may change m according to the A scan speed of the OCT device and the motion analysis of the fundus surface image of the subject 118.

In FIG. 2, p indicates the sampling number of A scan in one B scan. That is, the plane image size is determined by p × n. If p × n is large, a wide range can be scanned at the same measurement pitch, but the scanning time becomes long, and the above-mentioned motion artifact and patient burden problems occur. In this embodiment, n = p = 300 is carried out in consideration of the balance between the two. The above n and p can be freely changed as appropriate.

Further, Δx in FIG. 2 is an interval (x pitch) between adjacent x positions, and Δy is an interval (y pitch) between adjacent y positions. In the present embodiment, the x-pitch and y-pitch are determined as 1/2 of the beam spot diameter of the irradiation light in the fundus and set to 10 μm. By setting the x-pitch and y-pitch to 1/2 of the diameter of the beam spot on the fundus, it is possible to form a high-definition image. Even if the x-pitch and y-pitch are made smaller than 1/2 of the fundus beam spot diameter, the effect of further increasing the definition of the generated image is small.

On the contrary, if the x-pitch and y-pitch are made larger than 1/2 of the fundus beam spot diameter, the definition is deteriorated, but a wide range of images can be acquired with a small data capacity. The x-pitch and y-pitch may be freely changed according to clinical requirements.

The scan range of this embodiment is p × Δx = 3 mm in the x direction and n × Δy = 3 mm in the y direction.

Next, a specific processing procedure of the image forming method of the present embodiment will be described with reference to FIG.
In step S101, the signal acquisition control unit 145 controls the optical interference tomographic image acquisition unit 100 to acquire the optical interference tomographic signal. A detailed description of the process will be described later. In step S102, the control unit 143 generates display information. A detailed description of the process will be described later. By carrying out the above steps, the procedure for processing the image forming method of the present embodiment is completed.

[Interference signal acquisition procedure]
Next, a specific processing procedure for acquiring the interference signal in step S101 of the present embodiment will be described with reference to FIG. In step S109, the signal acquisition control unit 145 sets the index i of the position yi in FIG. 2 to 1. In step S110, the OCT apparatus moves the scan position to yi. In step S119, the signal acquisition control unit 145 repeatedly sets the index j of the B scan to 1. In step S120, the OCT apparatus performs a B scan.

In step S130, the detector 141 detects an interference signal for each A scan, and the interference signal is stored in the signal processing unit 144 via an A / D converter (not shown). The signal processing unit 144 acquires the interference signal of A scan as a p-sample to obtain the interference signal of 1B scan.
In step S139, the signal acquisition control unit 145 repeatedly increments the index j of the B scan.

In step S140, the signal acquisition control unit 145 determines whether j is larger than a predetermined number of times (m). That is, it is determined whether the B scan at the position y is repeated m times. If it is not repeated, the process returns to S120 and the B scan measurement at the same position is repeated. If it is repeated a predetermined number of times, the process proceeds to S149. In step S149, the signal acquisition control unit 145 increments the index i of the position yi. In step S150, the signal acquisition control unit 145 determines whether i is larger than the number of measurements (n) at a predetermined Y position, that is, whether the B scan is performed at all y positions at n locations. If the number of measurements at the predetermined Y position is less than (no), the process returns to S110 and the measurement at the next measurement position is repeated. When the number of measurements at the predetermined Y position is completed (yes), the process proceeds to the next step S160.

In step S160, the OCT apparatus acquires background data. The OCT device measures 100 A-scans with the shutter 85 closed, and the signal acquisition control unit 145 averages and stores 100 A-scans. The number of background measurements is not limited to 100.

By carrying out the above steps, the interference signal acquisition procedure in the present embodiment is completed.

[Signal processing procedure]
Next, a specific process for generating three-dimensional blood flow site information in step S102 of the present embodiment will be described with reference to FIG.

In this embodiment, it is necessary to calculate the motion contrast of the OCT angiography in order to generate the three-dimensional blood flow site information from the OCT angiography information.

Here, motion contrast is defined as a contrast between a flowing tissue (for example, blood) and a non-flowing tissue among the subject tissues. The feature amount expressing the motion contrast is simply defined as the motion contrast (or the motion contrast feature amount, the motion contrast value). The motion contrast will be described later.

In step S210, the signal processing unit 144 sets the index i of the position yi to 1. In step S220, the signal processing unit 144 extracts the repeated B scan interference signal (m times) at the position yi. In step S230, the signal processing unit 144 repeatedly sets the index j of the B scan to 1. In step S240, the signal processing unit 144 extracts the j-th B scan data.

In step S250, the signal processing unit 144 generates a luminance image of a tomographic image by performing a general reconstruction process on the interference signal of the B scan data of step S240.

First, the image generation unit 147 removes fixed pattern noise consisting of background data from the interference signal. Fixed pattern noise removal is performed by extracting fixed pattern noise by averaging the A scan signals of a plurality of detected background data and subtracting the fixed pattern noise from the input interference signal. Next, the image generation unit 147 performs a desired window function processing in order to optimize the depth resolution and the dynamic range, which are in a trade-off relationship when the Fourier transform is performed in a finite interval. After that, a luminance image of a tomographic image is generated by performing FFT processing. In step S260, the signal processing unit 144 repeatedly increments the index j of the B scan. In step S270, it is determined whether the signal processing unit 144 is larger than m. That is, it is determined whether the luminance calculation of the B scan at the position y is repeated m times. In the case of no, the process returns to step S240, and the luminance calculation of the repeated B scan at the same Y position is repeated. That is, the image generation unit 147 acquires a plurality of tomographic image data (tomographic images) of the subject indicating a tomographic image at substantially the same location of the subject.

On the other hand, if yes is determined in step S270, the process proceeds to step S280. In step S280, the signal processing unit 144 aligns the m-frame of the repeated B scan at a certain y position. Specifically, first, the signal processing unit 144 selects any one of the m frames as a template. For the frames selected as the template, the correlation may be calculated for all combinations of each other, the sum of the correlation coefficients may be obtained for each frame, and the frame having the maximum sum may be selected. Next, the signal processing unit 144 collates each frame with the template and obtains the amount of misalignment (δX, δY, δθ). Specifically, the signal processing unit 144 calculates Normalized Cross-Correlation (NCC), which is an index showing the degree of similarity while changing the position and angle of the template image, and determines the difference in the image position when this value becomes maximum. Obtained as the amount of misalignment.

In the present invention, the index indicating the degree of similarity can be variously changed as long as it is a scale indicating the similarity between the features of the template and the image in the frame. For example, Sum of Absolute Difference (SAD), Sum of Squared Difference (SSD), Zero-means Normalized Cross-Correlation (ZNCC) may be used. Further, Phase Only Correlation (POC), Rotation Invariant Phase Only Correlation (RIPOC) and the like may be used.

Next, the signal processing unit 144 applies the position correction to the m-1 frame other than the template according to the amount of misalignment (δX, δY, δθ), and aligns the m frame.

In step S290, the signal processing unit 144 averages the aligned luminance images calculated in step S280 to generate a luminance averaging image.

In step S300, the map generation unit 148 is a step of segmenting the retina (acquisition of site information) from the luminance averaging image generated in step S290 by the signal processing unit 144, but this step is used in the first embodiment. This process is skipped because it does not. The description will be given in the second embodiment.

In step S310, the image generation unit 147 calculates the motion contrast. In this embodiment, the dispersion value of the signal intensity (luminance) is calculated for each pixel at the same position from the luminance image of the tomographic image of the m frame output by the signal processing unit 144 in step S300, and the dispersion value is used as the motion contrast. .. That is, the image generation unit 147 calculates the motion contrast using the corresponding pixel data between the calculated tomographic image data. In addition to the variance value, any of the standard deviation, the difference value, the non-correlation value, and the correlation value may be used. Further, the phase may be used instead of the signal strength.

There are various methods for obtaining the motion contrast, and in the present invention, the type of the feature amount of the motion contrast can be applied as long as it is an index showing the change in the luminance value of each pixel of the plurality of B scan images at the same Y position. .. Further, for the motion contrast, it is also possible to use a coefficient of variation normalized by the average value for each pixel of each frame instead of the variance value for each pixel at the same position from the luminance image of the tomographic image of m frame. In this case, the motion contrast becomes independent of the pixel value indicating the structure of the retina, and it becomes possible to obtain a more sensitive motion contrast. However, on the other hand, in the motion contrast, the noise component at a low pixel value is relatively emphasized due to various factors such as alignment error and camera noise. Therefore, for example, in a layer containing few capillaries, it becomes difficult to separate the noise and the blood flow region. Therefore, the image processing method of the present invention works even more effectively.

In step S320, the signal processing unit 144 performs the first threshold value processing of the motion contrast output by the signal processing unit 144. For the value of the first threshold, the area where only random noise is displayed on the noise floor is extracted from the brightness averaging image output by the signal processing unit 144 in step S311, the standard deviation σ is calculated, and the average brightness of the noise floor is calculated. Set as + 2σ. The signal processing unit 144 sets the value of the motion contrast corresponding to the region where each luminance is equal to or less than the threshold value to 0.

By the first threshold processing of S320, noise can be reduced by removing the motion contrast caused by the change in luminance due to random noise.

The smaller the value of the first threshold value, the higher the detection sensitivity of the motion contrast, but also the noise component. Also, the larger the value, the less noise, but the lower the sensitivity of motion contrast detection.

In the present embodiment, the threshold value is set as the average brightness of the noise floor + 2σ, but the threshold value is not limited to this.

In step S330, the signal processing unit 144 increments the index i of the position yi.

In step S340, the signal processing unit 144 determines whether i is larger than n. That is, it is determined whether or not the alignment is performed at all the y positions of n locations, the luminance image averaging calculation, the motion contrast calculation, and the threshold processing are performed. In the case of no, the process returns to S220. In the case of yes, the process proceeds to the next step S350.

At the end of S340, the brightness average image of each pixel of the B scan image (Z depth vs. X direction data) at all Y positions and the three-dimensional data of the motion contrast are acquired. The B scan images at the plurality of Y positions correspond to the three-dimensional tomographic image data.

In step S350, the signal processing unit 144 performs display information generation processing using the three-dimensional data of motion contrast. FIG. 6 shows the details of step S350.

In step S351, the signal processing unit 144 acquires the three-dimensional data of the motion contrast previously determined.

In step S352, the signal processing unit 144 performs smoothing processing on the motion contrast three-dimensional data in order to remove noise while retaining the blood flow site information.
The optimum smoothing process differs depending on the nature of the motion contrast, but the following can be considered, for example.

A smoothing method that outputs the maximum value of motion contrast from nx × ny × nz voxels in the vicinity of the pixel of interest. Alternatively, a smoothing method that outputs the average value of the motion contrasts of nx × ny × nz voxels in the vicinity of the pixel of interest. Alternatively, a smoothing method that outputs the median value of the motion contrast of nx × ny × nz voxels in the vicinity of the pixel of interest. Alternatively, a smoothing method in which the motion contrast of nx × ny × nz voxels in the vicinity of the pixel of interest is weighted by a distance. Alternatively, a smoothing method in which the motion contrast of nx × ny × nz voxels in the vicinity of the pixel of interest is weighted according to the difference between the weight due to the distance and the pixel value of the pixel of interest. Alternatively, a smoothing method that outputs a value using weights according to the similarity between the motion contrast pattern of a small area around a pixel of interest and the motion contrast pattern of a small area around a peripheral pixel.

In addition, a method of smoothing while leaving other blood flow site information may be used.

In step S353, the signal processing unit 144 obtains from the display control unit 149 the threshold value for determining the pixel to be displayed in step S353 and the initial value in the range in the depth direction to be displayed. The initial value of the display range is usually about 1/4 in the depth direction, and the position includes the range of the surface layer of the retina. Here, the reason why the initial value of the display range is not the entire range in the depth direction is that the main blood vessels and the capillary network in the surface layer portion are first displayed in an easy-to-see manner. That is, if the surface layer portion including the main blood vessels and the capillary network and the RPE layer having no blood vessels and having a large noise are displayed at the same time, the discrimination of the main blood vessels and the capillary network in the surface layer portion is hindered. The method for determining the initial value of the display threshold value will be described later.

Next, in step 354, a display threshold value process for displaying pixels exceeding the smoothed three-dimensional data using the initial value of the display threshold value is performed. FIG. 7 shows an example of conversion from the motion contrast pixel value to the display pixel value by this processing. FIG. 7 (a) shows an example in which a pixel value below the display threshold is set to zero, and a display pixel value proportional to the pixels from the pixel value on the threshold to the maximum intensity is assigned. In FIG. 7 (b), the pixel value below the display threshold is assigned. Is multiplied by 0, and the pixel values beyond that are multiplied by 1, which is an example of allocating the display value. In any case, if the motion contrast is equal to or less than the display threshold value, the motion contrast is invalidated, and the area having the motion contrast to be displayed is displayed in a separated form. That is, the value of the motion contrast is controlled according to the comparison result between the motion contrast and the threshold value. The process in step S354 corresponds to an example of a step of comparing the motion contrast and the threshold value and a step of invalidating the motion contrast below the threshold value based on the result of the comparison.

In step S355, the display control unit 149 displays the motion contrast image processed by the display threshold value shown in FIG. 7 on the display unit 146. That is, the process in step S355 corresponds to an example of a step of generating a motion contrast image based on the motion contrast after the step of invalidating the process is performed. For example, the display process step 355 is designed to display the GUI and the 3D motion contrast image shown in FIG. 8B, and displays them on the display unit 146. Reference numeral 400 is a parallelogram area prepared in the display unit 146, and is a display area frame for projecting and displaying the calculated three-dimensional motion contrast image. A slider 407 for adjusting the range in the depth direction for displaying the three-dimensional motion contrast image to be displayed is displayed on the side thereof. The examiner can specify a range in the depth direction of the three-dimensional motion contrast image to be displayed on the display unit 149 by, for example, dragging the operation unit ends 401 and 402 of the slider 407 with a mouse. Further, by dragging, for example, the central portion of the operation portion of the slider 407, the displayed depth position can be changed without changing the width of the displayed depth range. In FIG. 8A, a tomographic image of a three-dimensional motion contrast image is also shown for the purpose of explaining the corresponding depth. The emission lines 403 and 404 on the tomographic image are the positions on the tomographic image corresponding to the slider ends 401 and 402. In the display step, only the motion contrast image of the area 405 sandwiched between the two emission lines is displayed on the display area frame 401. For example, the display control unit 149 may display all the images shown in FIGS. 8A and 8B on the display unit 149, or display only the images shown in FIG. 8B. good.

Further, below the display area frame 400, another slider 406 is provided for adjusting a threshold value for determining a pixel to be displayed. When the examiner drags this slider with a mouse, for example, the display threshold value is changed in step S356 of FIG. 6, and the process is returned to step S354 to update the three-dimensional motion contrast image to be displayed. The process of step S356 corresponds to an example of a step of changing the threshold value. Further, the repeated execution of steps S354 and 355 corresponds to the repeated execution of the step of generating the motion contrast image and the step of displaying the motion contrast image in response to the change of the threshold value.

At this time, if the threshold value adjustment is set so that it can be changed by a relative value with respect to the initial value, an equivalent effect can be obtained for different data of different subjects such as different eyes and sites. With the above configuration, the examiner can arbitrarily change the display depth range, and can set the optimum display threshold value for the selected depth range. Similarly, when the examiner drags the slider operation unit ends 401 and 402 with the mouse to change the display range in the depth direction, step S357 changes the display range. Then, the process is returned to step S354 to update the three-dimensional motion contrast image to be displayed. That is, the motion contrast image displayed is updated according to the change in the display range. Here, the process of step S357 corresponds to an example of a step of setting a display range in the depth direction of a motion contrast image. Further, the execution of step S355 after the execution of step S357 corresponds to an example of a step of displaying a motion contrast image based on a set display range.

In the above explanation, the tomographic image shown in FIG. 8A is used only for explanation, but if this tomographic image is displayed at the same time in the display step, it is easy for the examiner to set the depth range to be displayed. It becomes possible to do it, and it is more suitable. Further, it is desirable that the tomographic image is provided on the side of the display area frame 400 in order to clearly indicate the depth direction. Further, it is desirable to superimpose the position corresponding to the tomographic image to be displayed on the three-dimensional motion contrast image. For example, the table display control unit 149 may display a line corresponding to the tomographic image superimposed on the three-dimensional motion contrast image.

FIG. 9 is a diagram showing an example of a two-dimensional motion contrast image generated by projecting or integrating each pixel value of the three-dimensional motion contrast image in the selected depth range in the depth direction.

In the above embodiment, the three-dimensional motion contrast image is displayed as shown in FIG. 8B, but the present invention is not limited to this, and the two-dimensional motion contrast image may be displayed. For example, a two-dimensional motion contrast image may be displayed instead of the three-dimensional motion contrast image, or both may be displayed at the same time.

In order to generate a two-dimensional motion contrast image, it is possible not only to integrate the motion contrast values of the corresponding pixels, but also to extract and project representative values such as the maximum value, the minimum value, and the median value. Here, FIG. 9 shows an example of a two-dimensional motion contrast image when integrated. Of course, the display threshold can be changed in the same manner by the examiner operating the slider 406 shown in FIG. 9 (b) shows the case where the threshold value is empirically considered to be optimal, (a) is the case where the threshold value is lower than (b), and (c) is the case where the threshold value is higher than (b). Equivalent to. In (a), noise appears and it can be said that it is not suitable for grasping the structure of the blood flow site, but (b) is suitable for grasping the structure of the fine blood flow site, and when it is compared with a conventional fluorescent fundus photograph. An image like (c) would be preferred.

Here, a method of automatically determining the threshold value will be described with reference to FIG. FIG. 10A is a histogram of the motion contrast in a certain depth range selected, and the noise peak N1 is on the low-luminance side and the signal in the blood flow region is on the high-luminance side. A peak is observed. In the display threshold step, Th1 corresponding to the intersection of these two peaks is programmed to be the initial value of the display threshold. Of course, it is also possible to give a certain ratio or a certain amount of shift empirically. FIGS. 10 (b) and 10 (c) show changes in the histogram when the range in the depth direction displayed by the examiner is changed. When the range with low blood flow is selected, it is (b), and when the range with high blood flow is selected, the noise N2, N3, and the signal peaks S2 and S3 in the blood flow region move, respectively, as in (c). Then, the initial values Th2 and Th3 of the display threshold value suitable for it are set. That is, the display threshold value is automatically changed in conjunction with the display range of the motion contrast image. As described above, according to the present embodiment, the motion region and the non-motion region can be estimated from the histogram of the motion contrast of the predetermined region, and the threshold value can be determined from the histogram of the motion region and the histogram of the non-motion region.

The method of determining a uniform threshold value for the target area using the motion contrast histogram in the display range in the depth direction, which is the target area, has been described above, but the present invention is not limited to this. For example, it is also possible to use a local determination method such as determining a predetermined region of the same display region based on the average value and the variance of the motion contrast without uniformly setting the threshold value for the same region.

Of course, when the examiner operates the slider 406 as described above, it is possible to memorize the value and use it as the threshold value for the subsequent display, and it is also possible to provide a switch to return to the initial setting separately. be.

According to the above embodiment, by making the appropriate display threshold value variable or plural for the motion contrast data constituting the OCT angiography, noise in the motion contrast calculation is removed, and blood flow site information that is easier to see can be quickly obtained. It will be possible to provide.

Further, in the motion contrast calculation generated by further including a step of normalizing the motion contrast by using the average value of the corresponding pixel data of the plurality of tomographic image data used in the calculation in the step of calculating the motion contrast. It is possible to effectively remove noise.

Further, when displaying the calculated motion contrast image, by setting the display range in the depth direction, the display range can be easily changed and an appropriate display threshold value can be set.

Further, by limiting the display setting range to a predetermined width in the tomographic image depth direction, unnecessary overlapping portions of the motion contrast image can be removed, so that an easy-to-understand image can be taught. That is, in the present embodiment, the settable display range can be limited to a predetermined width in the depth direction.

In this case, by further providing a step of detecting the layer structure of the tomographic image of the eye to be inspected from the three-dimensional tomographic image data, it becomes possible to select and limit the display range in the depth direction according to the structure of the retina of the inspected eye. Display processing according to the anatomical structure of the optometry becomes possible, which is more effective.

Further, if a two-dimensional motion contrast image is generated by projecting and integrating the three-dimensional motion contrast according to the selection of the display range, it is possible to provide a motion contrast image that is easier to understand more intuitively.

In addition, if the display means selects or generates a tomographic image of the position corresponding to the position specified in the motion contrast image from the three-dimensional motion contrast and displays it, it is more intuitive to identify which layer the information is currently displayed. Can be done. That is, in the present embodiment, in the step of displaying the motion contrast image, the tomographic image of the position corresponding to the position designated on the motion contrast image is selected or generated from the three-dimensional motion contrast and displayed.

Further, the threshold value in the predetermined region can be adaptively determined based on the motion contrast value of the peripheral pixels of each pixel of the motion contrast image to which the threshold value is applied. For example, the motion region and the non-motion region can be estimated from the motion contrast histogram of the predetermined region, and the threshold value can be adaptively determined from the histogram of each region. Alternatively, the threshold can be determined locally based on the mean value and variance of the motion contrast in a predetermined area. Therefore, it is possible to provide a motion contrast image that is easier to see and understand.

[Second Embodiment]
In the first embodiment described above, the examiner directly selects the display range in the depth direction, but the fundus of the eye to be imaged has a layered structure as shown in FIG. Are known. Further, considering that the blood vessel density differs for each retinal layer in the depth direction, it is preferable to make the threshold value for detecting the blood flow site variable for each layer. FIG. 5 step S300, which was not used in the first embodiment, is a step of segmenting this layer structure, and in this embodiment, six layers can be detected. That is, the process in step S300 corresponds to an example of a step of detecting a layer from tomographic image data. The number of layers to be detected is not limited to six. Here, the breakdown of the 6 layers is (1) a layer combining (1) a nerve fiber layer (NFL), (2) a ganglion cell layer (GCL) + an inner plexiform layer (IPL), and (3) an inner nuclear layer (INL). + Outer plexiform layer (OPL) combined layer, (4) Outer nuclear layer (ONL) + External limiting membrane (ELM) combined layer, (5) Ellipside Zone (EZ) + Interdiction Zone (IZ) + Retinal pigment A layer combined with epithelium (RPE), (6) Choroid.

Since the specific process of generating the three-dimensional blood flow site information in step S102 in this embodiment is almost the same as that of the first embodiment shown in FIG. 5, detailed description thereof will be omitted. Here, the segmentation of the retina in the characteristic step S300 will be described below.

The map generation unit 148 creates an image by applying a median filter and a Sobel filter to the tomographic image to be processed extracted from the luminance averaging image (hereinafter, also referred to as a median image and a Sobel image, respectively). .. Next, a profile is created for each A scan from the created median image and Sobel image. The median image has a luminance value profile, and the Sobel image has a gradient profile. Then, the peak in the profile created from the Sobel image is detected. By referring to the profile of the median image corresponding to before and after the detected peak and between the peaks, the boundary of each region of the retinal layer is extracted. The segmentation result obtained by step S300 is held once here, and after processing is performed in the same manner as in the first embodiment below, the display information generation step of step 350 is performed.

The display information generation step of step 350 in the second embodiment will be described with reference to FIG. The second embodiment is characterized in that the setting of the display range in the depth direction of the motion contrast image is performed by selecting the layer based on the result of the segmentation of the retina in step S300. That is, it is possible to select the display range based on the detected layer.

FIG. 12 shows the details of step S350. However, the basics are the same as those in the first embodiment. That is, in step S351, three-dimensional motion contrast data is acquired, and in step S352, smoothing processing is performed on the three-dimensional motion contrast data in order to remove noise while retaining the blood flow site information.

Next, in step S353, the signal processing unit 144 obtains a display threshold value for determining the pixels to be displayed in step S353 and an initial value of the layer to be displayed. The method for determining the initial value of the display threshold value is the same as that of the first embodiment, but the initial value of the display range is, for example, four layers from the surface layer, that is, the nerve fiber layer (NFL) and the ganglion cell layer (GCL). , Inner plexiform layer (IPL), inner nuclear layer (INL) are set. As an initial value, at least 3 layers may be selected from 4 layers from the surface layer. However, when selecting a plurality of layers as initial values, it is desirable that they are continuous layers. In the case of a layer that cannot be separated due to segmentation of the retinal layer, it is desirable that the layer is described as a synthetic layer. Here, the reason why the initial value of the display range is not the entire retinal layer is that the main blood vessels and the capillary network in the surface layer are to be displayed in an easy-to-see manner. That is, if the surface layer portion including the main blood vessels and the capillary network and the RPE layer having no blood vessels and having a large noise are displayed at the same time, the discrimination of the main blood vessels and the capillary network in the surface layer portion is hindered.

Next, in step S354, display threshold processing for displaying pixels exceeding this is performed on the three-dimensional data smoothed using the same initial value. After that, in step S355, a step of displaying the motion contrast image processed by the display threshold value as shown in FIG. 13 is performed. For example, as shown in FIG. 13, the two-dimensional motion contrast image 71, the tomographic image 72 at the position of the markers AA'shown on the two-dimensional motion contrast image 71, and the other GUI 73 are displayed by the display control unit 149. It is displayed in the unit 146.

Further GUI 73 is provided on the side of the tomographic image 72. From the right, the configuration is provided with the name of the retinal layer used for displaying a 2D motion contrast image, a check box for selecting it, and a slider for adjusting the threshold value for determining each display pixel for the selected layer. ing. When the examiner drags this slider with the mouse, the display threshold value is changed in step S356 of FIG. 12, and the process is returned to step S354 to update the two-dimensional motion contrast image to be displayed. That is, as shown in GUI73, in the present embodiment, the threshold value is set for each detected layer.

Further, when the examiner changes the check of the check box to change the layer selection (corresponding to the change of the display range in the depth direction of the first embodiment), in step S357, the display range of the motion contrast image is changed. Is changed, and the process is returned to step S354 to update the two-dimensional motion contrast image to be displayed.

At this time, the number of layer selections is limited to, for example, 5 layers, and when the upper retinal layer is selected (for example, nerve fiber layer (NFL), ganglion cell layer (GCL), inner plexiform layer (IPL)). , Inner nuclear layer (INL), Outer plexiform layer (OPL), Outer plexiform layer (ONL), External limiting membrane (ELM)) At least Ellipside Zone (EZ), Interdictionation Zone (IZ), RPE layer and choroid Make one unselectable. Alternatively, when the lower retinal layer is selected (eg, inner plexiform layer (INL), outer plexiform layer (OPL), outer plexiform layer (ONL), external limiting membrane (ELM), Ellipside Zone (EZ), Interdiction Zone (IZ)). , Retinal pigment epithelium (RPE) layer, or choroidal membrane) at least nerve fiber layer (NFL), ganglion cell layer (GCL), inner plexiform layer (IPL), inner granule layer (INL), outer plexiform layer (OPL) It is also effective in maintaining the diagnostic value of the motion contrast image, which also displays the control of making one of the outer plexiform layer (ONL) and the outer limiting membrane (ELM) unselectable. As described above, in the present embodiment, in the setting of the display range, any layer can be selected based on the detected layer, and the number of selectable layers can be limited.

It is desirable that the tomographic image be further displayed with the boundaries of each layer superimposed as a result of segmentation, and marked so that the selected layer can be easily recognized. The Layer / Border radio button 74 at the bottom of the other GUI 73 is a radio button for selecting a method for generating a two-dimensional motion contrast image. When Layer is selected, a 2D motion contrast image is generated based on the information of each pixel value of the selected 3D motion contrast image over the entire layer. However, when Border is selected, the checkboxes that can be selected are controlled so that two adjacent layers are restricted, and each of the three-dimensional motion contrast images of a predetermined depth that sandwiches the boundary between the two selected layers. A two-dimensional motion contrast image is generated based on the pixel value information.

The first embodiment and the second embodiment may be combined. For example, the slider 406 shown in FIG. 8B may be displayed on the screen in FIG.

According to this embodiment, it is possible to easily set the display range of the motion contrast image by using the segmentation result.

[Third Embodiment]
In the second embodiment, an example using the segmentation result calculated based on the luminance information as the site structure information for clarifying the three-dimensional blood flow site information has been described. On the other hand, in this embodiment, an example of acquiring site structure information using polarization information of an optical interference fault as site structure information will be described.

FIG. 14 is a diagram showing a configuration example of an image forming method and an apparatus using the optical coherence tomography method in the present embodiment. The image forming method and apparatus are composed of an optical interference tomographic acquisition unit 800 for acquiring an optical interference tomographic signal and a control unit 143. The control unit 143 is further composed of a signal processing unit 144, a signal acquisition control unit 145, a display control unit 149, and a display unit 146. The signal processing unit 144 is further composed of an image generation unit and a map generation unit.

First, the configuration of the optical interference fault acquisition unit 800 will be described. In this embodiment, a polarized OCT apparatus using SS (Swept Source) -OCT will be described. It is also possible to apply the present invention to a polarized OCT device using SD-OCT.

<Configuration of polarized OCT device 800>
The configuration of the polarization OCT device 800 will be described.

The light source 801 is a wavelength sweep type (Swept Source: SS) light source, and emits light while sweeping at a sweep center wavelength of 1050 nm and a sweep width of 100 nm, for example.

The light emitted from the light source 801 is a single mode fiber (hereinafter referred to as SM fiber) 802, a polarization controller 803 connector 804, an SM fiber 805, a polarizer 806, and a splitting (PM) fiber (hereinafter referred to as PM fiber). Description) It is guided to a beam splitter 810 via a 807, a connector 808, and a PM fiber 809, and is split into a measurement light (also referred to as an OCT measurement light) and a reference light (also referred to as a reference light corresponding to the OCT measurement light). The branching ratio of the beam splitter 810 is 90 (reference light): 10 (measurement light). The polarization controller 103 can change the polarization of the light emitted from the light source 101 to a desired polarization state. On the other hand, the polarizer 806 is an optical element having a characteristic of passing only a specific linearly polarized light component. Normally, the light emitted from the light source 801 has a high degree of polarization and is dominated by light having a specific polarization direction, but includes light having no specific polarization direction called a random polarization component. It is known that this random polarization component deteriorates the image quality of the polarized OCT image, and the random polarization component is cut by the polarizer. Since only light in a specific linearly polarized state can pass through the polarizer 806, the polarization state is adjusted by the polarization controller 803 so that a desired amount of light is incident on the eye to be inspected 118.

The branched measurement light is emitted via the PM fiber 811 and is converted into parallel light by the collimator 812. The measured light, which has become parallel light, passes through the 1/4 wave plate 813 and then enters the inspected eye 818 via the galvano scanner 814, the scan lens 815, and the focus lens 816 that scan the measured light in the fundus Er of the inspected eye 818. do. Here, the galvano scanner 814 is described as a single mirror, but in reality, it is composed of two galvano scanners so as to raster scan the fundus Er of the eye to be inspected 118. Further, the focus lens 816 is fixed on the stage 817, and the focus can be adjusted by moving in the optical axis direction. The galvano scanner 814 and the stage 817 are controlled by the signal acquisition control unit 145, and the measurement light is measured in a desired range (also referred to as a tomographic image acquisition range, a tomographic image acquisition position, and a measurement light irradiation position) of the fundus Er of the eye to be inspected 118. Can be scanned. Further, the 1/4 wave plate 813 is an optical element having a characteristic of delaying the phase between the optical axis of the 1/4 wave plate and the axis orthogonal to the optical axis by 1/4 wavelength. In this embodiment, the optical axis of the 1/4 wave plate is rotated by 45 ° with respect to the direction of linear polarization of the measurement light emitted from the PM fiber 811, and the light incident on the eye to be inspected 118 is circled. It is polarized. Although not described in detail in this embodiment, it is desirable that a tracking function for detecting the movement of the fundus Er and scanning the mirror of the galvano scanner 114 to follow the movement of the fundus Er is provided. The tracking method can be performed by using a general technique, and can be performed in real time or by post-processing. For example, there is a method using a scanning laser ophthalmoscope (SLO). This involves acquiring a two-dimensional image of the fundus Er in a plane perpendicular to the optical axis over time using SLO, and extracting feature points such as blood vessel branches in the image. Real-time tracking can be performed by calculating how the feature points in the acquired two-dimensional image move as the movement amount of the fundus Er, and feeding back the calculated movement amount to the galvano scanner 814.

The measurement light is incident on the eye to be inspected 118 by the focus lens 816 mounted on the stage 817 and is focused on the fundus Er. The measurement light irradiating the fundus Er is reflected and scattered in each retinal layer, and returns to the beam splitter 810 in the above-mentioned optical path. The return light of the measurement light incident on the beam splitter 810 passes through the PM fiber 826 and is incident on the beam splitter 828.

On the other hand, the reference light branched by the beam splitter 806 is emitted via the PM fiber 819 and is converted into parallel light by the collimator 820. The reference light enters the PM fiber 827 via the 1/2 wave plate 821, the dispersion compensating glass 822, the ND filter 823, and the collimator 824. One end of the collimator lens 824 and the PM fiber 827 is fixed on the coherence gate stage 825, and the signal acquisition control unit 145 is driven in the optical axis direction in response to the difference in the axial length of the subject. Is controlled by. The 1/2 wavelength plate 821 is an optical element having a characteristic of delaying the phase between the optical axis of the 1/2 wavelength plate and the axis orthogonal to the optical axis by 1/2 wavelength. In this embodiment, the linear polarization of the reference light emitted from the PM fiber 819 is adjusted so as to be in a polarized state in which the major axis is tilted by 45 ° in the PM fiber 827. Although the optical path length of the reference light is changed in this embodiment, it is sufficient that the optical path length difference between the optical path of the measurement light and the optical path of the reference light can be changed.

The reference light that has passed through the PM fiber 827 is incident on the beam splitter 828. In the beam splitter 828, the return light of the reference light and the reference light are combined to form interference light, and then split into two. The divided interference light is interference light having phases that are inverted from each other (hereinafter, referred to as a positive component and a negative component). The positive component of the split interference light enters the polarizing beam splitter 835 via the PM fiber 829, the connector 831 and the PM fiber 833. On the other hand, the negative polarization component of the interference light is incident on the polarization beam splitter 836 via the PM fiber 830, the connector 832, and the PM fiber 834.

In the polarizing beam splitters 835 and 836, the interference light is divided according to the two orthogonal polarization axes, and the vertical polarization component (hereinafter, V polarization component) and the horizontal (Horizontal) polarization component (hereinafter, H polarization component) are divided. It is divided into two lights. The positive interference light incident on the polarization beam splitter 835 is split into two interference lights, a positive V polarization component and a positive H polarization component, in the polarization beam splitter 835. The divided positive V-polarized component is incident on the detector 841 via the PM fiber 837, and the positive H-polarized component is incident on the detector 842 via the PM fiber 838. On the other hand, the negative interference light incident on the polarization beam splitter 836 is split into a negative V polarization component and a negative H polarization component in the polarization beam splitter 836. The negative V-polarized component is incident on the detector 841 via the PM fiber 839, and the negative H-polarized component is incident on the detector 142 via the PM fiber 840.
Both the detectors 841 and 842 are differential detectors, and when two interference signals whose phases are inverted by 180 ° are input, the DC component is removed and only the interference component is output.

The V-polarized component of the interference signal detected by the detector 841 and the H-polarized component of the interference signal detected by the detector 842 are output as electric signals according to the light intensity, respectively, and the signal processing unit is an example of the tomographic image generation unit. Enter in 144.

<Control unit 143>
A control unit 143 for controlling the entire apparatus will be described.

The control unit 143 is composed of a signal processing unit 144, a signal acquisition control unit 145, a display unit 146, and a display control unit 149. Further, the signal processing unit 144 is further configured to have an image generation unit 147 and a map generation unit 148. The image generation unit 147 has a function of generating a brightness image and a polarization characteristic image from an electric signal sent to the signal processing unit 144, and the map generation unit 148 has a function of detecting nerve fiber bundles and retinal pigment epithelium.

The signal acquisition control unit 145 controls each unit as described above. The signal processing unit 144 generates an image, analyzes the generated image, and generates visualization information of the analysis result based on the signals output from the detectors 841 and 842.

Since the display unit 146 and the display control unit 149 are substantially the same as those shown in the first embodiment, detailed description thereof will be omitted.

[Image processing]
Next, the image generation in the signal processing unit 144 will be described. The signal processing unit 144 performs general reconstruction processing on the interference signal output from the detectors 841 and 842 in the image generation unit 147. By this processing, the signal processing unit 144 generates a tomographic image corresponding to the H polarization component and a tomographic image corresponding to the V polarization component, which are two tomographic images based on each polarization component.

First, the image generation unit 147 removes fixed pattern noise from the interference signal. Fixed pattern noise removal is performed by extracting fixed pattern noise by averaging a plurality of detected A scan signals and subtracting this from the input interference signal. Next, the image generation unit 147 performs a desired window function processing in order to optimize the depth resolution and the dynamic range, which are in a trade-off relationship when the Fourier transform is performed in a finite interval. After that, a tomographic signal is generated by performing FFT processing.

By performing the above processing on the interference signals of the two polarization components, two tomographic images are generated. Luminance images and polarization characteristic images are generated based on these tomographic signals and tomographic images. The polarization characteristic image is an image of the polarization characteristics of the eye to be inspected, and includes, for example, an image based on retardation information, an image based on orientation information, and an image based on birefringence information.

<Generation of luminance image>
The image generation unit 147 generates a luminance image from the above-mentioned two tomographic signals. The brightness image is basically the same as the tomographic image in the conventional OCT (similar to step S250 of the first embodiment), and its pixel value r is the tomographic signals A _H and V of the H polarization component obtained from the detectors 141 and 142. It is calculated by Equation 1 from the tomographic signal _AV of the polarization component.

Further, by raster scanning with the galvano scanner 814, the B scan images of the fundus Er of the eye to be inspected 818 are arranged in the sub-scanning direction, and three-dimensional data of the luminance image is generated.

Further, when the process described in the first embodiment is applied, the fundus Er is photographed with the scan pattern for OCT angiography, and the OCT angiography is acquired from the luminance image calculated above.

Since the retinal pigment epithelium (RPE) has a property of eliminating polarization, the signal processing unit 144 detects RPE based on that property.

[RPE segmentation]
<DOPU image generation>
The image generation unit 147 calculates the Stokes vector S for each pixel from the acquired tomographic signals A _{H and} AV and the phase difference _ΔΦ between them by Equation 2.

<DOPU image generation>
The image generation unit 147 calculates the Stokes vector S for each pixel from the acquired tomographic signals A _{H and} AV and the phase difference _ΔΦ between them by Equation 2.

However, ΔΦ is calculated as ΔΦ = Φ _V −Φ _H from the phases Φ _H and Φ _V of each signal obtained when calculating two tomographic images.

Next, the image generation unit 147 set a window having a size of about 70 μm in the main scanning direction of the measurement light and about 18 μm in the depth direction for each B-scan image, and calculated for each pixel by Equation 2 in each window. Each element of the Stokes vector is averaged, and the uniformity of polarization DOPU (Image Of Preparation Uniformity) in the window is calculated by Equation 3.

However, Q _m , U _m , and V _m are values obtained by averaging the elements Q, U, and V of the Stokes vector in each window. By performing this process on all windows in the B-scan image, a DOPU image (also referred to as a tomographic image showing the uniformity of polarization) is generated.

DOPU is a numerical value indicating the uniformity of polarization, and is a numerical value close to 1 in a place where polarization is maintained, and a numerical value smaller than 1 in a place where polarization is not maintained. In the structure in the retina, since RPE has a property of eliminating the polarized state, the value of the portion corresponding to RPE in the DOPU image becomes smaller than that of other regions. Since the DOPU image images a layer that eliminates polarization such as RPE, even when the RPE is deformed due to a disease or the like, the RPE can be imaged more reliably than the change in brightness.

The segmentation information of RPE is acquired from this DOPU image.

By this processing, it is determined whether or not each position is RPE from the captured interference signal (three-dimensional data).

[Processing operation]
Next, a specific processing procedure of the image forming method of the present embodiment will be described. Since the basic processing flow in the present embodiment is the same as the processing flow in the first embodiment, the outline description will be omitted. However, since the detailed processing of step S250, step S300, and step S320 is different, the corresponding steps S250A, step S300A, and step S320A of the present embodiment will be described in detail below.

In step _S250A , the signal processing unit 144 generates a tomographic image A _H and a tomographic image AV to generate a luminance image. In addition, a DOPU image is generated.

In step S300A, the map generation unit 148 performs RPE segmentation using the luminance image and the DOPU image.

In step S320A, the signal processing unit 144 corrects the OCT angiography information (here, motion contrast) using the site information (retinal segmentation information) acquired in step S300A. Here, the noise threshold value (first threshold value) of the motion contrast in the RPE is raised by using the DOPU information (information which is the RPE) of the pixel obtained from the retinal segmentation information. For example, the threshold value related to RPE is set higher than the threshold value in the region above RPE. Alternatively, lower the motion contrast so that it is not a blood flow site. By doing so, the threshold value processing performed in step S320A can be performed more accurately. It should be noted that noise at a deep position may be reduced by raising the threshold value in a portion deeper than the RPE as compared with other regions.

By using the polarized OCT device described above, RPE segmentation can be obtained, noise can be reduced more accurately from the 3D data of motion contrast, and clear 3D blood flow site information can be obtained. Can be done. In addition, it is possible to hide the uncertain blood flow site.

The display threshold value in step S354 may be controlled like the noise threshold value described above. For example, noise at a deep position may be reduced by raising the display threshold value in a portion deeper than the RPE as compared with other regions. Further, the display threshold value related to the RPE may be higher than the display threshold value of the region above the RPE.

[Fourth Embodiment]
In the third embodiment, an example of acquiring structural information of RPE using polarization information of an optical interference fault as site structure information has been described, but in this embodiment, an example of acquiring structural information of RNFL will be described.

The image forming method and the configuration example of the apparatus in this embodiment are the same as those in FIG. 14 of the third embodiment, and thus the description thereof will be omitted here.

The layer having birefringence is the retinal nerve fiber layer (RNFL), and the signal processing unit 144 of the present embodiment detects RNFL based on its properties.

<Retention image generation>
The image generation unit 147 generates a retardation image from a tomographic image of polarized components orthogonal to each other.

The value δ of each pixel of the retardation image is a numerical value of the phase difference between the vertical polarization component and the horizontal polarization component at the position of each pixel constituting the tomographic image, and each tomographic signal A _H and _AV Is calculated from Equation 4.

By generating a retardation image, a layer with birefringence such as the retinal nerve fiber layer (RNFL) is grasped.

The signal processing unit 144 detects the retinal nerve fiber layer (RNFL) from the retardation images obtained from the plurality of B scan images.

<Generation map generation>
The signal processing unit 144 generates a retardation map from the retardation images obtained for the plurality of B-scan images.

First, the signal processing unit 144 detects retinal pigment epithelium (RPE) in each B scan image. Since RPE has the property of eliminating polarization, each A scan is examined for the distribution of retardation along the depth direction from the internal limiting membrane (ILM) to the extent that RPE is not included, and the maximum value is used in the A scan. It is a representative value of retardation.

The map generation unit 148 generates a retardation map by performing the above processing on all the retardation images.

[RNFL segmentation]
<Birrefringence map generation>
The image generation unit 147 linearly approximates the value of retardation δ in the range from ILM to the retinal nerve fiber layer (RNFL) in each A-scan image of the previously generated retardation image, and the inclination thereof is the A-scan image. Determined as a compound refraction at a position on the retina. By performing this process on all the retardation images obtained, a map representing birefringence is generated. Then, the map generation unit 148 performs segmentation of the RNFL using the birefringence value.

[Processing operation]
Next, a specific processing procedure of the image forming method of the present embodiment will be described. Since the basic processing flow in the present embodiment is the same as the processing flow in the second embodiment, the outline description will be omitted. However, since the detailed processing of step S250A, step S300A, and step S320A is different, the corresponding step S250B, step S300B, and step S320B of the present embodiment will be described in detail below.

In step _S250B , the signal processing unit 144 generates a tomographic image A _H and a tomographic image AV to generate a luminance image. In addition, it produces a retardation image.

In step S300B, the map generation unit 148 generates a retardation map and performs RNFL segmentation using the luminance image and the retardation image.

In step S320B, the signal processing unit 144 corrects the OCT angiography information (here, motion contrast) using the site information (retinal segmentation information) acquired in step S300B. Here, the noise threshold value (first threshold value) of the RNFL motion contrast is raised by using the pixel retardation information (information which is RNFL) obtained from the retinal segmentation information. Alternatively, lower the motion contrast so that it is not a blood flow site. By doing so, the threshold value processing performed in step S320B can be performed more accurately.

By using the polarized OCT device described above, RNFL segmentation can be obtained, noise can be reduced more accurately from the 3D data of motion contrast, and clear 3D blood flow site information can be obtained. Can be done.

The display threshold value in step S354 may be controlled like the noise threshold value described above.

In the above, a method of segmenting RPE and RNFL using the information of polarized OCT and acquiring clearer three-dimensional blood flow site information has been described, but the present embodiment is not limited to RPE and RNFL, and other It may also be applied to the site.

Furthermore, the polarization characteristics of the blood vessel wall can be used to identify the blood vessel and combine it with the motion contrast information to improve the reliability of the result.

[Other Examples]
Although the examples have been described in detail above, the present invention can be implemented as, for example, a system, an apparatus, a method, a program, a recording medium (storage medium), or the like. Specifically, it may be applied to a system composed of a plurality of devices (for example, a host computer, an interface device, an image pickup device, a web application, etc.), or may be applied to a device consisting of one device. good.

Needless to say, the purpose of the disclosed technology is achieved by doing the following. That is, a recording medium (or storage medium) in which a program code (computer program) of software that realizes the functions of the above-described embodiment is recorded is supplied to the system or device. Needless to say, the storage medium is a computer-readable storage medium. Then, the computer (or CPU or MPU) of the system or device reads and executes the program code stored in the recording medium. In this case, the program code itself read from the recording medium realizes the function of the above-described embodiment, and the recording medium on which the program code is recorded constitutes the present invention.

143 Control unit 144 Signal processing unit 145 Signal acquisition control unit 146 Display unit 147 Image generation unit 148 Map generation unit 149 Display control unit

Claims (18)

A step of calculating a motion contrast value using the corresponding pixel data between a plurality of tomographic image data of the eye to be inspected obtained by scanning substantially the same position of the eye to be inspected multiple times with measurement light.
Based on the comparison result obtained by comparing the motion contrast value and the threshold value, the step of invalidating the motion contrast value below the threshold value and the step of invalidating the motion contrast value.
The step of aligning the plurality of tomographic image data before the motion contrast value is calculated, and
A step of detecting a plurality of layer boundaries by performing a segmentation process using the averaged images of the plurality of tomographic image data, and
After the invalidation is performed, the motion contrast front image of the eye to be inspected is based on at least one of the plurality of layers classified based on the detected plurality of layer boundaries and the motion contrast value. And the process of generating
It is an initial value automatically set according to the distribution of noise and the distribution of the blood flow region in the histogram of the motion contrast value in the at least one layer, and determines at least one of the plurality of layers. The process of changing the threshold value according to the instruction from the examiner from the initial value automatically changed according to the instruction from the examiner.
A step of regenerating the motion contrast front image of the eye to be inspected based on the at least one determined layer and the comparison result obtained by comparing again using the threshold value obtained by the change. When,
An image generation method characterized by having. The image according to claim 1, wherein the calculation step further includes a step of normalizing the motion contrast value using the average value of the corresponding pixel data of the plurality of tomographic image data used in the calculation. Generation method. A step of setting a display range in the depth direction of the motion contrast front image based on at least one of the detected plurality of layer boundaries, and a step of setting the display range in the depth direction.
It further comprises a step of displaying the motion contrast front image generated based on the set display range.
The image generation method according to claim 1 or 2, wherein the motion contrast front image displayed in response to a change in the display range is updated. In the step of setting the display range, the set display range can be changed according to an instruction from the examiner, and the setable display range can be limited to a predetermined width in the depth direction. The image generation method according to claim 3, wherein the image is generated. The step of setting the display range according to claim 3 or 4, wherein any layer can be selected from the plurality of classified layers, and the number of selectable layers can be limited. Image generation method. The image generation method according to any one of claims 3 to 5, wherein the step of regenerating and the step of displaying are repeatedly executed in response to the change of the threshold value. In the step of setting the display range, the upper retinal layer or the lower retinal layer can be selected, and the nerve fiber layer (NFL), the ganglion cell layer (GCL), the outer plexiform layer (IPL), and the inner plexiform layer (INL) can be selected. ), Outer plexiform layer (OPL), Outer plexiform layer (ONL), Outer plexiform membrane (ELM), at least one of the Ellipsoid Zone (EZ), Interdiction Zone (IZ), RPE layer and choroidal membrane. One cannot be selected, and the inner granule layer (INL), outer plexiform layer (OPL), outer plexiform layer (ONL), outer boundary membrane (ELM), Ellipside Zone (EZ), Interdiction Zone (IZ), and retinal pigment epithelium ( When either the RPE) layer or the choroidal membrane is selected, at least the nerve fiber layer (NFL), ganglion cell layer (GCL), inner plexiform layer (IPL), inner granule layer (INL), and outer plexiform layer (OPL). The image generation method according to any one of claims 3 to 6, wherein one of the outer plexiform layer (ONL) and the outer boundary membrane (ELM) cannot be selected. Claims 3 to 7 are characterized in that, in the process of displaying, a tomographic image of a position corresponding to a position designated on the displayed motion contrast front image is selected or generated from three-dimensional motion contrast and displayed. The image generation method according to any one of the above items. The averaged image of the plurality of aligned tomographic image data on which the information indicating the positions of the plurality of layers is superimposed and the information indicating the substantially same position corresponding to the averaged image are superimposed. Further, it has a step of displaying the motion contrast front image and the information for accepting the change of the threshold value side by side on the display means.
The image generation method according to any one of claims 1 to 8, wherein the plurality of layer boundaries are detected by performing a segmentation process using the averaged image. The plurality of tomographic data according to any one of claims 1 to 9 , wherein the plurality of tomographic data can be obtained by scanning the substantially same position a plurality of times with the measurement light while following the movement of the eye to be inspected. Image generation method. The item according to any one of claims 1 to 10, wherein the initial value of the threshold value is determined based on the motion contrast value of the peripheral pixels of the image corresponding to the motion contrast value to be compared with the threshold value. The image generation method described. Any one of claims 1 to 1 that estimates a motion region and a non-motion region from a histogram of motion contrast values in a predetermined region, and determines an initial value of the threshold value from the histogram of the motion region and the histogram of the non-motion region. The image generation method described in the section. The image generation according to any one of claims 1 to 12, wherein the plurality of tomographic image data is obtained by scanning substantially the same position of the fundus of the eye to be examined a plurality of times with measurement light. Method. The image obtained by using the at least one tomographic image data is a polarized OCT image.
The segmentation is performed using the polarized OCT image, and the segmentation is performed.
Any of claims 1 to 13, wherein a map showing the polarization information is generated using the polarization information obtained by using the tomographic image data for calculating the motion contrast value and the tomographic image data common to the tomographic image data. The image generation method according to item 1. The image generation according to any one of claims 1 to 14, wherein the number of times the measurement light scans at substantially the same position is determined according to the motion analysis of the fundus surface image of the eye to be inspected. Method. A program comprising causing a computer to execute the image generation method according to any one of claims 1 to 15 . A calculation means for calculating a motion contrast value using the corresponding pixel data between a plurality of tomographic image data of the eye to be inspected obtained by scanning substantially the same position of the eye to be inspected with measurement light multiple times.
Based on the comparison result obtained by comparing the motion contrast value and the threshold value, an invalidation means for invalidating the motion contrast value below the threshold value and an invalidation means.
An alignment means for aligning the plurality of tomographic image data before the motion contrast value is calculated, and
A detection means for detecting a plurality of layer boundaries by performing a segmentation process using the averaged images of the plurality of tomographic image data.
After the invalidation is performed, the motion contrast front image of the eye to be inspected is based on at least one of the plurality of layers classified based on the detected plurality of layer boundaries and the motion contrast value. And the generation method to generate
It is an initial value automatically set according to the distribution of noise and the distribution of the blood flow region in the histogram of the motion contrast value in the at least one layer, and determines at least one of the plurality of layers. It is provided with a changing means for changing the threshold value according to the instruction from the examiner from the initial value automatically changed according to the instruction from the examiner.
The generation means is a motion contrast frontal image of the eye to be inspected based on the at least one determined layer and the comparison result obtained by recomparing with the threshold value obtained by the modification. An image generator characterized by regenerating the image. The image generator according to claim 17 and
An optical interference tomographic imaging apparatus having a scanning means for scanning the eye to be inspected with the measurement light and a light detection means for detecting the interference light between the return light from the eye to be inspected and the reference light irradiated with the measurement light. ,
A system characterized by being equipped with.

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