JP6870723B2 - OCT motion contrast data analysis device, OCT motion contrast data analysis program. - Google Patents

Description

The present disclosure relates to an apparatus for analyzing motion contrast data acquired by an optical coherence tomography (OCT).

In recent years, a technique for obtaining motion contrast data of a subject by using OCT technique has attracted attention (see Non-Patent Document 1).

Roberto Reif et al. “Quantifying Optical Microangiography I mages Obtained from a Spectral Domain Optical Coherence Tomography System”, International Journal of Biomedical Imaging, Vol.2012, Article ID 509783, p. 11

However, although various improvements have been made to the imaging of motion contrast data, there may be room for improvement in various aspects regarding the analysis relationship.

For example, the analysis using the motion contrast data and the analysis using the OCT data (for example, the layer thickness analysis of the fundus) are independent, which is troublesome. Moreover, it was difficult to compare the results of each analysis. It was also troublesome to analyze multiple motion contrast data.

The technical subject of the present disclosure is to provide an OCT motion contrast data analysis device and an OCT motion contrast data analysis program capable of suitably analyzing motion contrast data in view of at least one of the problems of the prior art. ..

In order to solve the above problems, the present disclosure is characterized by having the following configurations.

(1) An OCT motion contrast data analysis device for analyzing OCT motion contrast data of the eye to be inspected acquired by an optical coherence tomography.
The first analysis region divided into a plurality of sections is set to the OCT data of the fundus of the eye to be inspected, which is image data different from the OCT motion contrast data, and the fundus of the eye to be inspected in the plurality of preset sections is set. An acquisition method for acquiring basic statistics on layer thickness,
It has an analysis processing means for setting a second analysis region divided into a plurality of sections to the OCT motion contrast data of the fundus of the eye to be inspected and performing analysis processing of the motion contrast data.
The arrangement position and range of each section in the second analysis area are the same as the arrangement position and range of each section in the first analysis area. (2) Acquired by an optical interference tomography. It is an OCT motion contrast data analysis program executed in the OCT motion contrast data analysis device for analyzing the OCT motion contrast data of the eye to be inspected , and is executed by the processor of the OCT motion contrast data analysis device.
The first analysis region divided into a plurality of sections is set to the OCT data of the fundus of the eye to be inspected, which is image data different from the OCT motion contrast data, and the fundus of the eye to be inspected in the plurality of preset sections is set. Steps to get basic statistics on layer thickness,
It has a step of setting a second analysis region divided into a plurality of sections to the OCT motion contrast data of the fundus of the eye to be inspected and performing analysis processing of the motion contrast data.
The arrangement position and range of each section in the second analysis region are the same as the arrangement position and range of each section in the first analysis region.

It is a block diagram which shows the outline of this Example. It is a figure which shows an example of the optical system of an OCT device. It is a figure for demonstrating acquisition of motion contrast. It is a figure which shows an example of the display screen. It is a figure which shows an example of the setting screen. It is a figure which shows an example of the display screen.

Hereinafter, the present embodiment will be briefly described. The OCT motion contrast data analysis device of the present embodiment analyzes, for example, the motion contrast data of the subject acquired by the optical interference tomography. The OCT motion contrast data analysis device includes, for example, an analysis processing unit (for example, a control unit 70). The analysis processing unit performs analysis processing on the motion contrast data based on, for example, an analysis chart set on the second image data. Here, the second image data is, for example, image data different from the motion contrast data. As a result, the present analysis device can smoothly analyze the motion contrast.

For example, the analysis processing unit may set an analysis area for the motion contrast data based on the position information of the analysis chart. Then, the analysis processing unit may perform analysis processing on the motion contrast with respect to the set analysis area. Such an analysis process may be applied to, for example, an extraction process of a blood vessel region in the analysis region.

Further, the analysis processing unit may set a reference position for performing analysis processing on the motion contrast data based on the position information of the analysis chart, and perform analysis processing on the motion contrast based on the set reference position. Good. In this case, the analysis area may be set with reference to the set reference position. The analysis processing unit may perform analysis processing on the motion contrast with respect to the set analysis area. Such a process may be applied to, for example, an extraction process of a blood vessel region in an analysis region. Further, the analysis process for the motion contrast data may be executed with the set reference position as a reference. Such a process may be applied, for example, to the setting of a reference position when performing the extraction process of the avascular region.

Further, an analysis area for motion contrast data may be set based on the range of the analysis chart.

The motion contrast data may be, for example, two-dimensional motion contrast data, face-to-face motion contrast data, or three-dimensional motion contrast data.

The analysis chart may be an analysis chart showing the basic statistics of the measurement results in the set section. For example, the basic statistics of the measurement results based on the analysis results for the OCT data which is the basis of the motion contrast data. It may be.

The second image data may at least overlap with the motion contrast data with respect to the acquisition site on the subject. For example, the second image data may be the same as the motion contrast data with respect to the acquisition range on the subject. The second image data may include, for example, the acquisition range of motion contrast data with respect to the acquisition range on the subject.

The analysis processing unit may perform analysis processing based on the changed analysis chart in conjunction with the change of the analysis chart, for example. As a result, it is possible to smoothly change the motion contrast analysis according to the setting change of the analysis chart.

For example, the analysis processing unit may change the position of the analysis area with respect to the motion contrast data in conjunction with the change of the display position of the analysis chart. For example, the analysis processing unit may change the range of the analysis area for the motion contrast data in conjunction with the change of the range of the analysis chart.

Further, for example, the analysis processing unit may change the reference position of the analysis processing for the motion contrast data in conjunction with the change of the display position of the analysis chart.

The analysis processing unit may set the center position or the reference position of the analysis processing for the motion contrast data, for example, based on the center position of the analysis chart.

The analysis processing unit may perform measurement processing of the subject based on the analysis result of the analysis processing, for example.

The analysis processing unit may set the vessel analysis region based on the analysis chart. Then, the analysis processing unit may perform the vascular extraction processing in the set vascular analysis region.

The analysis processing unit may perform measurement on the extracted vasculature. The measurement related to the vessel may be the area / volume of the vessel, the density of the vessel, the amount of the vessel, the total amount of the vessel, the degree of meandering of the vessel, the regularity of the vessel, the symmetry of the vessel, or the like. ..

For example, the analysis processing unit may set the reference position of the pulseless tube extraction process in the motion contrast data based on the position of the analysis chart. Then, the analysis processing unit may perform the pulseless tube extraction process with reference to the set reference position.

The device may further include, for example, a first instruction receiving unit (for example, a control unit 70). The first instruction receiving unit receives, for example, an instruction from the examiner for setting the position of the analysis chart on the second image data. In this case, the analysis processing unit may perform analysis processing on the motion contrast data based on the position information of the analysis chart set by the first instruction receiving unit.

The second image data may be, for example, at least one of a front image of the subject, an analysis map relating to the subject, and the like.

The device may further include, for example, a second instruction receiving unit (for example, a control unit 70). The second instruction receiving unit receives, for example, an instruction from the examiner for setting the position of the analysis region on the motion contrast data or the reference position of the analysis process. In this case, the analysis processing unit may perform analysis processing on the motion contrast data based on, for example, the position information of the analysis region or the position information of the reference position set by the second instruction receiving unit.

The analysis processing unit may be able to set the position of the analysis chart based on the position information of the analysis area or the position information of the reference position set by the second instruction receiving means.

The second image data may be associated with the OCT data that is the basis of the motion contrast data.

When the analysis processing unit extracts the blood vessel region by the threshold value processing as the analysis process, the analysis processing unit may set the region on the motion contrast data set to obtain the threshold value based on the position information of the analysis chart. ..

The device may include a third instruction receiving unit. The third instruction receiving unit receives, for example, an instruction from the examiner for selecting an analysis area in the motion contrast data. In this case, the analysis processing unit may set the analysis area on the second image data based on the analysis area selected by the third instruction receiving unit.

The subject may be the fundus of the eye to be inspected. In this case, for example, the analysis processing unit can set at least one of the position, range, and shape of the analysis area set for performing the analysis processing according to the acquisition area of the motion contrast data on the subject. It may be. Of course, the position, range, shape, etc. of the analysis area may be set in advance, or the range may be changed according to the analysis result for each data.

The acquisition region may be the surface direction of the subject (for example, the macula of the fundus of the eye to be inspected, the papilla, etc.) or the depth direction of the subject (for example, each blood vessel layer of the fundus of the eye to be inspected). You may.

When a plurality of motion contrast data having different acquisition areas are generated, the range of the analysis area may be set for each data. The plurality of motion contrast data may be, for example, a plurality of frontal motion contrast data separated into each blood vessel layer, or a different analysis area may be set for each frontal motion contrast data.

The analysis map may be, for example, a map showing a two-dimensional distribution of measurement results for a subject. In this case, for example, a color map that is color-coded according to the measured value may be used.

In addition, for example, the analysis chart 504 may be an analysis chart for obtaining the basic statistic of the measurement result of the subject in the preset section, or the basic statistic in the section may be measured. ..

<Example>
Hereinafter, the OCT motion contrast data analysis apparatus of this embodiment will be described with reference to the drawings. The OCT motion contrast data analysis device (hereinafter, OCT analysis device) 1 shown in FIG. 1 analyzes the motion contrast data acquired by the OCT device 10.

The OCT analysis device 1 includes, for example, a control unit 70. The control unit 70 is realized by, for example, a general CPU (Central Processing Unit) 71, a flash ROM 72, a RAM 73, or the like. The flash ROM 72 stores, for example, an analysis processing program for processing motion contrast data, a program for controlling the operation of the OCT device 10 to obtain motion contrast data, initial values, and the like. The RAM 73 temporarily stores various types of information, for example.

As shown in FIG. 1, the control unit 70 is electrically connected to, for example, a storage unit (for example, a non-volatile memory) 74, an operation unit 76, a display unit 75, and the like. The storage unit 74 is, for example, a non-transient storage medium capable of retaining the stored contents even when the power supply is cut off. For example, a hard disk drive, a flash ROM, a detachable USB memory, or the like can be used as the storage unit 74.

Various operation instructions by the inspector are input to the operation unit 76. The operation unit 76 outputs a signal corresponding to the input operation instruction to the CPU 71. For the operation unit 76, for example, at least one user interface such as a mouse, a joystick, a keyboard, and a touch panel may be used.

The display unit 75 may be a display mounted on the main body of the device 1 or a display connected to the main body. For example, a display of a personal computer (hereinafter referred to as "PC") may be used. The display unit 75 displays, for example, OCT data, motion contrast data, and the like acquired by the OCT device 10.

The OCT analysis device 1 of this embodiment is connected to, for example, the OCT device 10. The OCT analysis device 1 may have an integrated configuration housed in the same housing as the OCT device 10, or may have a separate configuration. The control unit 70 may acquire motion contrast data from the connected OCT device 10. The control unit 70 may acquire the motion contrast data acquired by the OCT device 10 via the storage medium.

<OCT device>
Hereinafter, the outline of the OCT device 10 will be described with reference to FIG. For example, the OCT device 10 irradiates the eye E to be inspected with the measurement light, and acquires the OCT signal acquired by the reflected light and the measurement light. The OCT device 10 mainly includes, for example, an OCT optical system 100.

<OCT optical system>
The OCT optical system 100 irradiates the eye E to be inspected with the measurement light, and detects an interference signal between the reflected light and the reference light. The OCT optical system 100 mainly includes, for example, a measurement light source 102, a coupler (optical divider) 104, a measurement optical system 106, a reference optical system 110, a detector 120, and the like. For the detailed configuration of the OCT optical system, refer to, for example, Japanese Patent Application Laid-Open No. 2015-131107.

The OCT optical system 100 is an optical system of a so-called optical coherence tomography (OCT). The OCT optical system 100 divides the light emitted from the measurement light source 102 into the measurement light (sample light) and the reference light by the coupler 104. The divided measurement light is guided to the measurement optical system 106, and the reference light is guided to the reference optical system 110. The measurement light is guided to the fundus Ef of the eye E to be inspected via the measurement optical system 106. After that, the detector 120 receives the interference light obtained by combining the measurement light reflected by the eye E to be inspected with the reference light.

The measurement optical system 106 includes, for example, a scanning unit (for example, an optical scanner) 108. The scanning unit 108 may be provided, for example, to scan the measurement light on the fundus in the XY direction (transverse direction). For example, the CPU 71 controls the operation of the scanning unit 108 based on the set scanning position information, and acquires the OCT signal based on the received light signal detected by the detector 120. The reference optical system 110 generates a reference light that is combined with the reflected light acquired by the reflection of the measurement light at the fundus Ef. The reference optical system 110 may be a Michaelson type or a Machzenda type.

The detector 120 detects an interference state between the measurement light and the reference light. In the case of the Fourier domain OCT, the spectral intensity of the interference light is detected by the detector 120, and the depth profile (A scan signal) in a predetermined range is acquired by the Fourier transform on the spectral intensity data.

As the OCT device 10, for example, Spectral-domain OCT (SD-OCT), Swept-source OCT (SS-OCT), Time-domain OCT (TD-OCT) and the like may be used.

<Front photography optical system>
The frontal imaging optical system 200, for example, photographs the fundus Ef of the eye E to be examined from the front direction (for example, the optical axis direction of the measurement light) to obtain a frontal image of the fundus Ef. The frontal photographing optical system 200 may have, for example, a device configuration of a scanning laser ophthalmoscope (SLO) (see, for example, Japanese Patent Application Laid-Open No. 2015-666242), or may have a so-called fundus camera type configuration. (See Japanese Patent Application Laid-Open No. 2011-10944). As the frontal photographing optical system 200, the OCT optical system 100 may also be used, or a frontal image may be acquired based on the detection signal from the detector 120.

<Fixed target projection unit>
The fixation target projection unit 300 has an optical system for guiding the line-of-sight direction of the eye E. The projection unit 300 has a fixation target presented to the eye E and can guide the eye E. For example, the fixation target projection unit 300 has a visible light source that emits visible light, and changes the presentation position of the fixation target two-dimensionally. As a result, the line-of-sight direction is changed, and as a result, the acquisition site of OCT data is changed.

<Acquisition of motion contrast data>
The OCT analysis device 1 of this embodiment may, for example, process the OCT data detected by the OCT device 10 to acquire motion contrast data. The CPU 71 controls the driving of the scanning unit 108 to scan the measurement light in the region A1 on the fundus Ef. In FIG. 3A, the direction of the z-axis is the direction of the optical axis of the measurement light. The direction of the x-axis is perpendicular to the z-axis and is the left-right direction of the subject. The direction of the y-axis is perpendicular to the z-axis and is the vertical direction of the subject.

For example, the CPU 71 scans the measurement light in the x direction along the scanning lines SL1, SL2, ..., SLn in the area A1. Scanning the measurement light in a direction intersecting the optical axis direction of the measurement light (for example, the x direction) is called "B scan". Then, the two-dimensional OCT data obtained by one B scan will be described as one frame of two-dimensional OCT data. The CPU 71 may, for example, scan the measurement light two-dimensionally in the xy direction to obtain an A scan signal in the z direction at each scanning position.

The CPU 71 may acquire motion contrast data based on the OCT data. The motion contrast may be, for example, information that captures the blood flow of the eye to be examined, changes in the retinal tissue, and the like. When acquiring motion contrast data, the CPU 71 acquires at least two OCT data that are temporally different with respect to the same position of the eye to be inspected. For example, in each scanning line, the CPU 71 performs a plurality of B scans at different times and acquires a plurality of OCT data at different times.

For example, FIG. 3B shows an OCT signal acquired when a plurality of B scans having different times are performed on the scanning lines SL1, SL2, ..., SLn. For example, FIG. 3B scans the scanning line SL1 at time T11, T12, ..., T1N, scans scanning line SL2 at time T21, T22, ..., T2N, and scans scanning line SLn for time. The case where scanning is performed with Tn1, Tn2, ..., TnN is shown. For example, the CPU 71 acquires a plurality of OCT data having different times in each scanning line, and stores the OCT data in the storage unit 74.

As described above, when the CPU 71 acquires a plurality of OCT data that are temporally different with respect to the same position, the CPU 71 processes the OCT data to acquire the motion contrast data. Examples of the method of calculating the OCT data for acquiring the motion contrast include a method of calculating the intensity difference of the complex OCT data, a method of calculating the phase difference of the complex OCT data, and a method of calculating the vector difference of the complex OCT data. Examples thereof include a method of multiplying the phase difference and the vector difference of the complex OCT signal, a method of using the correlation of the signals (correlation mapping), and the like. As one of the calculation methods, refer to, for example, Japanese Patent Application Laid-Open No. 2015-131107.

The CPU 71 may acquire the three-dimensional motion contrast data of the eye E to be inspected by arranging the motion contrast data on different scanning lines. As described above, as the motion contrast data, not only the phase difference but also the intensity difference, the vector difference, and the like may be acquired.

<Analysis processing of motion contrast data>
An example of the analysis processing of the motion contrast data acquired as described above will be described below.

The CPU 71 may acquire at least one analysis result by setting an analysis area for the motion contrast data and performing analysis processing on the set analysis area. In this case, the CPU 71 may set the analysis area for the motion contrast data with reference to the position information of the analysis chart on the second image data which is the image data different from the motion contrast data.

Hereinafter, as an example of the analysis result, a case where the blood vessel region of the eye to be inspected is extracted by the analysis processing for the motion contrast data will be described. In this case, a blood vessel analysis region is set as an analysis region for the motion contrast data, and analysis processing for extracting the blood vessel region is performed at least in the blood vessel analysis region.

FIG. 4 is a diagram showing an example of an analysis screen when extracting a blood vessel region. For example, the CPU 71 may display the MC display area 400 and the second image display area 500 on the display screen of the display unit 75 on the analysis screen. In this case, the MC display area 400 and the second image display area 500 may be displayed at the same time, or may be displayed at different timings.

The MC display area 400 is an area for displaying motion contrast data (hereinafter, MC data) 402. For example, as MC data 402, as shown in FIG. 4, front MC data (also referred to as face MC data). May be displayed. The frontal MC data may be obtained, for example, by extracting three-dimensional MC data for at least a part of the region in the depth direction (see, for example, Japanese Patent Application Laid-Open No. 2015-121574). For example, the front MC data may be generated by the integrated value or the maximum value in the depth direction in the MC data. Of course, as the MC data 402, one-dimensional MC data, two-dimensional MC data, and three-dimensional MC data may be displayed.

The CPU 71 may display a display (for example, graphic 404) indicating the blood vessel analysis region on the MC data 402 on the MC data 402. The display showing the blood vessel analysis area may be a frame display showing the outer edge of the blood vessel analysis area as shown in graphic 404 of FIG. 4, or a color-coded display of the blood vessel analysis area and the non-blood vessel analysis area. May be good.

The second image display area 500 is an area for displaying the second image data 502, which is image data different from the MC data 402, and for example, at least one of a front image and an analysis map is displayed. May be good. As the second image data 502, image data that at least partially overlaps with the MC data 402 is used for the acquisition site. For example, if the MC data 402 is data centered on the macula, the second image data on the macula is displayed, and if the MC data 402 is data centered on the nipple, the second image data on the nipple is displayed. May be done.

The analysis map may be, for example, a map showing a two-dimensional distribution of measurement results relating to the fundus. In this case, for example, a color map that is color-coded according to the measured value may be used. The analysis map includes, for example, a thickness map showing the layer thickness, a comparison map showing the comparison result between the layer thickness of the eye to be examined and the layer thickness of the normal eye stored in the normal eye database, and the layer thickness of the eye to be examined and the normal eye database. It may be a deviation map showing the deviation from the layer thickness of the normal eye stored in the standard deviation, or an examination date comparison thickness difference map showing the difference in thickness from each examination date. When determining the layer thickness, for example, the OCT data is divided into layers by image processing (for example, segmentation processing) on the OCT data, and the thickness of each layer is measured based on the interval between the layer boundaries. Of course, it is not limited to the layer thickness, and the analysis map is not limited to the layer thickness, and may be, for example, a map showing the curvature distribution of the fundus.

The front image may be, for example, a front image taken by the front photographing optical system 200, or may be front OCT data (also referred to as face OCT data) generated from OCT three-dimensional data. In the case of 3D OCT data, it may be 3D OCT data that is the basis of 3D motion contrast data. The analysis map may be, for example, a color map that two-dimensionally expresses the analysis result on the eye to be inspected (for example, the thickness and curvature of the fundus layer). In FIG. 4, as the second image data 502, an image in which the analysis map is superimposed on the front image is displayed.

<Analysis chart>
The CPU 71 may superimpose and display the analysis chart 504 on the second image data 502. In this case, the second image data 502 may be associated with the measurement result based on the analysis result for the three-dimensional OCT data (for example, the measurement data of the analysis map) in advance (registration), and the analysis chart 504 is set. The measurement result corresponding to the area is output. In this case, the second image data 502 may be associated with the three-dimensional OCT data, the analysis process may be executed for the region in which the analysis chart is set, or the measurement result may be output based on the analysis result. In this case, the three-dimensional OCT data is preferably the three-dimensional OCT data that is the basis of the MC data. This is because the positional correspondence (registration) between the MC data and the second image data is easy and accurate.

For example, the analysis chart 504 may be an analysis chart for measuring the basic statistic of the measurement result in the preset section, or the basic statistic in the section may be measured. The sections forming the analysis chart 504 may be one region or a plurality of sections. In the case of a plurality of sections, the basic statistic may be measured for each divided section. The basic statistic may be a representative value (mean value, median value, mode value, maximum value, minimum value, etc.), dispersal degree (variance, standard deviation, coefficient of variation), or the like.

For example, the analysis chart 504 may be a chart for obtaining the average for each region with respect to the two-dimensional distribution of the layer thickness of the fundus. Further, the analysis chart 504 may be provided with a numerical display area for displaying the layer thickness in a predetermined area numerically. Instead of the numerical display, color coding may be performed for each section according to the measurement result. The layer thickness data may be the sum of each layer or the thickness of a certain layer (for example, the optic nerve fiber layer).

The analysis chart 504 can be arbitrarily selected, and when the thickness map is a macula map, the analysis chart 504 can be selected by, for example, the examiner from GCHART, S / I chart, and ETDRS. When the thickness map is a teat map, the analysis chart can be selected from, for example, an overall chart, an upper and lower chart (2 divisions), a TSNIT chart (4 divisions), and a LockHour chart (12 divisions).

The CPU 71 may receive the operation signal from the operation unit 76 and change the display position of the analysis chart 504 on the second image data 502. As a result, the analysis area according to the analysis chart 504 on the second image data 502 is changed. The CPU 71 may obtain the analysis result in the changed analysis area in conjunction with the change of the display position of the analysis chart 504. A part of the analysis chart may extend beyond the second image data 502.

For example, the examiner moves the analysis chart 504 using the operation unit 76 to move the center 504c of the analysis chart to the reference site of the fundus (for example, the center of the fovea (see M in FIG. 4), the center of the optic nerve head). , Abnormal part). Thereby, for example, the measurement result by the analysis chart 504 can be obtained centering on the reference portion of the fundus. For example, the average layer thickness of the entire chart centered on the reference part, the layer thickness of the reference part, the average layer thickness in a predetermined area centered on the reference part (for example, 1, 2, 3 mm), etc. are measured. May be good. As a result, measurement results centered on the reference site on the fundus can be obtained, which is clinically useful.

<Linkage between analysis chart and blood vessel analysis area>
For example, the CPU 71 may extract the blood vessel region on the MC data by using the position information of the analysis chart 504. More specifically, the CPU 71 may move the position of the blood vessel analysis region on the MC data in conjunction with the movement of the analysis chart 504. In this case, the CPU 71 may move the display (for example, graphic 404) indicating the blood vessel analysis region on the MC data 402. That is, the position of the blood vessel analysis region changes in conjunction with the movement of the analysis region according to the analysis chart 504.

As a result of the movement of the blood vessel analysis area, the blood vessel analysis area on the MC data is changed. Therefore, the CPU 71 may obtain the analysis result in the changed blood vessel analysis region in conjunction with the change in the blood vessel analysis region (the method of blood vessel analysis will be described later).

When linking the analysis chart and the blood vessel analysis region, the CPU 71 has the center 504c of the analysis chart 504 in the second image data 502 and the center 404c of the blood vessel analysis region in the MC data 402 at the same position in the analysis. The vessel analysis area may be moved so that it is located. That is, the CPU 71 may set the center of the analysis region at a position corresponding to the center position of the analysis chart 504 in the second image data 502 in the MC data 402. In this case, it is preferable that the second image data 502 and the MC data 402 are positionally associated (registered).

Here, for example, when the examiner sets the center 504c of the analysis chart 504 to the reference site of the fundus (for example, the center of the fovea centralis, the center of the optic nerve head, the abnormal site), the center of the blood vessel analysis region is the reference of the fundus. It is automatically set for the part. As a result, the reference position of the analysis can be matched between the analysis by the analysis chart 504 and the analysis for the MC data 402 without changing the analysis area on the MC data 402 again.

<Setting of blood vessel analysis area>
The blood vessel analysis area may be arbitrarily set by the examiner. For example, the CPU 71 may receive an operation signal from the operation unit 76 and change the position of the blood vessel analysis region on the MC data. In this case, the position of the display indicating the blood vessel analysis region may be changed. The CPU 71 may obtain the analysis result in the changed blood vessel analysis area according to the change in the blood vessel analysis area. In this case, the CPU 71 may move the position of the analysis chart 504 on the second image data 502 in conjunction with the movement of the blood vessel analysis region. As a result, it is possible to save the trouble of adjusting the position of the analysis chart 504.

When analyzing a plurality of motion contrast data, it may be used to set the position of the blood vessel analysis region in the second motion contrast data in conjunction with the change in the position of the blood vessel analysis region in the first motion contrast data. Good. For example, it can be applied in the analysis of a plurality of motion contrast data different in the depth direction of the fundus. Further, the CPU 71 utilizes the first data area set on the first motion contrast data, and the second data that corresponds to the first data area in the second motion contrast data. The artifacts in the region may be removed (eg, the brightness of each pixel in the second data region is subtracted from the brightness of each brightness in the first data region).

The range (size) of the blood vessel analysis area may be set by the examiner. The range of the blood vessel analysis region may be set according to the acquisition region of MC data 402 on the fundus. The acquisition region may be set according to different acquisition regions with respect to the surface direction of the fundus. For example, the range may be set for the macula site and the papillary site, respectively.

As the setting according to the acquisition area, it may be possible to set according to different acquisition areas in the depth direction of the fundus. For example, ranges may be set for different vascular layers. Of course, the range is not limited to the vascular layer, and the range may be set for different retinal layers (or choroidal layers). This enables blood vessel analysis according to the acquisition region on the fundus. When a plurality of frontal MC data are generated for each blood vessel layer, the range of the blood vessel analysis region may be preset in the frontal MC data of each blood vessel layer. This enables blood vessel analysis according to each blood vessel layer.

FIG. 5 is an example of a setting screen, in which the macula map shows motion contrast data centered on the macula and the papilla map shows motion contrast data centered on the papilla, and the range (for example, diameter) is shown in map units. Is set. When setting the range, for example, the CPU 71 may change the range (size) of the graphic 404 by receiving an operation signal from the operation unit 76. Further, the range of the blood vessel analysis region may be the same as that of the analysis chart 504. Further, the range of the blood vessel analysis region may be set based on the range of the analysis chart 504.

In the above description, the position and range (size) of the blood vessel analysis region can be set as the change parameters of the blood vessel analysis region, but the present invention is not limited to this. For example, the shape of the blood vessel analysis region may be set (eg, circle, ellipse, rectangle, etc.). In this case, the shape of the blood vessel analysis region may be set according to the acquisition region of the MC data 402 on the fundus.

The blood vessel analysis region may be a region divided into a plurality of sections, and blood vessel analysis may be performed in each section. A plurality of blood vessel analysis regions having different arrangement positions or ranges (sizes) of each section may be selectable.

In this case, the division pattern of the blood vessel analysis region may be set according to the acquisition region of the MC data 402 on the fundus. For example, the Superficial Capillary Plexus may be an entire chart (one section), and the Intermediate Capillary Plexus may be an S / I chart (upper and lower divided sections). In this case, the arrangement position and range of each section of the blood vessel analysis region may be set to be the same as the arrangement position and range of each section of the analysis chart 504. Thereby, the analysis result of each section of the analysis chart 504 and the analysis result of each section in the blood vessel analysis region can be evaluated in association with each other. Therefore, the relationship between the blood vessel analysis result of the fundus and the morphological analysis result (for example, layer thickness) of the fundus can be confirmed in section units.

<Blood vessel extraction processing, blood vessel measurement>
The CPU 71 may display the measurement result in the set blood vessel analysis area on the display unit 75 by analyzing the MC data 402 in the blood vessel analysis area set as described above. In this way, the measurement on the analysis chart and the measurement on the MC data 402 can be smoothly performed. The analysis result may be displayed as a numerical value 406 on the MC display area 400, for example.

For example, the CPU 71 discriminates between a blood vessel region and a non-blood vessel region by performing image processing analysis on a region set as a blood vessel analysis region on MC data. The blood vessel region is extracted by the discrimination process. In this case, the non-vascular region may be extracted by the discrimination process.

The discrimination process may be, for example, a threshold value process, and pixels that satisfy the threshold value may be defined as a blood vessel region, and pixels that do not satisfy the threshold value may be discriminated as a non-blood vessel region. The threshold value itself may be arbitrarily set by the examiner, or may be predetermined as a fixed value. Further, the threshold value may be set after performing an image analysis process on the MC data 402.

For example, the CPU 71 may perform measurement on the blood vessel region based on the result of the discrimination process. The CPU 71 may measure the blood vessel region based on the blood vessel region extracted by the discrimination process. The measurement result may be, for example, blood vessel density and blood vessel area. As the density of the blood vessel region, for example, the area of the blood vessel (blood vessel volume) per unit area can be obtained by obtaining the ratio of the blood vessel region in the entire blood vessel analysis region. The measurement result is not limited to this, and may be, for example, the total amount of blood vessels, the degree of meandering of blood vessels, the regularity of blood vessels, and the like. When the blood vessel analysis region is divided into a plurality of sections, the CPU 71 may obtain the ratio and the difference of the measurement results between the sections. Thereby, for example, the symmetry of blood vessels can be obtained.

Regarding blood vessel measurement, since the scanning range of OCT may differ depending on the axial length of the eye, the CPU 71 may correct the measurement result according to the axial length value of the eye to be inspected. The CPU 71 may discriminate between the vascular region and the non-vascular region and display them based on the result of the discriminant processing. For example, the vascular region may be colored and displayed.

For example, the CPU 71 may perform reanalysis in response to a change in the blood vessel analysis area and update the result of the blood vessel extraction process. In this case, the CPU 71 may update the result of the blood vessel extraction process and update the measurement result regarding the blood vessel region based on the updated blood vessel extraction result.

For example, the CPU 71 may update the measurement result regarding the blood vessel region in response to the change in the blood vessel analysis region linked to the change in the analysis chart 504. As a result, when the examiner sets the center 504c of the analysis chart 504 at the reference site of the fundus (for example, the center of the fovea centralis and the center of the optic nerve head), the blood vessel measurement centering on the reference site of the fundus can be smoothly performed. Can be done.

When automatically discriminating between the blood vessel region and the non-blood vessel region, the CPU 71 applies a binarization process (for example, a discriminant analysis method) from the brightness value of the MC data 402 to vascularize / non-blood vessel. The area may be defined. When the analysis chart 504 has a plurality of sections, the threshold value may be set for each region corresponding to each section of the chart, or the threshold value may be set for the entire region corresponding to the entire chart. When the blood vessel analysis region is divided into a plurality of sections, a threshold value may be set for each region corresponding to each section, or a threshold value may be set for the entire blood vessel analysis region.
In this case, the CPU 71 sets only a predetermined area (for example, 2.0 mm) from the center coordinates corresponding to the center 504c of the analysis chart 504 as a target area for calculating the binarization parameter (threshold value), and sets the calculated parameter as the target area. It may be used to perform binarization processing on the area around the target area. In many cases, the peripheral part of the MC data 402 contains unnecessary components. For example, in the case of an eye having a long axial length, the curvature of the eye is large, so that the basic OCT data itself is lacking when the image is taken in a wide angle of view. In addition, the eye may move at the edge of the data (for example, toward the end of imaging), and the underlying OCT data may be missing. Therefore, the discrimination process can be performed accurately by using the position of the analysis chart 504.

<Detection of foveal avascular region (FAZ) using analysis chart>
Next, a case where the FAZ of the eye to be inspected is extracted by the analysis process for the MC data 402 will be described. In this case, the MC data is subjected to an analysis process for extracting the avascular analysis region.

FIG. 6 is a diagram showing an example of an analysis screen when extracting FAZ. Those with the same number as in FIG. 4 shall have the same function and configuration unless otherwise specified.

For example, the CPU 71 may perform the extraction process of the foveal avascular region (hereinafter, FAZ) on the MC data by using the position information of the center 504c of the analysis chart 504. More specifically, when FAZ is extracted by image processing, the CPU 71 may extract a region corresponding to FAZ by analyzing peripheral pixel values with reference to a seed point S (start of region detection). ..

Since FAZ is an avascular region and has a low brightness value, for example, FAZ is extracted by determining the brightness and connectivity around the center with reference to the seed point S set in the center of FAZ. To. The extraction processing method includes, for example, extraction processing based on graph theory, extraction by the region expansion method, and extraction by a dynamic contour model such as Snake and Level Set. In addition, the method described in "Noninvasive Imaging of the Foveal Avascular Zone with High-Speed, Phase-Variance Optical Coherence Tomography" by Kim et al., January 2012 may be used.

Here, in the CPU 71, the center 504c of the analysis chart 504 in the second image data 502 and the reference position (for example, the seed point S) of the analysis process on the MC data 402 are arranged at the same position in the analysis. The reference position of the avascular extraction process may be set so as to be performed. Here, the CPU 71 makes the position of the center 504c of the analysis chart 504 coincide with the reference position (for example, the seed point S) of the avascular extraction process on the MC data 402. That is, the CPU 71 may set the reference position for the analysis process at the position corresponding to the center position of the analysis chart 504 in the second image data 502 in the MC data 402. In this case, it is preferable that the second image data 502 and the MC data 402 are positionally associated (registered).

For example, when the center 504c of the analysis chart 504 is set at the center of the fovea, the reference position of the analysis process (for example, the position of the seed point S) is set at the center of the fovea, so that FAZ can be detected smoothly. it can. If it deviates from the reference position of the analysis processing, the image processing may be performed mainly on the blood vessel region, and the FAZ extraction accuracy may be lowered.

Of course, the CPU 71 may receive an operation signal from the operation unit 76 and set a reference position in the analysis process, or may detect the FAZ by image processing with the set reference position as a reference. In this case, the CPU 71 may change the display position of the analysis chart 504 so that the reference position of the analysis process at the time of FAZ extraction and the center 504c of the analysis chart 504 are arranged at the same position in the analysis. ..

The above analysis is not limited to blood vessels, and can be applied to vascular analysis (for example, lymphatic vessels) as a vascular analysis region.

In the above description, the analysis process is limited to the analysis area, but the analysis process is not limited to this, and the CPU 71 performs the analysis process for the set analysis area and also performs the analysis process for the other areas. You may.

In the above description, the front MC data has been described as an example, but if it is MC data, the present embodiment can be applied. For example, the analysis area of the 3D MC data may be set based on the position information of the analysis chart on the 3D OCT data. Of course, the MC data may be, for example, one-dimensional MC data or two-dimensional MC data.

In the above description, the MC data is displayed on the display unit 75, and the measurement result of the blood vessel for the MC data is output. However, the present invention is not limited to this, and the MC data is not displayed and the second image is displayed. Along with the data 502, only the measurement result performed on the CPU 71 may be displayed. This makes it possible to simplify the display on the screen.

In the above description, the front image of the subject and the analysis map for the subject are used as the second image data, but for example, the second motion contrast data is different from the motion contrast data for which the analysis process is performed. You may. As a result, it is possible to smoothly analyze a plurality of motion contrast data.

Further, when a wide range of MC data is generated by synthesizing a plurality of front MC data different with respect to the surface direction of the fundus, the CPU 71 may set an area wider than one front MC data as an analysis area. Good. This enables analysis in a wide range. Further, the CPU 71 may set an analysis area for each front MC data that forms a wide range of MC data generated as described above. In this case, a plurality of analysis areas may be set in each front MC data.

In the above description, the fundus of the eye to be inspected has been described as an example, but the present invention is not limited to this, and the application is also applicable to the anterior segment of the eye to be inspected. Furthermore, it is applicable not only to the eye to be inspected but also to other motion contrast data acquired by OCT (for example, motion contrast data in tissues other than the eye).

1 OCT motion contrast data analysis device 10 OCT device 70 Control unit 75 Display unit 400 MC display area 402 MC data 500 Second image display area 502 Second image data 504 Analysis chart

Claims (7)

It is an OCT motion contrast data analysis device for analyzing OCT motion contrast data of the eye to be inspected acquired by an optical coherence tomography.
The first analysis region divided into a plurality of sections is set to the OCT data of the fundus of the eye to be inspected, which is image data different from the OCT motion contrast data, and the fundus of the eye to be inspected in the plurality of preset sections is set. An acquisition method for acquiring basic statistics on layer thickness,
It has an analysis processing means for setting a second analysis region divided into a plurality of sections to the OCT motion contrast data of the fundus of the eye to be inspected and performing analysis processing of the motion contrast data.
An OCT motion contrast data analysis apparatus, characterized in that the arrangement position and range of each section in the second analysis area are the same as the arrangement position and range of each section in the first analysis area. The OCT motion contrast data analysis apparatus according to claim 1, wherein an analysis region divided into a plurality of sections is set on the OCT motion contrast data based on an analysis chart. The OCT motion contrast data analysis device according to claim 2, wherein the analysis chart is an analysis chart for measuring basic statistics of measurement results of an eye to be inspected in a plurality of preset sections. The OCT motion contrast data analysis apparatus according to any one of claims 1 to 3, wherein the measurement result in the second analysis region is displayed on a monitor. The OCT motion contrast data analysis apparatus according to any one of claims 1 to 4, wherein the measurement result in the second analysis region is corrected according to the axial length value of the eye to be inspected. The OCT motion contrast data analysis apparatus according to any one of claims 1 to 5, wherein the blood vessel density of the eye to be inspected is measured based on the analysis result of the analysis process. It is an OCT motion contrast data analysis program executed in the OCT motion contrast data analysis device for analyzing the OCT motion contrast data of the eye to be inspected acquired by the optical interference tomography, and is performed by the processor of the OCT motion contrast data analysis device. By being executed
The first analysis region divided into a plurality of sections is set to the OCT data of the fundus of the eye to be inspected, which is image data different from the OCT motion contrast data, and the fundus of the eye to be inspected in the plurality of preset sections is set. Steps to get basic statistics on layer thickness,
It has a step of setting a second analysis region divided into a plurality of sections to the OCT motion contrast data of the fundus of the eye to be inspected and performing analysis processing of the motion contrast data.
An OCT motion contrast data analysis program characterized in that the arrangement position and range of each section in the second analysis area are the same as the arrangement position and range of each section in the first analysis area.

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