JP2020044362A - Oct motion contrast data analysis apparatus and oct motion contrast data analysis program - Google Patents

Abstract

To favorably analyze motion contrast data.SOLUTION: The OCT motion contrast data analysis apparatus for analyzing motion contrast data of a subject acquired by an optical coherence tomograph includes the steps of: setting up a first analysis area divided into a plurality of sections on OCT data of the fundus oculi of the subject's eye, the image data different from the OCT motion contrast data and acquiring a basic statistic relating to the layer thickness of the fundus oculi of a subject's eye in the multiple preset sections; and setting up a second analysis area divided into a plurality of sections on the motion contrast data of the fundus oculi of the subject's eye and performing analysis processing of the motion contrast data. The arrangement positions and ranges of the respective sections of the second analysis area are same as the arrangement positions and ranges of the respective sections in the first analysis area.SELECTED DRAWING: Figure 4

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 using the OCT technique has attracted attention (see Non-Patent Document 1).

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

  However, various improvements have been made to the imaging of the motion contrast data, but there is room for improvement in the analysis relation in various aspects.

  For example, the analysis using the motion contrast data and the analysis using the OCT data (for example, the fundus layer thickness analysis) are independent and troublesome. Also, it was difficult to compare the results of each analysis. Analyzing a plurality of motion contrast data was troublesome.

  An object of the present disclosure is to provide an OCT motion contrast data analysis device and an OCT motion contrast data analysis program that can appropriately analyze motion contrast data in view of at least one of the problems of the related art. .

  In order to solve the above problem, the present disclosure is characterized by including the following configuration.

(1) An OCT motion contrast data analysis device for analyzing motion contrast data of a subject acquired by an optical coherence tomography, wherein the first analysis region divided into a plurality of sections includes the OCT motion contrast data. Setting the OCT data of the fundus of the eye to be examined, which is image data different from the data, to obtain basic statistics regarding the layer thickness of the fundus of the eye to be examined in a plurality of preset sections; Setting the second analysis region to the motion contrast data of the fundus of the eye to be examined, and performing an analysis process of the motion contrast data, wherein the arrangement position and range of each section of the second analysis region Is the same as the arrangement position and range of each section in the first analysis area And it features.
(2) An OCT motion contrast data analysis program executed by an OCT motion contrast data analysis device for analyzing motion contrast data of a subject acquired by an optical coherence tomography, wherein the OCT motion contrast data analysis program includes: By being executed by the processor, the first analysis area divided into a plurality of sections is set as OCT data of the fundus of the eye to be examined, which is image data different from the OCT motion contrast data, and a plurality of sections set in advance are set. Acquiring basic statistics regarding the layer thickness of the fundus of the eye to be examined in the section of the eye, and setting a second analysis area divided into a plurality of sections as the motion contrast data of the fundus of the eye to be examined, Analysis of Anda step of performing, position and range of each section of the second analysis region, wherein the first is identical to the position and the range of each section of the analysis region.

It is a block diagram showing the outline of this example. FIG. 2 is a diagram illustrating an example of an optical system of an OCT device. FIG. 9 is a diagram for describing acquisition of motion contrast. It is a figure showing an example of a display screen. It is a figure showing an example of a setting screen. It is a figure showing an example of a display screen.

  Hereinafter, the present embodiment will be briefly described. The OCT motion contrast data analyzer of the present embodiment analyzes, for example, motion contrast data of a subject acquired by an optical coherence tomography. The OCT motion contrast data analysis device includes, for example, an analysis processing unit (for example, the control unit 70). The analysis processing unit performs an analysis process 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. Thus, the present analysis apparatus 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 an analysis process on the motion contrast for the set analysis region. Such an analysis process may be applied to, for example, a blood vessel region extraction process in the analysis region.

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

  Further, an analysis area in the 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, interface motion contrast data, or three-dimensional motion contrast data.

  Note that the analysis chart may be an analysis chart showing basic statistics of measurement results in a set section, for example, basic statistics of measurement results based on analysis results for OCT data serving as a basis for motion contrast data. It may be.

  The second image data may at least overlap the motion contrast data with respect to the acquired region 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, an acquisition range of motion contrast data with respect to an acquisition range on the subject.

  The analysis processing unit may perform an analysis process based on the changed analysis chart, for example, in conjunction with the change of the analysis chart. This makes it possible to smoothly change the analysis of the motion contrast 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 on 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 on the motion contrast data based on the center position of the analysis chart, for example.

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

  Note that the analysis processing unit may set the vascular analysis region based on the analysis chart. Then, the analysis processing unit may perform a vessel extraction process in the set vessel analysis region.

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

  The analysis processing unit may set, for example, the reference position of the no-vessel extraction processing in the motion contrast data based on the position of the analysis chart. Then, the analysis processing unit may perform the no-vessel extraction processing based on the set reference position.

  Note that the present device may further include, for example, a first instruction receiving unit (for example, the 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 an analysis process on the motion contrast data based on the position information of the analysis chart set by the first instruction receiving unit.

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

  Note that the present device may further include, for example, a second instruction receiving unit (for example, the control unit 70). The second instruction receiving unit receives, for example, an instruction from the examiner for setting the position of the analysis area on the motion contrast data or the reference position of the analysis processing. 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.

  Note that the analysis processing unit may be able to set the position of the analysis chart based on the position information of the analysis region or the position information of the reference position set by the second instruction receiving unit.

  Note that the second image data may be associated with OCT data on which motion contrast data is based.

  Note that, when extracting a blood vessel region by threshold processing as the analysis processing, the analysis processing unit may set an area on the motion contrast data set for obtaining the threshold based on the position information of the analysis chart. .

  Note that the present 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 based on the motion contrast data. In this case, the analysis processing unit may set an 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 subject's eye. In this case, the analysis processing unit can set, for example, at least one of a position, a range, and a shape of the analysis area set for performing the analysis processing according to an acquisition area of the motion contrast data on the subject. It may be. Of course, the position, range, shape, and the like of the analysis region may be set in advance, or the range may be changed according to the analysis result for each data.

  Note that the acquisition region may be in the surface direction of the subject (for example, a macula or a nipple in the fundus of the eye to be examined) or in the depth direction of the subject (for example, for each blood vessel layer in the fundus of the subject). You may.

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

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

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

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

  The OCT analyzer 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, and 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, for example, various information.

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

  Various operation instructions from the examiner are input to the operation unit 76. The operation unit 76 outputs a signal corresponding to the input operation instruction to the CPU 71. As the operation unit 76, for example, at least one of a 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 may be 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 apparatus 1 according to the present embodiment is connected to, for example, an OCT device 10. The OCT analyzer 1 may be, for example, an integrated configuration housed in the same housing as the OCT device 10 or may be 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 a storage medium.

<OCT device>
Hereinafter, an outline of the OCT device 10 will be described with reference to FIG. For example, the OCT device 10 irradiates the eye E with measurement light, and obtains an OCT signal obtained from 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 with 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 (light splitter) 104, a measurement optical system 106, a reference optical system 110, a detector 120, and the like. The detailed configuration of the OCT optical system should be referred to, for example, JP-A-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 measurement light (sample light) and reference light by a coupler 104. The split 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 oculi Ef of the eye E through the measurement optical system 106. After that, the detector 120 receives the interference light resulting from the synthesis of the measurement light reflected by the eye E and 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 in the X and Y directions (transverse direction) on the fundus. For example, the CPU 71 controls the operation of the scanning unit 108 based on the set scanning position information, and acquires an OCT signal based on the light receiving signal detected by the detector 120. The reference optical system 110 generates reference light that is combined with reflected light obtained by reflection of the measurement light at the fundus oculi Ef. The reference optical system 110 may be a Michelson type or a Mach-Zehnder type.

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

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

<Front photographing optical system>
The front imaging optical system 200 captures, for example, the fundus oculi Ef of the eye E from the front direction (for example, the optical axis direction of the measurement light), and obtains a front image of the fundus oculi Ef. The front photographing optical system 200 may have, for example, an apparatus configuration of a scanning laser ophthalmoscope (SLO) (see, for example, JP-A-2015-66242) or a configuration of a so-called fundus camera type. (See Japanese Patent Application Laid-Open No. 2011-10944). The OCT optical system 100 may be used as the front photographing optical system 200, and a front image may be acquired based on a detection signal from the detector 120.

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

<Acquisition of motion contrast data>
The OCT analysis apparatus 1 of the present embodiment may, for example, process the OCT data detected by the OCT device 10 to obtain motion contrast data. The CPU 71 controls the driving of the scanning unit 108 to scan the measurement light in the area A1 on the fundus oculi 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 causes the measurement light to scan in the x direction along the scanning lines SL1, SL2,..., SLn in the area A1. Note that scanning the measurement light in a direction (for example, the x direction) crossing the optical axis direction of the measurement light is referred to as “B scan”. The two-dimensional OCT data obtained by one B-scan will be described as one-frame two-dimensional OCT data. For example, the CPU 71 may scan the measurement light two-dimensionally in the xy directions, and 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 information that captures, for example, blood flow of the eye to be examined, changes in retinal tissue, and the like. When acquiring motion contrast data, the CPU 71 acquires at least two temporally different OCT data for the same position of the subject's eye. For example, in each scan line, the CPU 71 performs a plurality of B scans at different times to acquire a plurality of OCT data at different times.

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

  As described above, when acquiring a plurality of temporally different OCT data for the same position, the CPU 71 processes the OCT data to acquire motion contrast data. Examples of a method of calculating the OCT data for obtaining the motion contrast include a method of calculating an intensity difference of the complex OCT data, a method of calculating a phase difference of the complex OCT data, a method of calculating a vector difference of the complex OCT data, A method of multiplying the phase difference and the vector difference of the complex OCT signal, a method of using signal correlation (correlation mapping), and the like can be given. In addition, as one of the calculation methods, refer to, for example, JP-A-2015-131107.

  The CPU 71 may obtain the three-dimensional motion contrast data of the eye E by arranging the motion contrast data on different scanning lines. As described above, the motion contrast data is not limited to the phase difference, but may be an intensity difference, a vector difference, or the like.

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

  The CPU 71 may obtain an at least one analysis result by setting an analysis region for the motion contrast data and performing an analysis process on the set analysis region. In this case, the CPU 71 may set the analysis area in the motion contrast data based on the position information of the analysis chart on the second image data which is image data different from the motion contrast data.

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

  FIG. 4 is a diagram illustrating 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 simultaneously, 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 shown in FIG. 4, front MC data (also referred to as interface MC data) as the MC data 402. May be displayed. The front MC data may be acquired, for example, by extracting three-dimensional MC data for at least a part of the region in the depth direction (for example, refer to Japanese Patent Application No. 2015-121574). For example, the front MC data may be generated by an integrated value or a maximum value in the depth direction of 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, a graphic 404) indicating the blood vessel analysis area on the MC data 402 on the MC data 402. The display indicating the blood vessel analysis area may be a frame display indicating the outer edge of the blood vessel analysis area as shown by the graphic 404 in FIG. 4 or a display in which the blood vessel analysis area and the non-blood vessel analysis area are color-coded. Is also 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. For example, at least one of a front image and an analysis map is displayed. Is also good. As the second image data 502, image data that at least partially overlaps with the MC data 402 with respect to the acquired region is used. For example, when the MC data 402 is data centering on the macula, the second image data related to the macula is displayed. When the MC data 402 is data centering on the nipple, the second image data related to the nipple is displayed. May be done.

  As the analysis map, for example, a map indicating a two-dimensional distribution of the measurement result regarding the fundus may be used. In this case, for example, a color map that is color-coded according to the measured value may be used. As the analysis map, for example, a thickness map indicating the layer thickness, a comparison map indicating 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, the layer thickness of the eye to be examined and the normal eye database May be a deviation map showing a deviation from the layer thickness of the normal eye stored as a standard deviation, and an examination date comparison thickness difference map showing a difference between the thicknesses of the respective examination dates. When obtaining 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 layer boundaries. Of course, the analysis map is not limited to the layer thickness, and is not limited to the layer thickness, and may be, for example, a map showing a curvature distribution of the fundus.

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

<Analysis chart>
The CPU 71 may display the analysis chart 504 so as to be superimposed on the second image data 502. In this case, the second image data 502 may be previously associated with a measurement result (for example, measurement data of an analysis map) based on the analysis result of the three-dimensional OCT data (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, an analysis process may be performed on a region where an analysis chart is set, or a measurement result may be output based on the analysis result. In this case, the three-dimensional OCT data is preferably three-dimensional OCT data that is the basis of 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 a basic statistic of a measurement result in a preset section, or a basic statistic in a section may be measured. The section forming the analysis chart 504 may be a single region or a plurality of sections. In the case of a plurality of sections, a basic statistic may be measured for each divided section. The basic statistics may be representative values (average value, median value, mode value, maximum value, minimum value, etc.), degree of dispersion (variance, standard deviation, coefficient of variation), and the like.

  For example, the analysis chart 504 may be a chart that calculates an average for each region with respect to a two-dimensional distribution of the fundus layer thickness. Further, the analysis chart 504 may be provided with a numerical value display area for numerically displaying the layer thickness in the predetermined area. Instead of numerical display, color coding may be performed in section units 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. When the thickness map is a macula map, for example, the examiner can select the analysis chart 504 from GCHART, S / I chart, and ETDRS. When the thickness map is a nipple map, the analysis chart can be selected from, for example, an overall chart, a vertical chart (divided into two), a TSNIT chart (divided into four), and a ClockHour chart (divided into twelve).

  The CPU 71 may receive an operation signal from the operation unit 76 and change the display position of the analysis chart 504 on the second image data 502. Thus, the analysis area on the second image data 502 by the analysis chart 504 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. Note that 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 so that the center 504c of the analysis chart is set to the reference part of the fundus (for example, the fovea center (see M in FIG. 4), the optic disc center). , Abnormal part). As a result, for example, a measurement result based on the analysis chart 504 is obtained around the reference portion of the fundus. For example, the average layer thickness in the entire chart centered on the reference region, the layer thickness of the reference region, the average layer thickness (for example, 1, 2, 3 mm) in a predetermined area centered on the reference region are measured. Is also good. As a result, a measurement result centering on the reference site on the fundus is obtained, which is clinically useful.

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

  When the analysis chart and the blood vessel analysis area are linked, the CPU 71 determines that the center 504c of the analysis chart 504 in the second image data 502 and the center 404c of the blood vessel analysis area in the MC data 402 are at the same position in the analysis. The blood vessel analysis region may be moved so as to be arranged. That is, the CPU 71 may set the center of the analysis area in the MC data 402 at a position corresponding to the center position of the analysis chart 504 in the second image data 502. 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 a reference part of the fundus (for example, the center of the fovea, the center of the optic disc, or the abnormal part), the center of the blood vessel analysis area is set to the reference of the fundus. It is automatically set to the part. Thus, the reference position of the analysis can be matched between the analysis based on the analysis chart 504 and the analysis on 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 region 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 area on the MC data. In this case, the display position indicating the blood vessel analysis region may be changed. The CPU 71 may obtain an 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 area. As a result, the labor for adjusting the position of the analysis chart 504 can be saved.

  When analyzing a plurality of motion contrast data, it may be used to set the position of the blood vessel analysis area in the second motion contrast data in conjunction with the change in the position of the blood vessel analysis area in the first motion contrast data. Good. For example, the present invention can be applied to the analysis of a plurality of different motion contrast data in the depth direction of the fundus. Further, the CPU 71 uses the first data area set on the first motion contrast data, and uses the first data area in the second motion contrast data to correspond to the second data position corresponding to the first data area. Artifacts in the area may be removed (for example, the luminance of each luminance in the first data area is subtracted from the luminance of each pixel in the second data area).

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

  The setting according to the acquisition region may be set according to a different acquisition region in the depth direction of the fundus. For example, ranges may be set for different blood vessel layers, respectively. Of course, the range is not limited to the blood vessel layer, and ranges may be set for different retinal layers (or choroid layers). Thereby, a blood vessel analysis according to the acquisition area on the fundus becomes possible. When a plurality of frontal MC data is generated for each blood vessel layer, the range of the blood vessel analysis region may be set in advance by the frontal MC data of each blood vessel layer. This enables a blood vessel analysis according to each blood vessel layer.

  FIG. 5 is an example of a setting screen. The macula map shows motion contrast data centered on the macula, and the nipple map shows motion contrast data centered on the nipple. 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 range as 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 (for example, a circle, an ellipse, a 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 a blood vessel analysis may be performed in each section. A plurality of blood vessel analysis regions that differ in either the arrangement position or range (size) 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 two 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 relevance between the blood vessel analysis result of the fundus and the morphology analysis result (eg, layer thickness) of the fundus can be confirmed in section units.

<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 performed smoothly. The analysis result may be displayed as a numerical value 406 on the MC display area 400, for example.

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

  The determination processing may be, for example, threshold processing. Pixels satisfying the threshold may be determined as a blood vessel area, and pixels not satisfying the threshold may be determined as a non-blood vessel area. The threshold value itself may be arbitrarily set by the examiner, or may be determined in advance as a fixed value. Further, the threshold value may be set through an image analysis process on the MC data 402.

  For example, the CPU 71 may measure the blood vessel region based on the result of the determination process. The CPU 71 may measure the blood vessel region based on the blood vessel region extracted by the determination processing. The measurement result may be, for example, a blood vessel density or a blood vessel area. As the density of the blood vessel region, for example, the area of the blood vessel per unit area (blood vessel volume) is 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 calculate the ratio and the difference of the measurement results between the sections. Thereby, for example, symmetry of a blood vessel can be obtained.

  In addition, regarding the blood vessel measurement, since the scanning range of the OCT may be different depending on the axial length, the CPU 71 may correct the measurement result according to the axial length value of the eye to be examined. The CPU 71 may discriminate and display the blood vessel region and the non-blood vessel region based on the result of the discrimination process, and may display the blood vessel region by coloring it, for example.

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

  For example, the CPU 71 may update the measurement result related to the blood vessel region in accordance with the change in the blood vessel analysis region linked to the change in the analysis chart 504. Accordingly, when the examiner sets the center 504c of the analysis chart 504 to a reference portion of the fundus (for example, the center of the fovea or the center of the optic disc), blood vessels can be smoothly measured around the reference portion of the fundus. Can be.

Note that when automatically performing the discrimination process 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 thereby perform the blood vessel / non-vascular An area may be defined. When the analysis chart 504 has a plurality of sections, the threshold may be set in units of regions corresponding to each section of the chart, or the threshold may be set in the entire region corresponding to the entire chart. When the blood vessel analysis region is divided into a plurality of sections, a threshold may be set for each region corresponding to each section, or a threshold 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 when calculating a binarization parameter (threshold), and uses the calculated parameter as a target area. The binarization process may be performed on an area around the target area by using the peripheral area of the MC data 402. In many cases, an unnecessary component is included. For example, in the case of an eye having a long axial length, the curvature of the eye is large, so that when the image is captured in a wide range of the angle of view, the basic OCT data itself is lacking. Also, the eye may move at the end of the data (for example, at the end of imaging), and the underlying OCT data may be missing. Therefore, the determination process can be performed with high accuracy 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 subject's eye is extracted by an analysis process on the MC data 402 will be described. In this case, the MC data is subjected to an analysis process for extracting an avascular analysis region.

  FIG. 6 is a diagram illustrating an example of an analysis screen when FAZ is extracted. It is to be noted that components denoted by the same reference numerals as those in FIG. 4 have the same functions and configurations unless otherwise specified.

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

  Since the FAZ is an avascular region and has a low luminance value, for example, the FAZ is extracted by determining the luminance and connectivity around the central portion with reference to the seed point S set at the central portion of the FAZ. You. In addition, as a method of the extraction processing, for example, in addition to the extraction processing based on the graph theory, there is an extraction by an area extension method, and an extraction by a dynamic contour model such as Snake and Level Set. Alternatively, the method described in Kim, et al., “Nonvasive Imaging of the Foveal Avascular Zone with High-Speed, Phase-Variance Optical Coherence Tomography”, January 2012, may be used.

  Here, the CPU 71 arranges 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 processing on the MC data 402 at the same position in the analysis. The reference position of the avascular extraction processing may be set as described above. Here, the CPU 71 matches the position of the center 504c of the analysis chart 504 with the reference position (for example, the seed point S) of the avascular extraction processing on the MC data 402. That is, the CPU 71 may set the reference position of the analysis process in the MC data 402 at a position corresponding to the center position of the analysis chart 504 in the second image data 502. 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, image processing may be performed centering on the blood vessel region, and FAZ extraction accuracy may be reduced.

  Of course, the CPU 71 may receive an operation signal from the operation unit 76 and set a reference position in the analysis processing, or may detect FAZ by image processing based on the set reference position. In this case, the CPU 71 may change the display position of the analysis chart 504 such that the reference position of the analysis processing 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, but can be applied to vascular analysis (for example, lymph vessels) as a vascular analysis region.

  In the above description, the analysis process is performed only on the analysis region. However, the present invention is not limited to this. The CPU 71 performs the analysis process on the set analysis region and also performs the analysis process on other regions. You may.

  In the above description, the front MC data has been described as an example, but the present embodiment can be applied to MC data. For example, the analysis area of the three-dimensional MC data may be set based on the position information of the analysis chart on the three-dimensional 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 measurement result of the blood vessel with respect to the MC data is output after the MC data is displayed on the display unit 75. However, the present invention is not limited to this. Along with the data 502, only the measurement result performed by the CPU 71 may be displayed. Thereby, the display on the screen can be simplified.

  In the above description, the front image of the subject and the analysis map relating to the subject are used as the second image data. However, for example, the second motion contrast data is different from the motion contrast data for performing the analysis process. You may. As a result, a plurality of motion contrast data can be smoothly analyzed.

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

  In the above description, the fundus of the eye to be examined has been described as an example, but the invention is not limited to this, and the present invention is also applicable to the anterior segment of the eye to be examined. Furthermore, the present invention is not limited to the subject's eye, and can be applied to other motion contrast data acquired by OCT (for example, motion contrast data in a tissue other than the eye).

1 OCT motion contrast data analyzer 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 (10)

An OCT motion contrast data analysis device for analyzing motion contrast data of a subject acquired by an optical coherence tomography,
The first analysis region divided into a plurality of sections is set as 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 sections set in advance is set. Obtaining basic statistics about the layer thickness;
Setting a second analysis region divided into a plurality of sections as the motion contrast data of the fundus of the eye to be examined, and performing an analysis process 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. The OCT motion contrast data analysis device according to claim 1, wherein an analysis area divided into a plurality of sections is set on the 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 a subject in a plurality of sections set in advance. The OCT motion contrast data analysis device according to any one of claims 1 to 3, wherein a measurement result in the second analysis area is displayed on a monitor. The OCT motion contrast data analysis device according to any one of claims 1 to 4, wherein the measurement result in the second analysis area is corrected according to an axial length value of the eye to be inspected. The OCT motion contrast data analyzer according to any one of claims 1 to 5, wherein an analysis result of each section in the analysis area and an analysis result of each section of the analysis chart are evaluated in association with each other. The OCT motion contrast according to any one of claims 1 to 6, wherein the second image data is at least one of OCT data of the subject, a front image of the subject, and an analysis map of the subject. Data analysis device. The OCT motion contrast data analysis device according to claim 1, wherein the second image data is associated with OCT data on which the OCT motion contrast data is based. The OCT motion contrast data analysis device according to claim 1, wherein a blood vessel density of the eye to be inspected is measured based on an analysis result obtained by the analysis processing. An OCT motion contrast data analysis program executed by an OCT motion contrast data analysis device for analyzing motion contrast data of a subject acquired by an optical coherence tomography, the program being executed by a processor of the OCT motion contrast data analysis device. Being done
The first analysis region divided into a plurality of sections is set as OCT data of the fundus of the eye to be examined, which is image data different from the OCT motion contrast data, and the fundus of the eye to be examined in the plurality of sections set in advance is set. Obtaining basic statistics about the layer thickness;
Setting a second analysis region divided into a plurality of sections as the motion contrast data of the fundus of the eye to be examined, and performing an analysis process of the motion contrast data,
An OCT motion contrast data analysis program, wherein 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.

Images