JP2019103762A - Oct data analysis device, and oct data analysis program - Google Patents

Abstract

To provide an OCT data analysis device and an OCT data analysis program that allow an analysis result of OCT data to be displayed clearly.SOLUTION: The present invention provides an OCT data analysis device that analyzes OCT data of an analyte acquired with an OCT optical system, the OCT data analysis device having analysis means that analyzes the OCT data to acquire evaluation information of the analyte, and display control means that controls display means to display a distribution amount of the evaluation information.SELECTED DRAWING: Figure 7

Description

  The present disclosure relates to an apparatus for analyzing OCT data acquired by Optical Coherence Tomography (OCT).

  Conventionally, as a device capable of capturing a tomographic image of a subject, a device using an OCT (Optical Coherence Tomography: optical tomographic interferometer) device is known (see Patent Document 1). The OCT device divides the light emitted from the light source into measurement light and reference light, and irradiates the divided measurement light to the tissue of the subject. The OCT device combines the measurement light reflected by the tissue with the reference light to obtain an OCT signal of the combined light.

  Also, in recent years, it has been proposed to acquire motion contrast (for example, one that captures the movement of an object such as blood flow) using an OCT signal obtained by an OCT device. Motion contrast is used for angiographic images and the like.

JP 2011-172822 A

  However, while OCT data acquired from the OCT device has much information to be obtained, the examiner took time to confirm the analysis result of the OCT data.

  This disclosure makes it a technical subject to provide an OCT data analysis device and an OCT data analysis program which display the analysis result of OCT data in an easy-to-see manner in view of the problems of the prior art.

  In order to solve the above-mentioned subject, this indication is characterized by having the following composition.

(1) An OCT data analysis apparatus for analyzing OCT data of a subject acquired by an OCT optical system, the analysis means for acquiring evaluation information of the subject by analyzing the OCT data, and the evaluation information Display control means for causing the display means to display the distribution amount of
And the like.
(2) An OCT data analysis program executed in an OCT data analysis apparatus for analyzing OCT data of a subject acquired by an OCT optical system, the OCT data analysis program being executed by a processor of the OCT data analysis apparatus, the OCT Causing the OCT data analysis device to execute an analysis step of acquiring evaluation information of the subject by analyzing data, and a display control step of causing display means to display a distribution amount of the evaluation information in the subject It is characterized by

It is a block diagram showing an outline of an OCT data analysis device. 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 OCT data. It is a figure which shows an example of an analysis map. It is a histogram which shows the amount of distribution of analysis value. It is the figure which piled up the distribution amount of analysis value and was shown by the bar graph. It is a figure which shows the example which displayed distribution amount by time series. It is the figure which compared and displayed the amount of distribution of the object eye and the normal eye. It is a figure which shows three-dimensional OCT data. It is a figure which shows an example at the time of superimposing a several foveal avascular region. It is a figure showing an example of a parameter about a fovea avascular region. It is a figure which shows an example when a chart is displayed on a fovea avascular region. It is a figure which shows the display example of a foveolar avascular region and a chart. It is a figure which shows an example when a chart of a predetermined size is displayed on a foveolar avascular region. It is a figure which shows an example of the chart displayed on a foveolar avascular region. It is a figure for comparing the foveal avascular region of a normal eye and a diseased eye.

First Embodiment
The first embodiment will be described. The OCT data analysis apparatus (for example, the OCT data analysis apparatus 1) of the first embodiment analyzes OCT data of a subject acquired by an OCT optical system (for example, the OCT optical system 100). The OCT optical system is, for example, an optical system that detects interference light of the reflected light of the measurement light irradiated to the object and the reference light corresponding to the measurement light. The OCT data is, for example, data obtained from the detection result of the interference light. For example, OCT data includes an OCT signal, tomographic image data, motion contrast data, motion contrast image data, and the like.

  The OCT data analysis device (abbreviated as analysis device) includes an analysis unit (for example, control unit 70) and a display control unit (for example, control unit 70). The analysis unit acquires evaluation information (for example, blood vessel density and the like) of the subject by, for example, analyzing the OCT data. For example, an evaluation value may be used as the evaluation information. The evaluation value may be an analysis value indicating an analysis result of the OCT data. The display control unit, for example, causes the display unit (for example, the display unit 75) to display the distribution amount (for example, a histogram or the like) of the evaluation information. The analysis device of the present embodiment can present the state of the subject to the examiner in an easy-to-understand manner by the above configuration. For example, although various evaluation information can be obtained by analyzing a tomographic image based on OCT data, the examiner took a long time to confirm because the amount of information is abundant. However, as the distribution amount of the evaluation information is displayed as in the present embodiment, the state of the subject can be easily confirmed, and the screening can be made more efficient. In addition, since the distribution amount does not require position information, there is no need for alignment when comparing a plurality of pieces of evaluation information.

  In addition, as a display which shows the distribution amount of evaluation information, the graph or table which shows the distribution amount of evaluation information may be sufficient, for example. In this case, for example, it may be a graph or a table that is statistical based on the distribution amount for each evaluation value. As a graph which shows the distribution condition of evaluation information, the graph which represented the amount or composition ratio of the evaluation value divided into steps, for example may be used. As a graph which shows the distribution condition of evaluation information, the class which divided the evaluation value in steps may be made into a horizontal axis, and the histogram which makes the frequency which belongs to each class a vertical axis may be sufficient as it, for example. The table indicating the distribution status of the evaluation information may be a table representing constituent amounts or constituent ratios of the evaluation values divided in stages. Note that a display (for example, a graph, a table) indicating the amount of distribution of evaluation information is displayed together with a mapping display (for example, a blood vessel density map, layer thickness increase) that two-dimensionally shows evaluation information at each position of the subject. May be

  The analysis unit may acquire the first evaluation information by analyzing the first OCT data. The analysis unit may acquire the second evaluation information by analyzing second OCT data different from the first OCT data. In this case, the display control unit may cause the display unit to display the first distribution amount, which is the distribution amount of the first evaluation information, and the second distribution amount, which is the distribution amount of the second evaluation information. For example, the display control unit may cause the screen of the display unit to display the first distribution amount and the second distribution amount side by side on the screen of the display unit. As a result, the analyzer can compare and display a plurality of OCT data without performing processing such as alignment of the first OCT data and the second OCT data.

  The first OCT data may be OCT data of a subject acquired at a first date and time by the OCT optical system. The second OCT data may be OCT data of a subject acquired at a second date and time by the OCT optical system. The second date is a date that is different from the first date by at least one of the date and the time. The analysis unit may acquire the first evaluation information by analyzing the first OCT data acquired at the first date and time. The analysis unit may acquire the second evaluation information by analyzing the second OCT data acquired at the second date and time. The display control unit may display the first distribution amount of the first evaluation information and the second distribution amount of the second evaluation information on the screen of the display unit in time series. By this, the analyzer can display the temporal change of the subject in an easy-to-understand manner. Of course, the analysis unit is not limited to OCT data acquired at two different dates and times, and may analyze multiple pieces of evaluation information by analyzing OCT data acquired at three or more different dates and times. In this case, the display control unit may arrange and display the distribution amounts of the evaluation information acquired at three or more different dates and times on the display unit.

  The first OCT data may be OCT data of a first subject. The second OCT data may be OCT data of a second subject different from the first subject. The analysis unit may acquire the first evaluation information by analyzing the first OCT data of the first subject. The second evaluation information may be acquired by analyzing the second OCT data of the second subject. The display control unit may cause the display unit to display the first distribution amount of the first evaluation information and the second distribution amount of the second evaluation information. For example, the display control unit may arrange and display the first distribution amount and the second distribution amount on the screen. This allows the analyzer to observe OCT data of different subjects.

  The second OCT data may be OCT data of a plurality of subjects different from the first subject. For example, the second OCT data may be a normal eye database created by collecting OCT data of normal eyes. In this case, the display control unit may display the distribution amount of the evaluation information of the first subject and the distribution amount of the evaluation information of the normal eye side by side on the display unit.

  The first OCT data may be OCT data of the right eye of the subject. The second OCT data may be OCT data of the left eye of the subject. The analysis unit may acquire the first evaluation information by analyzing the first OCT data of the right eye. The analysis unit may acquire the second evaluation information by analyzing the second OCT data of the left eye. The display control unit may display the first distribution amount of the first evaluation information and the second distribution amount of the second evaluation information on the screen of the display unit. By this, the analysis device can display the states of the right eye and the left eye in an easy-to-compare manner.

  For example, a histogram may be used as the display of the distribution amount. For example, the display control unit may display a histogram of the evaluation information. By this, the analysis device can display the distribution of the evaluation information intuitively and easily.

  The display control unit may display a stacked bar graph, a bar graph, a pie graph, a numerical value, a graph of a cumulative distribution function, and the like of the evaluation information. Thereby, the examiner can confirm the condition of the subject at a glance by using a graph or a numerical value, as compared to the case of viewing the image of the subject.

  The evaluation information may be the blood vessel density of the subject, the blood vessel diameter of the subject, the number of blood vessel branches, or the like. In this case, for example, the analysis unit calculates motion contrast data from a plurality of OCT signals acquired by the OCT optical system. The motion contrast is, for example, data representing the movement of an object such as blood flow. For example, the analysis unit may acquire the blood vessel density, the blood vessel diameter, the blood vessel bifurcation density, the blood flow volume and the like by analyzing and processing the motion contrast data. The display control means may cause the display unit to display the distribution amounts of these analysis values.

  The evaluation information may be the thickness of the retinal layer of the subject's eye. The analysis unit acquires the thickness of the retinal layer of the subject's eye by image processing of the tomographic image based on the OCT signal. When the layer thickness is determined, for example, the OCT data is divided for each layer by image processing (for example, segmentation processing) on the OCT data, and the thickness of each layer is measured based on the distance between the layer boundaries. The display control unit may display the distribution amount of the layer thickness on the display unit.

  The display control unit may display the distribution amount in the measurement area specified in the subject. For example, the display control unit may specify an area excluding the fovea of the eye to be examined as a measurement area. Since the fovea usually has few blood vessels, by removing the fovea from the measurement area of the distribution amount, it is possible to make the avascular region generated at a site other than the fovea prominent.

  Further, the display control unit may display the distribution amount in the measurement area designated in the subject. For example, when a circular area is designated as a measurement area in the eye to be examined, it is possible to reduce the possibility of picking up noise in the peripheral portion caused by the curvature of the eye or the like. The measurement area is not limited to a circular area, and a rectangular area, a grid area, a chart area, and the like may be designated. The chart area is, for example, an area of a chart of an arbitrary shape superimposed on the image, and the examiner may change the shape or position of the measurement area by specifying the shape or position of the chart.

  The OCT data analysis program may be executed by the processor of the analysis device. The OCT data analysis program includes, for example, an analysis step and a display control step. The analysis step is, for example, a step of acquiring evaluation information of a subject by analyzing OCT data. The display control step is a step of causing the display unit to display the distribution amount of the display information in the subject.

Second Embodiment
The second embodiment will be described. The OCT data analysis apparatus (for example, the OCT data analysis apparatus 1) of the second embodiment analyzes OCT data of a subject acquired by an OCT optical system (for example, the OCT optical system 100). The OCT optical system is, for example, an optical system that detects interference light of the reflected light of the measurement light irradiated to the object and the reference light corresponding to the measurement light. The OCT data is, for example, data obtained from the detection result of the interference light. For example, OCT data includes an OCT signal, tomographic image data, motion contrast data, motion contrast image data, and the like.

  The OCT data analysis device (abbreviated as analysis device) includes an analysis unit (for example, control unit 70) and a display control unit (for example, control unit 70). The analysis unit identifies, for example, the first foveal avascular region and the second foveal avascular region different from the first foveal avascular region by analyzing OCT data. The display control unit causes the display unit to compare and display the first foveal avascular region and the second foveal avascular region. According to the above-described configuration, the analysis device of the second embodiment can be displayed so that data of a plurality of different foveolar avascular regions different from one another can be easily compared. The display control unit displays a first pattern (for example, FAZ601, FAZ606, etc.) indicating a first foveal avascular region and a second pattern (for example, FAZ602, FAZ608, etc.) indicating a second foveal avascular region. It may be displayed on the screen. Of course, the data of the fovea avascular region is not limited to two, and three or more data may be compared and displayed on the display unit.

  The analysis unit identifies the first foveal avascular region by analyzing the first slab of the OCT data, and identifies the second foveal avascular region by analyzing the second slab of the OCT data. It is also good. In this case, the display control unit may superimpose and display the first foveal avascular region based on the OCT data of the first slab and the second foveal avascular region based on the OCT data of the second slab. This allows the examiner to easily compare multiple foveal avascular regions extracted in different slabs. The slab is, for example, a layer region at a certain depth position of the OCT data. For example, slabs are separated by segmentation processing on OCT data. Of course, the slab may be set manually by the examiner.

  The analysis unit identifies the first foveal avascular region by analyzing the OCT data of the right eye of the subject, and analyzes the OCT data of the left eye of the subject to obtain the second foveal absence. The vascular region may be identified. In this case, the display control unit causes the display unit to superimpose a first foveal avascular region based on OCT data of the right eye and a second foveal avascular region based on OCT data for the left eye. By this, it is possible to easily compare the foveal avascular regions of the left and right subject eyes and to confirm whether the fovea avascular regions of the left and right eyes are symmetrical or not.

  The analysis unit identifies the first foveal avascular region by analyzing the OCT data of the eye to be examined acquired at the first date and time by the OCT optical system, and the second different from the first date and time by the OCT optical system. The second foveal avascular region may be identified by analyzing the OCT data of the subject eye acquired at the date and time. In this case, the display control unit superimposes the first foveal avascular region based on the OCT data acquired at the first date and the second avascular region based on the OCT data acquired at the second date on the display unit. Let This makes it easy to confirm the temporal change of the subject's eye. Of course, foveal avascular regions extracted from three or more OCT data acquired at different times and dates may be compared.

  The display control unit may cause the display unit to superimpose and display the first foveal avascular region and the second fovea avascular region. This makes it easy to compare the shape or size of the first foveal avascular region with the second foveal avascular region. Of course, the display control unit may cause the display unit to display the first foveal avascular region and the second fovea avascular region in parallel.

  The display control unit may display the first foveal avascular region in the first display color and display the second foveal avascular region in the second display color different from the first display color. This makes it possible to clearly display the differences in the plurality of foveal avascular regions. In addition, the display control unit may cause the overlapping portion of the first foveal avascular region and the second foveal anovascular region to be displayed in a third display color different from the first display color and the second display color. . For example, the third display color may be a mixed color of the first display color and the second display color. By this, it is possible to easily grasp how much the first foveal avascular region and the second foveal avascular region overlap with each other.

  The analysis unit may acquire a first analysis parameter related to the first foveal avascular region, and acquire a second analysis parameter related to the second foveal avascular region. In this case, the display control unit may cause the display unit to display the first analysis parameter and the second analysis parameter. This makes it possible to easily identify differences in multiple foveal avascular regions. The analysis parameters are, for example, the area of the fovea avascular region, circumferential length, circularity, axial ratio and the like. The parameters such as the area may be numerical values in consideration of the axial length correction amount.

  The analysis unit may calculate a difference or a ratio between the first analysis parameter and the second analysis parameter. In this case, the display control unit may display the difference or the ratio on the display unit. This makes it possible to easily identify differences in multiple foveal avascular regions.

  The display control unit displays on the display unit at least one of a first chart of a size corresponding to the first foveal avascular region and a second chart of a size corresponding to a second foveal avascular region. You may The first chart is, for example, a reference for evaluating the first foveal avascular region. The second chart is, for example, a reference for evaluating the second foveal avascular region. By displaying at least one of the first chart and the second chart on the display unit, the examiner can confirm the size of the foveolar avascular region based on the size of the chart. For example, each foveal avascular region is evaluated by comparing the first pattern indicating the first foveal avascular region or the second pattern indicating the second foveal anovascular region with the first chart or the second chart. can do. In addition, as a shape of a chart, arbitrary shapes, such as a circle | round | yen, an ellipse, a rectangle, a short diameter, convex hull, may be sufficient, for example.

  The display control unit may display the first chart with the smallest size including the first foveal avascular region, and may display the second chart with the smallest size including the second foveal avascular region. Good. This allows the examiner to easily confirm the size of the foveal avascular region by the size of the chart.

  The display control unit may set the size of the first chart according to the depth position of the first slab, and may set the size of the second chart according to the depth position of the second slab. By this, the examiner can grasp the size of the fovea avascular region suitable for each layer by the size of the chart.

  The display control unit may set the sizes of the first chart and the second chart on the basis of the size of the foveal avascular region of the normal eye, or the size of the foveal avascular region of the diseased eye. The sizes of the first chart and the second chart may be set based on By this, the examiner can easily confirm the difference in size of the foveal avascular region between the eye to be examined and the normal eye.

  The analysis unit identifies the first foveal avascular region by analyzing the OCT data of the eye to be examined acquired at the first date and time by the OCT optical system, and acquires the same day as the first date and time by the OCT optical system. The second foveal avascular region may be identified by analyzing OCT data of the subject eye to be examined. The OCT data may be obtained by one measurement.

  Note that the analysis unit may cause the display unit to display a chart of a size corresponding to one of the fovea avascular regions identified by analyzing the OCT data. This allows the examiner to confirm whether the foveal avascular region of the eye to be examined is normal based on the size of the chart.

  The processor (for example, the control unit 70) of the OCT data analysis apparatus may execute the OCT data analysis program stored in the storage unit (for example, the storage unit 74). The OCT data analysis program includes, for example, an analysis step and a display control step. The analysis step is a step of identifying the first foveal avascular region and the second foveal avascular region different from the first foveal avascular region by analyzing the OCT data. The display control step is, for example, a step of causing the display unit to superimpose and display the first foveal avascular region and the second fovea avascular region.

First Embodiment
An OCT data analysis apparatus according to a first embodiment will be described with reference to the drawings. An OCT data analysis apparatus (abbreviated as an analysis apparatus) 1 shown in FIG. 1 analyzes and processes OCT data acquired by the OCT device 10.

  The analysis device 1 includes, for example, a control unit 70. The control unit 70 is, for example, a general central processing unit (CPU) 71, a ROM 72, a RAM 73, and the like. The ROM 72 stores, for example, an analysis processing program for analyzing OCT data, an initial value, and the like. The RAM 73 temporarily stores various information, for example.

  As shown in FIG. 1, for example, a storage unit (for example, 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 the supply of power is shut off. For example, a hard disk drive, a removable USB memory, or the like can be used as the storage unit 74.

  Various operation instructions by the examiner are input to the operation unit 76. The operation unit 76 outputs a signal corresponding to the input operation instruction to the control unit 70. For the operation unit 76, for example, at least one of user interfaces 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 acquired by the OCT device 10, motion contrast data, and the like.

  Note that, for example, an OCT device 10 is connected to the analysis apparatus 1 of the first embodiment. The OCT analysis apparatus 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 motion contrast data acquired by the OCT device 10 via a storage medium.

<OCT device>
Hereinafter, the outline of the OCT device 10 will be described based on FIG. For example, the OCT device 10 applies measurement light to the eye to be examined E, and acquires an 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 emits measurement light to the eye E 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. For a detailed configuration of the OCT optical system, see, for example, Japanese Patent Application Laid-Open No. 2015-131107.

  The OCT optical system 100 is an optical system of so-called optical coherence tomography (OCT). The OCT optical system 100 divides the light emitted from the measurement light source 102 into a measurement light (sample light) and a 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 oculi Ef of the eye E via the measurement optical system 106. After that, the detector 120 is made to receive the interference light by the combination of the measurement light reflected by the eye to be examined 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 XY direction (cross direction) on the fundus. For example, the control unit 70 controls the operation of the scanning unit 108 based on the set scanning position information, and acquires an OCT signal based on the light reception signal detected by the detector 120. The reference optical system 110 generates reference light that is combined with the reflected light acquired by the 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 spectral intensity of the interference light is detected by the detector 120, and a depth profile (A scan signal) in a predetermined range is acquired by Fourier transformation on the spectral intensity data.

  In addition, 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 shooting optical system
For example, the front photographing optical system 200 photographs the fundus Ef of the eye to be examined E from the front direction (for example, the optical axis direction of the measurement light), and obtains a front image of the fundus Ef. The front photographing optical system 200 may be, for example, an apparatus configuration of a scanning laser ophthalmoscope (SLO) (see, for example, JP-A-2015-66242) or a so-called fundus camera type configuration. (Refer to Japanese Patent Application Laid-Open No. 2011-10944). In addition, as the front imaging optical system 200, the OCT optical system 100 may be shared, and a front image may be acquired based on a detection signal from the detector 120.

<Fixation target projection part>
The fixation target projection unit 300 has an optical system for guiding the viewing direction 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 has a visible light source that emits visible light, and changes the presentation position of the fixation target two-dimensionally. As a result, the viewing direction is changed, and as a result, the acquisition site of the OCT signal is changed.

<Acquisition of motion contrast data>
The analysis apparatus 1 of the first embodiment may process, for example, an OCT signal detected by the OCT device 10 to acquire motion contrast data. The control unit 70 controls the drive of the scanning unit 108 to scan the measurement light in the area A1 on the fundus oculi Ef. In FIG. 3A, the z-axis direction 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 lateral 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 control unit 70 scans the measurement light in the x direction along the scanning lines SL1, SL2, ..., SLn in the region A1. Note that scanning the measurement light in a direction (for example, the x direction) intersecting the optical axis direction of the measurement light is referred to as “B scan”. Then, two-dimensional OCT data obtained by one B-scan will be described as one-frame two-dimensional OCT data. For example, the control unit 70 may two-dimensionally scan the measurement light in the xy direction, and obtain an A scan signal in the z direction at each scanning position.

  The control unit 70 may acquire motion contrast data based on the OCT data. The motion contrast may be, for example, information capturing the blood flow of the eye to be examined, changes in retinal tissue, and the like. When acquiring motion contrast data, the control unit 70 acquires at least two OCT signals that are temporally different with respect to the same position of the eye to be examined. For example, in each scanning line, the control unit 70 performs a plurality of times of B-scans with different times, and acquires a plurality of OCT signals with different times.

  For example, FIG. 3B shows an OCT signal acquired in the case where a plurality of B-scans with different times are performed on the scan lines SL1, SL2,. For example, in FIG. 3B, scan line SL1 is scanned at times T11, T12,..., T1N, scan line SL2 is scanned at times T21, T22,. It shows the case of scanning with Tn1, Tn2, ..., TnN. For example, the control unit 70 acquires a plurality of OCT data different in time in each scanning line, and stores the OCT data in the storage unit 74.

  As described above, when acquiring a plurality of OCT signals temporally different with respect to the same position as described above, the controller 70 processes the OCT signals to acquire motion contrast data. As a method of calculating an OCT signal for acquiring motion contrast, for example, a method of calculating an intensity difference of a complex OCT signal, a method of calculating a phase difference of a complex OCT signal, a method of calculating a vector difference of a complex OCT signal, The method of multiplying the phase difference and vector difference of the complex OCT signal, the method of using the correlation of the signal (correlation mapping), etc. may be mentioned. In addition, please refer to, for example, JP-A-2015-131107 as one of the calculation methods.

  The control unit 70 may acquire three-dimensional motion contrast data of the eye E by arranging motion contrast data in different scan lines. As described above, the motion contrast data is not limited to the phase difference, and an intensity difference, a vector difference, or the like may be acquired.

  FIG. 4 shows an example of motion contrast data (hereinafter, MC data) 402. FIGS. 4A and 4B show MC front image data (also referred to as MC face image data) 403. The MC front image data 403 is acquired, for example, by extracting three-dimensional MC data for at least a partial region in the depth direction (see, for example, Japanese Patent Application No. 2015-121574). For example, the MC front image data 403 may be generated by an integrated value or a maximum value in the depth direction in the MC data 402. Of course, one-dimensional MC data, two-dimensional MC data, or three-dimensional MC data may be displayed as the MC data 402.

Analysis processing of motion contrast data
An example of analysis processing of the MC data 402 acquired as described above will be described. The control unit 70 performs analysis processing on the MC data 402 to obtain at least one analysis value (evaluation information). As an example, the case where the blood vessel area of the eye to be examined is extracted by analysis processing on the MC data 402 will be described.

<Blood vessel extraction processing>
The control unit 70 extracts a blood vessel by analyzing the MC data 402. For example, the control unit 70 performs a discrimination process between a blood vessel region and a non-blood vessel region by image processing of the MC data 402. For example, the control unit 70 extracts a blood vessel region by discrimination processing. Of course, the non-blood vessel region may be extracted by discrimination processing.

  For example, threshold processing is used as the determination processing. For example, the control unit 70 may set a pixel satisfying the threshold as a blood vessel region, and determine a pixel not satisfying the threshold as a non-blood vessel region. The threshold itself may be set arbitrarily by the examiner, or may be predetermined as a fixed value. In addition, the threshold may be set through an image analysis process on the MC data 402.

  When the discrimination process between the blood vessel area and the non-blood vessel area is automatically performed, the control unit 70 applies the binarization process (for example, the discriminant analysis method) from the luminance value of the MC data 402 to A non-vascular region may be defined.

<Calculation of blood vessel density>
The control unit 70 calculates the blood vessel density for each local region based on the result of the determination process. For example, the control unit 70 calculates the blood vessel density by determining the proportion of blood vessels in a predetermined area centered on each pixel position. The blood vessel density may be calculated from two-dimensional data or three-dimensional data.

  FIG. 5 is an analysis map of blood vessel density. The analysis map 404 shows, for example, a two-dimensional distribution of blood vessel density. The analysis map 404 is a color map that is color-coded according to the blood vessel density. In the example of FIGS. 5A and 5B, the analysis map 404 is displayed superimposed on the MC front image data 403. Note that the image on which the analysis map is superimposed may be, for example, a front image captured by the front imaging optical system 200, or OCT front image data (also referred to as OCT face image data) generated from OCT three-dimensional data. It may be In the case of three-dimensional OCT data, it may be three-dimensional OCT data that is the basis of three-dimensional motion contrast data. As shown in FIG. 5, in the conventional analysis map 404, low density areas or high density areas are easily visible, but the obtained information does not differ much from the original MC front image data 403. Therefore, in the first embodiment, the information of the object is displayed in an easy-to-understand manner by measuring the distribution amount of the analysis value (for example, blood vessel density).

<Distributed amount measurement>
The distribution amount measurement of the analysis value will be described. The control unit 70 measures, for example, the distribution amount of the blood vessel density of the subject. For example, the control unit 70 divides the blood vessel density of the subject acquired by the MC data 402 into a plurality of classes (bins), and measures the frequency thereof. For example, the control unit 70 determines which class the numerical value belongs to in the blood vessel density of each pixel, and measures the number of pixels. The measurement area for measuring the distribution amount may be two-dimensional MC data or three-dimensional MC data. FIG. 6 is a histogram 501 in which the vertical axis represents frequency and the horizontal axis represents bar. The control unit 70 divides the density into 10 classes of 0 to 9%, 10 to 19%,..., 90 to 100% in the plurality of examples in FIG. Of course, classification of classes is not limited to this. For example, the bin width may be set to 20, and the classes may be divided into five stages of 1 to 19%, 20 to 39%, ..., 80 to 100%.

  For example, as shown in FIG. 7, the control unit 70 displays the frequencies of each class in a stacked bar graph. FIG. 7A shows an analysis map 404 of blood vessel density of normal eyes and a stacked bar graph 502 of distribution amounts, and FIG. 7B shows an analysis map 404 of blood vessel density of diseased eyes and a stacked bar graph 502 of distribution amounts. In the analysis map 404, it is necessary to look over the entire map image, but in the case of a stacked bar graph, it is possible to easily confirm whether the non-vascular area is large or small by simply confirming the graph. Of course, the control unit 70 may generate one stacked bar graph for the entire image, or may generate a stacked bar graph for each of a plurality of divided areas. For example, a stacked bar graph may be generated in each area divided into 3 × 3 blocks in the MC data 402. The amount of density distribution is different from the average density, and the scattered avascular regions are not averaged out and thus are useful for data including scattered avascular regions.

<Comparison display and follow up observation>
The control unit 70 may compare and display the distribution amounts of analysis values of a plurality of OCT data. For example, the control unit 70 may compare distribution amounts of analysis values in OCT data measured on different dates and times for the same subject. For example, as shown in FIG. 8, MC data 402 for 3 days taken at different dates and times are analyzed, and the obtained distribution amounts of blood vessel density are displayed on the screen of the display unit 75 as a plurality of stacked bar graphs 503a, 503b and 503c. It may be displayed side by side. By this, the analysis apparatus 1 can provide information suitable for follow-up observation of the eye to be examined. The examiner can easily grasp temporal changes of the subject by confirming the plurality of stacked bar graphs 503a, 503b, and 503c at different dates and times displayed in comparison.

<Normal eye comparison>
Further, the control unit 70 may compare and display the distribution amounts of analysis values of different subjects on the display unit 75. For example, the control unit 70 may compare and display the distribution amount of the analysis value of the eye of the target subject and the distribution amount of the analysis value of the normal eye. For example, as shown in FIG. 9, a stacked bar graph 504a indicating the blood vessel density distribution amount of the target eye and a stacked bar graph 504b indicating the blood vessel density distribution amount of the normal eye stored in the storage unit 74 may be displayed. This allows the examiner to easily compare the condition of the target eye with that of the normal eye.

<Left and right eye comparison>
In addition, the control unit 70 may compare and display left and right eyes. For example, the control unit 70 may measure the distribution amount of the analysis value of the right eye of the subject and the distribution amount of the analysis value of the left eye, and display the results side by side on the display unit 75. This allows the examiner to easily compare the information of the left and right subject eyes.

<Setting of distribution amount measurement area>
Note that the examiner may arbitrarily designate the measurement region of the distribution amount. For example, the control unit 70 may receive an operation signal from the operation unit 76, and specify the position of the distribution amount measurement area on the MC data. For example, the peripheral portion of the MC data 402 often contains unnecessary components. In the case of an eye with a long eye length or the like, the curvature of the eye is large, and thus, when imaging is performed in a wide angle range, the underlying OCT data itself is lost. Also, the eye may move at the end of the data (e.g. towards the end of the imaging) and the underlying OCT data may be missing. Therefore, the control unit 70 may measure the distribution amount of the blood vessel density in a part of designated areas. For example, the control unit 70 may measure the distribution amount of the blood vessel density in a circular region designated by the examiner. By this, it is possible to prevent the noise in the peripheral part of the MC data 402 from being measured. Of course, the measurement area may be specified not only in a circular shape but also in a shape such as an ellipse or a rectangle. Also, the measurement area may be designated by a chart of arbitrary shape, a grid or the like.

  Further, the range (size) of the measurement area of the distribution amount may be arbitrarily designated by the examiner. The range of the measurement area may be set according to the acquisition area of the 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, ranges may be set for the macular site and the papillary site, respectively.

  The setting according to the acquisition area may be set according to different acquisition areas in the depth direction of the fundus. For example, ranges may be set for different blood vessel layers. Of course, the range is not limited to the blood vessel layer, but may be set for different retinal layers (or choroidal layers).

<Exclusion of foveal avascular region (FAZ)>
The control unit 70 may detect (specify) the foveal avascular region (FAZ) of the eye to be examined by analysis processing on the MC data 402, and may exclude the region from the distribution amount measurement region. By this, it is possible to make the avascular region other than FAZ conspicuous. In this case, the MC data 402 is subjected to analysis processing for extracting an avascular analysis region.

  Since FAZ is an avascular region and has a low luminance value, for example, FAZ is extracted by determining the luminance and connectivity around the central portion based on the seed point set in the central portion of FAZ. . Note that as a method of extraction processing, for example, other than extraction processing based on graph theory, there are extraction by an area expansion method, extraction by an active contour model such as Snake, Level Set, and the like. Alternatively, the method described in Kim, et al., “Non-Invasive Imaging of the Foveal Avascular Zone with High-Speed, Phase-Variance Optical Coherence Tomography”, January 2012 may be used.

  In the above embodiments, the blood vessel density is mainly described as an analysis value (evaluation information), but the present invention is not limited to this. For example, the analysis value may be obtained by analyzing OCT data. For example, the analysis value may be the blood vessel diameter of the subject, the blood vessel bifurcation density, the blood flow rate, or the layer thickness of each layer of the fundus obtained by analysis of the tomographic image. Here, the blood vessel branch density is, for example, the number of blood vessel branches per unit area (or unit volume). The vascular bifurcation is extracted, for example, based on the blood vessel shape extracted from the MC data 402. Also in these analysis values, by displaying the distribution amount as in the above embodiment, the quality of the analysis result can be easily understood.

  In addition, in the above-mentioned Example, in the display of distribution amount, although the stacked bar graph was mainly demonstrated, it does not restrict to this. For example, the display of the distribution amount may be a bar graph such as a histogram, a circle graph, or a graph such as a cumulative distribution function (cumulative density function).

  In addition, the said analysis is not limited to a blood vessel, It is applicable to vascular analysis (for example, lymphatics) as a vascular analysis area | region.

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

Second Embodiment
A second embodiment will be described. The OCT data analysis apparatus of the second embodiment performs analysis processing different from that of the first embodiment. The configuration of the second embodiment is the same as the configuration of the first embodiment, so the same reference numerals are given and the description is omitted.

<Overlay display of foveal avascular region>
The analysis process of the second embodiment will be described. The control unit 70 extracts the foveal avascular region (FAZ) for each of the different slabs. The slab is, for example, a layer region at a certain depth position in OCT data. For example, in the MC data 402 as shown in FIG. 10, the control unit 70 extracts FAZ in the slab of the retina surface layer D1 and the retina deep layer D2. The method of extracting FAZ is the same as in the first embodiment. The control unit 70 may separate the slabs by segmentation processing on the MC data 402, or may separate the slabs based on an input from the operation unit 76 of the examiner. The control unit 70 may automatically select a slab from which the FAZ is to be extracted, or may select based on an input from the operation unit. FIG. 11A shows FAZ 601 extracted in OCT data of the retina surface layer D1. FIG. 11 (b) shows the FAZ 602 extracted in OCT data in the deep retina D2.

  The control unit 70 superimposes (displays) the FAZs 601 and 602 extracted in each layer and displays them. At this time, as shown in FIG. 11C, the control unit 70 may cause the FAZ of each layer to be displayed in different colors. By this, the control unit 70 can display the difference in the shape or size of the FAZ detected from different slabs in an easy-to-understand manner to the examiner. The control unit 70 may display the overlapping portion 603 of each FAZ in a color different from the FAZ of each layer. For example, the control unit 70 may display the overlapping portion 603 in a mixed color of the color of each layer. This makes it easy to grasp which is the FAZ of each layer or the overlapping portion.

<Parameter comparison of foveal avascular region>
Further, the control unit 70 may cause the display unit 75 to display various parameters related to FAZ extracted in each layer. For example, the control unit 70 displays various parameters of the FAZ 601 of the retina surface layer D1 and the FAZ 602 of the retina deep layer D2. For example, as shown in FIG. 12, the control unit 70 may display various parameters as a table. The parameters are, for example, the area of FAZ, circumferential length, circularity, axial ratio, angle of ellipse, eccentricity and the like. The degree of circularity is a numerical value representing the complexity of a figure, and is, for example, a numerical value that decreases as the figure becomes more complex, with a perfect circle of 1. For example, it can be determined as circularity = 4π × (area) ^ (perimeter) ^ 2. The axial ratio is, for example, the ratio of the minor axis to the major axis when the shape of the FAZ is elliptically approximated.

  The control unit 70 may calculate the ratio or difference of various parameters in each layer and cause the display unit 75 to display the ratio as a numerical value. This enables the examiner to easily confirm the difference in the FAZ parameters of each layer. In addition, for example, the control unit 70 may set a threshold of the difference in advance, and notify the examiner if the difference is large. For example, in the example of FIG. 12, the control unit 70 causes the alert 605 to be displayed because the difference in circularity is larger than the threshold. The difference threshold may be set on the basis of the difference between the parameters of each layer in the normal eye. Of course, the threshold value based on the parameter of normal eye may be set also for the individual parameter of each layer. As another example of the parameter, the center of gravity of FAZ (a parameter indicating whether FAZ is expanded in the vertical or horizontal direction), the inclination of an elliptical axis (short diameter, long diameter, etc.) may be used. Also, as the ratio of FAZ of each layer, an area ratio, a diameter ratio (for example, a vertical diameter ratio or a horizontal diameter ratio), or the like may be used.

<Chart display including foveal avascular region>
It is known that the shape of FAZ is circular if it is a normal eye, and if it is a diseased eye, it becomes a unique shape due to the deformation of the retina shape. Therefore, the control unit 70 may display the smallest circular chart surrounding the FAZ detected from each layer. For example, FIG. 13 (a) shows an image in which the smallest circular chart 607 surrounding the FAZ 606 in the deep retina D2 of a normal eye is displayed. FIG. 13B shows an image in which the smallest circular chart 609 surrounding the FAZ 608 in the deep retina D2 of the diseased eye is displayed.

  Since the FAZ 606 of the normal eye is circular, the ratio of the FAZ 606 to the inside of the circular chart 607 is large. On the other hand, since the FAZ 608 of the diseased eye has a unique shape, the proportion of the FAZ 608 occupying the inside of the circular chart 609 decreases. Therefore, the examiner may determine the possibility that the subject's eye is ill by confirming the proportion of FAZ in the circular chart. Further, since the FAZ 608 of the diseased eye is larger than the FAZ 607 of the normal eye, the examiner may confirm the magnitude relation of the FAZ by the size of the circular chart, and may use it to determine the presence or absence of the disease.

  Note that, as shown in FIG. 14, the control unit 70 may superimpose and display the FAZs 601 and 602 of each layer and the charts 612 and 613 corresponding to the FAZ. This makes it easy to compare the size of each FAZ with each chart. The control unit 70 may compare and display only the charts. The shape of the chart is not limited to a circle, but may be any shape such as an ellipse, a rectangle, a major axis, a minor axis, or a convex hull.

<Size of chart>
The control unit 70 may display a chart of a preset size together with the FAZ. The examiner may determine the possibility that the eye to be examined is ill by comparing the size of the FAZ of the eye to be examined with a chart of a predetermined size. For example, FIG. 15A shows an example in which a chart 610 of a predetermined size is displayed on the FAZ 606 of a normal eye. FIG. 15B is an example in which a chart 610 of a predetermined size is displayed on the FAZ 608 of the diseased eye. The FAZ 606 for normal eyes fits inside the chart 610 while the FAZ 608 for diseased eyes protrudes outside the chart 610. Thus, the examiner can examine the possibility of disease by comparing the size of the chart with the size of the FAZ. The size of the chart 610 may be set based on the size of a standard FAZ of a normal eye. For example, the control unit 70 may set the size of the chart 610 based on information of a normal eye database created by collecting OCT data of normal eyes.

  The control unit 70 may display charts of a plurality of sizes together with the FAZ. For example, as illustrated in FIG. 16, the control unit 70 may display circular charts 611 of three concentric circles. In this case, for example, the examiner may confirm the progress of the disease depending on which circle of the concentric chart the FAZ falls within.

<Normal eye comparison, right and left eye comparison, follow up>
The control unit 70 may, for example, compare the FAZ of the subject's eye with the FAZ of the normal eye. For example, the control unit 70 may superimpose the FAZ data of the normal eye stored in the storage unit 74 or the like on the FAZ of the subject eye. This allows the examiner to easily confirm the state of the subject's eye with respect to the normal eye. Further, the control unit 70 may superimpose and display the FAZ of the right eye and the left eye of the subject. This makes it easy for the examiner to compare the symmetry of the left and right eyes, and can obtain useful information for disease detection. Further, the control unit 70 may superimpose and display the FAZ of the same subject photographed at different dates and times. By this, it is possible to easily confirm the progress of the disease of the subject. In addition, when superimposing different FAZ, the control part 70 may be made to also superimpose a chart. Of course, the control unit 70 may compare and display only the charts. In addition, when superimposing data of different FAZs, the control unit 70 may perform alignment, for example, based on the center or the center of gravity of the fovea centralis. In the case of the same eye to be examined, alignment may be performed on the basis of the fundus oculi (entire image).

  As described above, the OCT data analysis apparatus 1 according to the second embodiment easily displays differences in the shape or size of the FAZ of each area by displaying the FAZ extracted in different areas of the OCT data in a superimposed manner. It can be compared. This allows the examiner to easily compare different FAZs.

  In diabetic retinopathy without macular edema, it has been reported that vascular density loss in the surface and deep layers is significantly correlated with visual loss, and in particular, enlargement of FAZ in the deep layer is more correlated with visual loss than in the surface. . For example, in the case of a normal eye, as shown in FIGS. 17 (a) and 17 (b), there is no significant difference in shape between the surface and deep layers of the retina, but as the disease develops, the symmetry of the shape It collapses (Fig. 17 (c), (d)). As described above, by comparing and displaying FAZs of different slabs (for example, the surface layer of the retina and the deep layer of the retina, etc.), it is possible to show the change of the FAZ of each layer to the examiner in an easy-to-understand manner, and screening using OCT-Angiography The availability of the function can be improved.

  The control unit 70 may arrange and display the analysis results of the FAZ of each layer on the display unit 75, as shown in FIG. Further, as shown in FIG. 17, the control unit 70 may display the analysis results of the FAZ of the eye to be examined and the normal eye side by side on the display unit 75.

1 OCT Data Analysis Device 10 OCT Device 70 Control Unit 75 Display Unit 402 MC Data

Claims (21)

An OCT data analyzer for analyzing OCT data of a subject acquired by an OCT optical system, comprising:
Analysis means for acquiring evaluation information of the subject by analyzing the OCT data;
Display control means for displaying on the display means the distribution amount of the evaluation information;
An OCT data analysis apparatus comprising: The analysis means acquires first evaluation information by analyzing the first OCT data, and acquires second evaluation information by analyzing the second OCT data different from the first OCT data.
The display control means is characterized in that a first distribution amount which is a distribution amount of the first evaluation information and a second distribution amount which is a distribution amount of the second evaluation information are displayed side by side on the screen of the display means. The OCT data analysis device according to claim 1. The first OCT data is OCT data of the subject acquired at a first date and time by the OCT optical system,
The second OCT data is OCT data of the subject acquired at a second date and time different from the first date and time by the OCT optical system,
The analysis means acquires the first evaluation information by analyzing the first OCT data acquired at the first date and time, and analyzes the second OCT data acquired at the second date and time. 2 get evaluation information,
The display control means causes the screen of the display means to display the first distribution amount of the first evaluation information and the second distribution amount of the second evaluation information in time series. Item 2. The OCT data analysis device of item 2. The first OCT data is OCT data of a first subject,
The second OCT data is OCT data of a second subject different from the first subject,
The analysis means acquires the first evaluation information by analyzing the first OCT data of the first subject and the second evaluation by analyzing the second OCT data of the second subject. Get information
The display control means may display the first distribution amount of the first evaluation information and the second distribution amount of the second evaluation information on the screen of the display means. OCT data analyzer.   The OCT data analysis device according to claim 4, wherein the second OCT data is OCT data of a plurality of subjects different from the first subject.   The OCT data analyzer according to claim 4 or 5, wherein the second OCT data is OCT data of a normal eye. The first OCT data is OCT data of the right eye of the subject,
The second OCT data is OCT data of the left eye of the subject,
The analysis means acquires the first evaluation information by analyzing the first OCT data of the right eye, and acquires the second evaluation information by analyzing the second OCT data of the left eye.
The display control means may display the first distribution amount of the first evaluation information and the second distribution amount of the second evaluation information on the screen of the display means. OCT data analyzer.   The OCT data analysis apparatus according to any one of claims 1 to 7, wherein the display control means displays a histogram of the evaluation information.   The OCT data analysis device according to any one of claims 1 to 7, wherein the display control means displays a stacked bar graph of the evaluation information.   The OCT data analysis apparatus according to any one of claims 1 to 7, wherein the display control means displays a bar graph of the evaluation information.   The OCT data analysis apparatus according to any one of claims 1 to 7, wherein the display control means displays a circle graph of the evaluation information.   The OCT data analysis apparatus according to any one of claims 1 to 7, wherein the display control means displays a numerical value of the evaluation information.   The OCT data analysis apparatus according to any one of claims 1 to 12, wherein the evaluation information is a blood vessel density of the subject.   The OCT data analysis apparatus according to any one of claims 1 to 12, wherein the evaluation information is a blood vessel diameter of the subject.   The OCT data analysis apparatus according to any one of claims 1 to 12, wherein the evaluation information is a blood vessel branch density of the subject.   The OCT data analysis apparatus according to any one of claims 1 to 12, wherein the evaluation information is a blood flow of the subject.   The OCT data analysis apparatus according to any one of claims 1 to 12, wherein the evaluation information is a thickness of a retinal layer of an eye to be examined.   The OCT data analysis apparatus according to any one of claims 1 to 17, wherein the display control means displays the distribution amount in a measurement area specified in the subject.   The OCT data analysis apparatus according to claim 18, wherein the measurement area is an area excluding a fovea of an eye to be examined.   The OCT data analysis apparatus according to any one of claims 1 to 17, wherein the display control means displays the distribution amount in a measurement area designated in the subject. An OCT data analysis program executed by an OCT data analysis apparatus for analyzing OCT data of a subject acquired by an OCT optical system, the program being executed by a processor of the OCT data analysis apparatus,
An analysis step of acquiring evaluation information of the subject by analyzing the OCT data;
A display control step of displaying on a display means a distribution amount of the evaluation information in the subject;
A program for causing an OCT data analysis device to execute the program.