JP2019217389A - Image generation apparatus, image generation method, and program - Google Patents

Abstract

To highly accurately create an image of a blood vessel.SOLUTION: An image generation apparatus includes: acquisition means for acquiring a plurality of tomographic data each representing a section at a substantially same portion of a subject; calculation means for calculating a motion contrast value on the basis of the plurality of tomographic data and a comparison result between a representative value of the plurality of tomographic data representing signal intensity and a threshold; a generation means for generating a motion contrast image on the basis of the motion contrast value; and change means for changing the threshold.SELECTED DRAWING: Figure 1

Description

  The disclosed technology relates to an image generation device, an image generation method, and a program.

  Optical coherence tomography (hereinafter referred to as OCT) has been put to practical use as a method for acquiring a tomographic image of a measurement target such as a living body in a non-destructive and non-invasive manner. OCT is widely used, especially in ophthalmic diagnosis.

  In OCT, a light reflected from a measurement target and light reflected from a reference mirror interfere with each other, and the intensity of the interference light is analyzed to obtain a tomographic image of the measurement target. As such an optical coherence tomographic image acquisition apparatus, a time domain OCT that obtains depth information of a measurement target by changing a position of a reference mirror, a spectral domain that disperses interference light, and replaces the depth information with frequency information and obtains the information. OCT (SD-OCT: Spectral Domain Optical Coherence Tomography), wavelength-swept optical coherence tomography (SS-OCT: Swept Source Optical Coherence Tomography, which is known in the art). Note that SD-OCT and SS-OCT are also collectively referred to as (FD-OCT: Fourier Domain Optical Coherence Tomography).

  In recent years, an angiography method using this FD-OCT has been proposed, and this angiographic method is called OCT angiography. An OCT angiography for imaging a motion contrast feature using a variation in logarithmic intensity of an interference signal as a motion contrast feature is known (Patent Document 1).

  In the method described in Patent Literature 1, a value 10 dB above the average value of the noise floor is set as a threshold, and this threshold is compared with the intensity of the interference signal, and the motion contrast feature amount corresponding to the interference signal intensity below the threshold is set to 0. I have to.

US Patent Application Publication No. 2014/21827

  However, in a tomographic image obtained by actual OCT, the signal intensity of noise or the signal intensity of a blood vessel differs depending on the position or layer in the depth direction of the retina. Therefore, when the threshold value is fixed as in Patent Literature 1, noise may be regarded as a blood vessel and blood vessels may be regarded as noise depending on the position or layer in the depth direction of the retina. That is, there is a possibility that the blood vessel cannot be accurately imaged by the conventional technique.

  The disclosed technology has been made in view of the above-described problem, and has as one object to accurately image a blood vessel.

It is to be noted that the present invention is not limited to the above-described object, and it is an operation effect derived from each configuration shown in the embodiment for carrying out the invention described later, and it is also possible to obtain an operation effect that cannot be obtained by the conventional technology. It can be positioned as one.

  An image generation apparatus according to an embodiment of the present disclosure includes an acquisition unit configured to scan a plurality of substantially the same position of a subject with measurement light to acquire a plurality of tomographic image data each representing a tomographic image of the subject, and the plurality of tomographic images. Calculating means for calculating a motion contrast value based on a comparison result between the data and the intensity of the tomographic image data and a threshold value; generating means for generating a blood vessel image based on the motion contrast value; and changing means for changing the threshold value An image generating apparatus comprising:

  According to the disclosed technology, it is possible to accurately image a blood vessel.

FIG. 1 is a diagram illustrating an example of an overall configuration of an imaging device according to an embodiment. FIG. 4 is a diagram illustrating an example of a scan pattern according to the embodiment. 7 is a flowchart illustrating an example of an interference signal acquisition procedure according to the embodiment. 5 is a flowchart illustrating an example of a signal processing procedure according to the embodiment. 5 is a flowchart illustrating details of an example of an OCT angiography image generation process according to the first embodiment. The figure which shows an example of a segmentation result. FIG. 3 is a diagram illustrating an example of an OCT angiography image according to the embodiment. FIG. 4 is a diagram illustrating an example of a display screen of a display unit 70 according to the first embodiment. 9 is a flowchart illustrating details of an example of an OCT angiography image generation process according to the second embodiment. FIG. 14 is a diagram illustrating an example of a display screen of a display unit 70 according to the second embodiment. FIG. 10 is a diagram illustrating an example of Z-direction dependence of noise characteristics of the OCT device according to the third embodiment. FIG. 14 is a diagram illustrating an example of a roll-off characteristic of the OCT device according to the fourth embodiment. The figure which shows an example of the three-dimensional volume data of a motion contrast feature-value.

  Hereinafter, an image generating apparatus according to the present embodiment will be described with reference to the accompanying drawings. Note that the configurations shown in the following embodiments are merely examples, and the present invention is not limited to the following embodiments.

(1st Embodiment)
[Configuration of entire imaging device]
Hereinafter, an example of the present embodiment will be described with reference to the drawings.
FIG. 1 is a diagram illustrating a configuration example of an imaging apparatus (OCT apparatus) using optical coherence tomography according to the present embodiment. Although the configuration in the case of the SS-OCT is shown, the same effect can be realized in an OCT apparatus of another system.

  The OCT apparatus includes a wavelength sweep light source 10, an optical signal branching / combining unit 20, an interference light detecting unit 30, a computer 40 (image generating device) for acquiring retinal information of the human eye 100, a measuring arm 50, and a reference arm 60. have. The computer 40 includes a central processing unit (CPU) and a storage device. The storage device includes, for example, a memory (RAM and ROM) and a mass storage device (HDD). Part or all of the storage device may be provided outside the computer 40. The wavelength sweep light source 10 emits light having a wavelength of 980 nm to 1100 nm at a frequency of 100 kHz (A scan rate), for example. Here, the wavelength and the frequency are merely examples, and the present invention is not limited to the above values. Similarly, in the following embodiments, the numerical values described are merely examples, and the present invention is not limited to the numerical values described.

  In the present embodiment, the subject 100 is a human eye (fundus), but is not limited thereto. For example, the subject 100 may be used for skin or the like. In the present embodiment, the imaging target is the fundus of the eye, but the anterior eye may be the imaging target.

  The optical signal branching / combining unit 20 has couplers 21 and 22. First, the coupler 21 splits the light emitted from the light source 10 into irradiation light for irradiating the fundus and reference light. The irradiation light is applied to the human eye 100 via the measurement arm 50. More specifically, the irradiation light that has entered the measurement arm 50 is emitted as spatial light from the collimator 52 after the polarization state is adjusted by the polarization controller 51. Thereafter, the irradiation light is applied to the fundus of the human eye 100 via the X-axis scanner 53, the Y-axis scanner 54, and the focus lens 55. The X-axis scanner 53 and the Y-axis scanner 54 are scanning units having a function of scanning the fundus with irradiation light. The irradiation position of the irradiation light on the fundus is changed by the scanning unit. Here, acquiring information in the depth direction (depth direction) of one point of the human eye 100 is called A-scan. Further, acquiring a two-dimensional tomographic image along a direction orthogonal to the A-scan is called a B-scan, and acquiring a two-dimensional tomographic image along a direction perpendicular to the two-dimensional tomographic image of the B-scan is called a C-scan. Called scan.

  Note that the X-axis scanner 53 and the Y-axis scanner 54 are each configured by a mirror arranged so that the rotation axes are orthogonal to each other. The X-axis scanner 53 performs scanning in the X-axis direction, and the Y-axis scanner 54 performs scanning in the Y-axis direction. Each of the X-axis direction and the Y-axis direction is a direction perpendicular to the eye axis direction of the eyeball, and is a direction perpendicular to each other. Further, the line scanning direction such as the B scan and the C scan does not need to coincide with the X axis direction or the Y axis direction. For this reason, the line scanning directions of the B scan and the C scan can be appropriately determined according to a two-dimensional tomographic image or a three-dimensional tomographic image to be captured.

  The light reflected from the fundus passes through the same path such as the focus lens 55 again, passes through the coupler 21, and enters the coupler 22. In addition, by closing the shutter 85 and performing measurement, the reflected light from the human eye 100 can be cut to measure the background (noise floor).

  On the other hand, the reference light enters the coupler 22 via the reference arm 60. More specifically, the reference light that has entered the reference arm 60 is adjusted in the polarization state by the polarization controller 61 and then emitted from the collimator 62 as spatial light. Thereafter, the reference light passes through the dispersion compensating glass 63, the optical path length adjusting optical system 64, and the dispersion adjusting prism pair 65, enters the optical fiber via the collimator lens 66, exits from the reference arm 60, and enters the coupler 22.

  In the coupler 22, the reflected light of the human eye 100 passing through the measurement arm 50 and the reference light passing through the reference arm 60 interfere. Then, the detecting unit 30 detects the interference light. The detection unit 30 has a differential detector 31 and an A / D converter 32. First, in the detection unit 30, the interference light split by the coupler 22 is detected by the differential detector 31. Then, the OCT interference signal (hereinafter, sometimes simply referred to as an interference signal) converted into an electric signal by the differential detector 31 is converted into a digital signal by the A / D converter 32. Here, sampling of the interference light of the operation detector 31 is performed at equal wave number intervals based on a k clock signal transmitted from a clock generator incorporated in the wavelength sweep light source 10. The digital signal output from the A / D converter 32 is sent to the computer 40. Next, the computer 40 processes the interference signal converted into a digital signal to calculate an OCT angiographic image. The image shown in FIG. 7 is an example of an OCT angiography image.

  The CPU of the computer 40 executes various processes. Specifically, the CPU functions as an acquisition unit 41, a positioning unit 42, a calculation unit 43, a generation unit 44, a change unit 45, and a display control unit 46 by executing a program stored in a storage device (not shown). . It should be noted that the computer 40 may have one or more CPUs and storage devices. That is, at least one or more processing devices (CPU) and at least one storage device (ROM or RAM or the like) are connected, and at least one or more processing devices execute a program stored in at least one or more storage devices. In this case, the computer 40 functions as each of the above units. The processing device is not limited to the CPU, but may be an FPGA or the like.

  The obtaining unit 41 obtains the output of the A / D converter 32. Specifically, a digital signal of interference light between the reference light and the return light of the measurement light scanned from the eye is acquired. Further, the obtaining unit 41 obtains a tomographic image by performing a Fourier transform on the digital signal of the interference light (interference signal). Specifically, the obtaining unit 41 obtains an OCT complex signal composed of a phase and an amplitude by applying a fast Fourier transform (FFT) to the interference signal. Note that the maximum entropy method may be used as the frequency analysis. Further, the acquisition unit 41 squares the absolute value of the OCT complex signal and calculates a signal intensity (Intensity), thereby acquiring a tomographic image indicating the Intensity (hereinafter, may be simply referred to as a tomographic image). This tomographic image corresponds to an example of tomographic image data indicating a tomographic image of the fundus of the subject's eye. That is, when the measurement light is scanned a plurality of times at substantially the same position on the fundus of the eye to be inspected, the acquisition unit 41 acquires a plurality of tomographic image data indicating tomographic images at substantially the same position of the subject. Note that the plurality of tomographic image data is data acquired by measurement light scanned at different timings.

  Note that the acquisition unit 41 also functions as a unit that controls the X-axis scanner 53 and the Y-axis scanner 54.

  The positioning unit 42 performs positioning of a plurality of tomographic images. In the present embodiment, the positioning unit 42 performs positioning of a plurality of tomographic images obtained by scanning substantially the same position of the fundus of the eye to be examined a plurality of times with the measurement light. More specifically, the positioning unit 42 positions the plurality of tomographic image data before the calculating unit 43 calculates the motion contrast value.

  Positioning of the tomographic image can be realized by various known methods. The positioning unit 42 performs positioning of a plurality of tomographic images so that, for example, the correlation between the tomographic images is maximized. Note that if the subject is not a moving subject like an eye, alignment is unnecessary. Even if the subject is an eye, positioning is unnecessary if tracking performance is high. That is, the positioning of the tomographic images by the positioning unit 42 is not essential.

  The calculating unit 43 calculates a motion contrast feature amount (hereinafter, may be referred to as a motion contrast value). Here, the motion contrast is a contrast between a flowing tissue (for example, blood) and a non-flowing tissue in the subject tissue, and a feature representing the motion contrast is defined as a motion contrast feature.

  The motion contrast feature amount is calculated based on a change in data between a plurality of tomographic images obtained by scanning substantially the same position a plurality of times with measurement light. For example, the calculating unit 43 calculates the variance of the signal intensities (luminances) of the plurality of aligned tomographic images as a motion contrast feature amount. More specifically, the variance of the signal intensity at each corresponding position of the plurality of aligned tomographic images is calculated as a motion contrast feature amount. For example, since the signal strength of an image corresponding to a blood vessel at a predetermined time and the signal strength of an image corresponding to a blood vessel at a time different from the predetermined time change depending on the blood flow, the variance value of the portion corresponding to the blood vessel is blood flow or the like. This value is larger than the variance value of the portion where there is no flow. That is, the motion contrast value is a value that increases as the change in the subject between the plurality of tomographic image data increases. Therefore, it is possible to express motion contrast by generating an image based on this variance value. The motion contrast feature value is not limited to a variance value, and may be any of a standard deviation, a difference value, a non-correlation value, and a correlation value. Note that the calculation unit 43 uses the variance of the signal intensity or the like, but may calculate the motion contrast feature amount using the variance of the phase or the like.

  The calculating unit 43 generates an averaged image by calculating an average value of the plurality of aligned tomographic images. The averaged image is a tomographic image in which the signal intensities of a plurality of tomographic images are averaged. This averaged image may be referred to as an intensity averaged image. The calculating unit 43 compares the signal intensity of the averaged image with a threshold. When the signal intensity at the predetermined position of the averaged image is lower than the threshold, the calculation unit 43 converts the motion contrast characteristic amount obtained based on the variance or the like corresponding to the predetermined position of the averaged image with the characteristic amount indicating a blood vessel. Use different values. For example, when the signal intensity of the averaged image is lower than the threshold value, the calculation unit 43 sets the motion contrast feature amount obtained based on the variance or the like to zero. That is, the calculating unit 43 sets the motion contrast value when the representative value indicating the signal strength is lower than the threshold value to a value lower than the motion contrast value when the representative value indicating the signal strength is higher than the threshold value. Note that the calculating unit 43 may compare the signal intensity of the averaged image with the threshold before calculating the variance of the signal intensity of the plurality of tomographic images as the motion contrast feature amount. For example, the calculating unit 43 calculates the motion contrast feature amount as 0 when the signal strength of the averaged image is lower than the threshold, and calculates the signal strength of a plurality of tomographic images when the signal strength of the averaged image is higher than the threshold. Is calculated as a motion contrast feature amount.

  Here, the fact that the feature amount is 0 indicates a black portion of the image shown in FIG. 7 and the like. It should be noted that the motion contrast feature value may be set to a value near 0 instead of completely 0. On the other hand, when the signal strength of the averaged image is higher than the threshold value, the calculating unit 43 maintains the motion contrast feature amount obtained based on the variance or the like. That is, the calculating unit 43 calculates the motion contrast value based on the plurality of tomographic image data, and calculates the motion contrast value again based on the comparison result between the representative value indicating the signal intensity and the threshold.

  Note that the signal intensity of the averaged image (the average value of the signal intensity) is used as a comparison target with the threshold value, but the representative value such as the maximum value, the minimum value, and the median value of the signal intensity at the corresponding positions of a plurality of tomographic images is used. May be used. Further, instead of comparing the signal intensities obtained from a plurality of tomographic images with a threshold value, the calculating unit 43 may compare the signal intensity of one tomographic image with the threshold value and control the motion contrast feature amount. .

  As described above, the calculation unit 43 calculates the motion contrast value based on the comparison result between the threshold value and the representative value of the plurality of tomographic image data and the plurality of tomographic image data indicating the signal intensity.

  The generating unit 44 generates an OCT angiographic image based on the motion contrast feature amount. The OCT angiography image is an image of the motion feature amount calculated by the calculation unit 43. As shown in FIG. 7, for example, as the motion contrast feature amount increases, the brightness increases, and as the motion contrast feature amount decreases, the brightness increases. This is a lowered image. In the example of FIG. 7, the portion having a high luminance is a portion corresponding to a blood vessel. The luminance may be lower as the motion contrast feature amount is larger, and may be higher as the motion contrast feature amount is lower. An OCT angiography image may be called a motion contrast image or a blood vessel image. That is, the generation unit 44 generates a motion contrast image of the subject based on the motion contrast value.

  The generating unit 44 can generate a three-dimensional OCT angiographic image when the calculating unit 43 calculates a three-dimensional motion contrast feature (three-dimensional data) from the three-dimensional tomographic image data. . The generation unit 44 can also generate a two-dimensional OCT angiographic image projected or integrated in an arbitrary depth range in the retinal direction of the three-dimensional OCT angiographic image. That is, the generation unit 44 projects or integrates a motion contrast value in a predetermined range in the depth direction of the subject in the depth direction to generate the two-dimensional motion contrast image. FIG. 7 is an example of a two-dimensional OCT angiography image.

  Further, the generation unit 44 can also generate a partial three-dimensional OCT angiography image by cutting out an arbitrary retinal depth range from the three-dimensional OCT angiography image. That is, the generation unit 44 generates a three-dimensional motion contrast image based on the motion contrast value in a predetermined range in the depth direction of the subject.

  An arbitrary depth range in the retinal direction can be set by an examiner (operator). For example, selectable layer candidates such as a layer from IS / OS to RPE and a layer from RPE to BM are displayed on the display unit 70. The inspector selects a predetermined layer from the displayed layer candidates. Then, in the layer selected by the examiner, the generating means 44 performs integration in the depth direction of the retina to generate a two-dimensional OCT angiographic image (en-face blood vessel image) or a partial three-dimensional OCT angiographic image. You may do it.

  Further, the generating unit 44 may generate an OCT angiographic image corresponding to a tomographic image from the motion contrast feature amount.

  The changing unit 45 changes a threshold value to be compared with the signal strength of the averaged image. The changing unit 45 receives a change in the threshold value via an arbitrary GUI, for example, and changes the threshold value. The slide bar 73 shown in FIG. 8 is an example of a display (GUI) for receiving a change in the threshold. That is, the changing unit 45 receives the change of the threshold via the display for receiving the change of the threshold displayed on the display unit, and changes the threshold.

  Here, the threshold value may be changed collectively as in the example shown in FIG. 8, or a GUI for receiving the change of the threshold value for each layer is provided as in a slide bar 73 shown in FIG. Changes may be made. Note that the threshold value may be a discrete value for each layer, or may be a continuous value along the depth direction by complementing the threshold value input by the inspector.

  Further, the changing unit 45 may automatically change the threshold. For example, the changing unit 45 may change the threshold value to a different value for each layer. Specifically, by lowering the threshold value for a deeper layer, it is possible to image a part that is a blood vessel but has a low signal intensity as a blood vessel. Note that the threshold value may be a discrete value for each layer, or may be a continuous value along the depth direction by complementation or the like. The method for automatically determining the threshold is not limited to the method using the depth of the layer, and the threshold can be automatically determined using a noise floor value or a roll-off characteristic described later. is there. Note that a method of setting a threshold value for each layer will be described in detail in the second and subsequent embodiments.

  The display control unit 46 causes the display unit 70 to display various information. Specifically, the display control unit 46 causes the display unit 70 to display the OCT angiography image generated by the generation unit. Further, the display control unit 46 causes the display unit 70 to display a display (GUI) for accepting the change of the threshold value. For example, the display control unit 46 causes the display unit 70 to display a slide bar 73 that is an example of a GUI that receives a change in the threshold. That is, the display control unit 46 causes the display unit to display a motion contrast image generated by the generation unit and a display for accepting a change in the threshold value.

  Further, the display control unit 46 may cause the display unit 70 to display a tomographic image indicating the intensity.

  Details of a specific signal processing procedure performed by the computer 40 will be described later in a signal processing procedure.

  The display unit 70 displays various information based on the control of the display control unit 46. The display unit 70 is, for example, a display such as a liquid crystal display. Further, the OCT angiography image obtained as a result of the above-described signal processing is displayed on the display unit 70.

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

  In OCT angiography, a time change of an interference signal due to a blood flow is measured, so that a plurality of interference signals repeatedly measured at least twice at substantially the same location are required. In FIG. 2, it is assumed that the axis direction of the irradiation light to the human eye 100 is the Z axis (depth direction), and the plane orthogonal to the Z axis, that is, the fundus plane direction is the X axis and the Y axis.

  In FIG. 2, y1 to yn indicate B scans at different Y positions, and n indicates the number of samples in the y scan direction. x1 to xp indicate sample positions in the X scan direction, and p indicates the number of samples in the X scan direction that compose the B scan. Δx is the distance between adjacent X positions (x pitch), and Δy is the distance between adjacent Y positions (y pitch). m represents the number of repetitive measurements of the B scan at substantially the same location. Here, the initial position (x1, y1) can be arbitrarily set by the computer 40.

  In the present embodiment, the OCT apparatus performs a scan method in which the B scan at substantially the same location is repeated m times and moves to n y locations. Note that the repetitive scan method may be a scan method in which the A-scan is repeated at substantially the same location and then moved to the next position to form the B-scan.

  Here, when the number of repetitions m is large, the number of times of measurement at the same location increases, so that the accuracy of blood flow detection is improved. On the other hand, the scanning time becomes longer, and there arises a problem that motion artifacts occur in an image due to eye movements (fixation fine movement) during scanning and a problem that the burden on the subject increases. In this embodiment, m = 4 in consideration of the balance between the two. Note that m may be freely changed according to the A-scan speed of the OCT apparatus and the amount of movement of the human eye 100. That is, the number of repetitive scans is not limited to the above value.

  The image size in the x and y directions is determined by p × n. If the image size in the x and y directions is large, a wide range can be scanned with the same measurement pitch, but the scan time becomes long, and the above-described problems of motion artifact and patient burden occur. In this embodiment, n = p = 300 in consideration of the balance between the two. Note that the above n and p can be freely changed as appropriate. That is, the image size is not limited to the above value.

  In the present embodiment, the x pitch and the y pitch are determined as の of the beam spot diameter of the irradiation light on the fundus, and are set to 10 μm. By setting the x pitch and the y pitch to の of the beam spot diameter on the fundus, an image to be generated can be formed with high definition. Even if the x pitch and the y pitch are smaller than の of the fundus beam spot diameter, the effect of further increasing the definition of the generated image is small.

  Conversely, when the x pitch and the y pitch are larger than 1/2 of the fundus beam spot diameter, the definition deteriorates, but an image in a wider range can be obtained. The x pitch and the y pitch may be freely changed according to clinical requirements.

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

[Interference signal acquisition procedure]
Next, an example of an interference signal acquisition procedure according to the present embodiment will be described with reference to FIG.

  First, in step S109, the acquisition unit 41 sets the index i of the position yi in FIG. Next, in step S110, the acquisition unit 41 controls the drive mechanism (not shown) to move the scan positions of the x-axis scanner 53 and the y-axis scanner 54 to (x1, yi) in FIG. In step S119, the acquiring unit 41 initializes the index j of the number of times of repetitive measurement of the B scan to 1.

Next, in step S120, the x-axis scanner 53 and the y-axis scanner 54 perform the j-th repetition measurement B-scan. Note that the B scan range is (x1, yi) to (xp, yi). Here, the wavelength-swept light source 10 emits light at an A-scan rate of 100 kHz, and the number p of samples constituting the B-scan in the x-scan direction is, for example, p = 300. Therefore, the net B scan time (Δtb) is as shown in Equation 1.
Δtb = (1/100 kHz) × 300 = 3 ms (1)
The time interval Δt of the repetitive measurement is the sum of the net B scan time Δtb and the preparation time Δtp of the X-axis scanner 53 as shown in Expression 2. The preparation time Δtp is a time for adjusting the scan positions of the x-axis scanner 53 and the y-axis scanner 54, for example. If Δtp = 1 ms,
Δt = Δtb + Δtp = 4 ms (2)
Further, the total measurement time tm is represented by Expression 3 using the number of repetitions m and the number n of samples in the y-scan direction.
tm = Δt * m * n = (Δtb + Δtp) * m * n (3)
In this embodiment, since m = 4 and y = 300, the total measurement time tm = 3.6 s.

  Here, the shorter the B scan time Δtb and the time interval Δt of the repetitive measurement, the less the influence of the movement of the human eye 100, and the smaller the bulk motion noise. Conversely, if Δt is long, the position reproducibility is reduced due to the movement of the human eye 100, and bulk motion noise is increased. In addition, the time required for measurement increases, and the burden on the patient increases. Here, bulk motion means movement of the eye to be inspected, and bulk motion noise means noise generated by movement of the eye to be inspected.

  Further, if the time interval Δt of the repetitive measurement is too small, the time required for blood flow detection is shortened, and the blood flow detection sensitivity is reduced.

  It is desirable to select tm, Δt, n, p, Δtb, and Δtp in consideration of these. Note that the X-axis scanner 53 and the Y-axis scanner 54 may perform the B-scan while tracking the human eye 100 in order to enhance the repeatability of the position of the repeated measurement.

  In step S130, the differential detector 31 detects the interference light every A scan, and is converted into a digital signal (interference signal) via the A / D converter 32. The acquisition unit 41 acquires an interference signal from the A / D converter 32 and stores the interference signal in a storage unit (not shown). The acquisition unit 41 acquires p A-scan signals in one B-scan. The p A-scan signals constitute one B-scan signal.

  In step S139, the acquisition unit 41 increments the index j of the number of times of repeated measurement of the B scan.

  Next, in step S140, the acquisition unit 41 determines whether the index j of the number of times of repetition is larger than the predetermined number m of repetitions. That is, the acquisition unit 41 determines whether the B scan at the position yi has been repeated m times. If it has not been repeated, the process returns to S120, and the B-scan measurement at the same position is repeated. If it has been repeated a predetermined number of times, the flow proceeds to S149.

  In step S149, the acquisition unit 41 increments the index i of the position yi.

  Next, in step S150, the acquisition unit 41 determines whether the index i of the position yi is greater than the predetermined number n of measurement positions, that is, whether the B scan has been performed at all n Y positions. If the B scan has not been performed at all n Y positions, the process returns to step S110, and the measurement at the next measurement position is repeated. If the B scan has been performed at all n Y positions, the process proceeds to the next step S160.

  In step S160, the acquisition unit 41 acquires background data. The acquisition unit 41 performs A-scan 100 times in a state where the shutter 85 is closed (inserted into the optical path) by controlling a driving unit (not shown), and the acquisition unit 41 averages and stores 100 A-scan signals. Store in the department. The number of A-scans for obtaining background data is not limited to 100.

  By performing the above steps, the acquisition unit 41 can acquire a plurality of interference signals and background data obtained by repeatedly measuring at least two times at substantially the same location.

[Signal processing procedure]
Next, an example of a signal processing procedure according to the present embodiment will be described with reference to FIG.

  FIG. 4 is an example of a flow until the acquisition unit 41 to which the interference signal is input outputs an OCT angiographic image as a result of signal processing.

  In the present embodiment, it is necessary to calculate a motion contrast feature amount in order to generate an OCT angiography image.

  In FIG. 4, first, in step S201, the changing unit 45 sets a threshold value for calculating a motion contrast feature amount described later. For the set value of the threshold value, the changing unit 45 extracts in advance the area on the noise floor of the tomographic image on which only random noise is displayed, calculates the standard deviation σ, and sets the average to the noise floor plus 2σ. Note that this threshold can be appropriately changed by the inspector.

  Next, in step S210, the acquisition unit 41 sets the index i of the position yi in the y direction to 1. In step S220, the obtaining unit 41 extracts the B-scan interference signals (for m times) obtained by the repetitive B-scan at the position yi from the storage unit from the interference signals obtained by the processing shown in FIG. Specifically, a plurality of B-scan interference signals obtained by the repetitive B-scan at the position yi are read from the storage unit.

  Next, in step S230, the acquisition unit 41 repeatedly sets the index j of the B scan to 1.

  In step S240, the acquisition unit 41 extracts the j-th B-scan interference signal from the m-times B-scan interference signals.

  Next, in step S250, the computer 40 subtracts the background data acquired in step S160 of FIG. 3 from the B-scan interference signal acquired in step S240.

  In step S260, the acquisition unit 41 performs a Fourier transform on the B-scan interference signal from which the background data has been subtracted. In this embodiment, a fast Fourier transform (FFT) is applied.

  In step S270, the acquisition unit 41 calculates the square of the absolute value of the amplitude of the B-scan interference signal Fourier-transformed in step S260. This value is the intensity of the B-scan tomographic image. That is, in step S270, the obtaining unit 41 obtains a tomographic image indicating Intensity.

  In step S280, the acquisition unit 41 increments the number of repetition measurements j indicating the number of repetitions of the B scan. Then, in step S290, the acquisition unit 41 determines whether the number of repetition measurements j is greater than the number of repetitions m. That is, the acquiring unit 41 determines whether the intensity calculation of the B scan at a certain position yi has been repeated m times. If the repetition measurement number j is smaller than the repetition number m, the process returns to step S240, and the acquisition unit 41 repeats the intensity calculation of the repetitive B scan at the same Y position. If the repetition count j is larger than the repetition count m, the process proceeds to step S300.

  In step S300, the positioning unit 42 positions the tomographic images for m frames of the repeated B scan at a certain Y position yi. Specifically, the positioning unit 42 first selects any one tomographic image from the tomographic images for m frames as a template. The positioning unit 42 may calculate the correlation for all combinations of the tomographic images for m frames, obtain the sum of the correlation coefficients for each frame, and select the tomographic image of the frame having the maximum sum as a template. .

  Next, the positioning means 42 collates the tomographic image selected as the template with the tomographic image of another frame to determine the amount of positional deviation (δX, δY, δθ). Specifically, the positioning unit 42 calculates Normalized Cross-Correlation (NCC), which is an index indicating the degree of similarity to the tomographic image of another frame, while changing the position and angle of the template image. Then, the positioning means 42 obtains the difference between the image positions when this value becomes the maximum as the positional deviation amount. In the present invention, the index indicating the degree of similarity can be variously changed as long as it is a scale indicating the similarity of the feature between the tomographic image selected as the template and the tomographic image of another frame. For example, Sum of Absolute Difference (SAD), Sum of Squared Difference (SSD), Zero-means Normalized Cross-Correlation (ZNCC), Phase Only Correlation Index (Relationship of POC, etc.) May be used.

  Next, the positioning unit 42 applies the position correction of the tomographic image indicating Intensity to the tomographic image of the m-1 frame other than the template based on the amount of positional deviation (δX, δY, δθ), and obtains the tomographic image of m frames. Align the images. After the completion of the alignment, the processes of steps S310 and S311 are performed.

  In step S310, the calculation unit 43 calculates a motion contrast feature amount. In the present embodiment, the calculation unit 43 calculates a variance value for each pixel at the same position from the tomographic image of the m frame aligned in step S300, and sets the variance value as a motion contrast feature amount. Note that there are various methods for obtaining the motion contrast feature amount, and any index can be applied to the present invention as long as it is an index indicating a change in the luminance value of each corresponding pixel of a plurality of tomographic images at the same Y position.

  On the other hand, in step S311, the calculation unit 43 calculates the average of the m aligned tomographic images (intensity images) obtained in step S300, and generates an average intensity image.

  In step S330, the acquisition unit 41 increments the index i of the position yi. Then, in step S340, the acquisition unit 41 determines whether the index i is larger than the number n of the measurement positions. That is, the acquisition unit 41 determines whether or not the alignment has been performed at all the n Y positions, the intensity averaged image has been calculated, and the motion contrast feature amount has been calculated. If the index i is smaller than the number n of the measurement positions, the process returns to S220. If the index i is larger than the number n of the measurement positions, the process proceeds to step S400.

  When step S340 is completed, the intensity averaged image and the three-dimensional volume data of the motion contrast feature amount of each pixel of the tomographic images (ZX plane) at all Y positions are obtained.

  In step S400, the generation unit 44 generates an OCT angiography image.

  Details of step S400 will be described with reference to FIG. First, the processing is divided into a retinal layer segmentation process of step S401 and a motion contrast feature value threshold process of step 402.

  As the segmentation process of the retinal layer in step S401, the segmentation process using the intensity averaged image generated in step S311 will be specifically described.

  The generation unit 44 extracts an intensity averaged image to be processed from the intensity averaged images at a plurality of Y positions. Then, the generation unit 44 creates an image by applying the median filter and the Sobel filter to the extracted intensity averaged image, respectively (hereinafter, also referred to as a median image and a Sobel image, respectively).

  Next, the generating unit 44 creates a profile for each A-scan from the created median image and Sobel image. The created profile is a brightness value profile in the median image and a gradient profile in the Sobel image. Then, the generation unit 44 detects a peak in the profile created from the Sobel image. The generation unit 44 extracts the boundary (layer boundary) of each region of the retinal layer by referring to the profile of the median image before and after the peak detected between the Sobel images and between the peaks. That is, the generation unit 44 corresponds to an example of a detection unit that detects a layer boundary of a tomographic slice included in the subject from the tomographic image data.

  FIG. 6 shows an example of the segmentation result. FIG. 6 is an intensity-averaged image at a certain Y position, in which a segmentation line is overlaid on the intensity-averaged image by a broken line. In the segmentation processing in the present embodiment, six layers are detected. The six layers are (1) nerve fiber layer (NFL), (2) ganglion cell layer (GCL) + inner plexiform layer (IPL), (3) inner granular layer (INL) + outer plexiform (4) Outer granular layer (ONL) + outer limiting membrane (ELM) combined layer, (5) Ellipsoid Zone (EZ) + Interdigestion Zone (IZ) + Retinal pigment epithelium (RPE) And (6) Choroid. Note that the segmentation process described in the present embodiment is an example, and another method such as a segmentation process using the Dijkstra method may be used. The number of layers to be detected can be set arbitrarily.

  Next, the details of the threshold processing of the motion contrast feature amount in step S402 will be described. The calculating unit 43 performs threshold processing of the motion contrast feature based on the threshold set in step S205. Specifically, the calculating unit 43 calculates the intensity averaged image and the motion contrast characteristic corresponding to the B scan at a certain Y position from the intensity averaged image and the three-dimensional volume data of the motion contrast characteristic amount obtained in step S340. Quantity and extract. Next, the calculating unit 43 compares the average intensity of each pixel in the B scan with the threshold. When the average intensity is equal to or smaller than the threshold, the calculation unit 43 sets the value of the motion contrast feature amount corresponding to the pixel to 0. If the average intensity is larger than the threshold, the calculation unit 43 maintains the value of the motion contrast feature amount corresponding to the pixel. By repeating this threshold processing at all Y positions, it is possible to acquire three-dimensional volume data of the motion contrast feature amount in which the influence of the intensity change due to random noise is reduced in a place where there is no blood vessel such as near the noise floor.

  Note that the smaller the threshold value, the higher the sensitivity of detecting the motion contrast feature amount and the more the noise component. Also, the larger the threshold value, the lower the noise, but the lower the sensitivity of motion contrast detection. In the present embodiment, the threshold is set as the average intensity of the noise floor + 2σ, but the threshold is not limited to this.

  In step S403, the generation unit 44 generates an OCT angiography image based on the retinal segmentation result and the threshold value-processed motion contrast feature. Then, the display control unit 46 causes the display unit 70 to display the generated OCT angiography image.

  Here, an example of a method of generating an OCT angiographic image will be specifically described. The generation unit 44 cuts out a region corresponding to an arbitrary layer, for example, a layer obtained by combining the ganglion cell layer (GCL) + the inner plexiform layer (IPL), from the three-dimensional volume data of the motion contrast feature amount. Then, the generation unit 44 determines a representative value of the motion contrast feature amount in the Z direction of each A scan. The A-scan representative value may be any of an average value, a maximum value, and a median value. By plotting (projecting) this A-scan representative value two-dimensionally (X direction, Y direction), an OCT angiography image corresponding to a layer obtained by combining the ganglion cell layer (GCL) + the inner plexiform layer (IPL) Is generated. Since the motion contrast feature and the segmentation result are obtained from the same tomographic image, the motion contrast feature and the segmentation result are associated with each other. Therefore, the generation unit 44 can extract the motion contrast feature of an arbitrary layer from the three-dimensional volume data of the motion contrast feature by using the correspondence between the motion contrast feature and the segmentation result.

  FIG. 7 shows an example of an OCT angiography image generated in the present embodiment. FIG. 7 shows the measurement of the macula using the OCT apparatus. In the present embodiment, the generation unit 44 cuts out the motion contrast feature amount of the layer obtained by combining the ganglion cell layer (GCL) + the inner plexiform layer (IPL) from the three-dimensional volume data of the motion contrast feature amount based on the segmentation result. . Then, the generation unit 44 projects or integrates the extracted motion contrast feature amount in the depth direction of the fundus to generate an OCT angiographic image. That is, the generation unit 44 generates a two-dimensional motion contrast image by projecting or integrating the motion contrast value in the depth direction of the subject based on the layer boundary detected by the detection unit. As shown in FIG. 7, a portion with a high motion contrast feature amount (white portion in the image) depicts a fundus blood vessel.

  FIG. 8 is an example of a display screen of the display unit 70 in the present embodiment. FIG. 8 shows an OCT angiography image 71 in a specific layer based on the result of the segmentation process in step S401, a tomographic image 72 corresponding to line AA 'in the figure, and a slide bar 73 for setting a threshold. ing. The selection range of the slide bar 73 is from R1 to R2. In the present embodiment, for example, when the average intensity of the noise floor of the OCT apparatus is m and the standard deviation is σ, R1 = m and R2 = m + 3σ may be used. Not limited to

  The layers constituting the OCT angiographic image 71 can be selected from the above-described six layers by operating means (not shown). That is, the inspector selects a layer from which the motion contrast feature is cut out from the result of the segmentation processing, and the generating unit 44 generates an OCT angiographic image of an arbitrary layer based on the selected layer. For example, when the inspector clicks a predetermined layer on the tomographic image 72 using an operation unit such as a mouse, the generation unit 44 detects the clicked layer and generates an OCT angiography image 71 of the clicked layer. . Then, the display control unit 46 causes the display unit 70 to display the OCT angiography image 71.

  Alternatively, the inspector may use the operation unit to click a plurality of layer boundaries displayed on the display unit 70 to define a layer for generating the OCT angiographic image 71. The generating means 44 generates an OCT angiographic image 71 each time the layer that generates the OCT angiographic image 71 is changed by the examiner, and the display control means 46 generates a display unit 70 each time the OCT angiographic image 71 is generated. Update the display of. Instead of clicking the tomographic image or the layer boundary, the name of the layer and a check box (or radio button) are displayed in an area different from the tomographic image 72. This may allow the inspector to select the layer for generating the OCT angiographic image 71 by clicking on the check box. In this case, the display control unit 46 causes the display unit 70 to display a plurality of layer names and a plurality of check boxes corresponding to the layer names. Then, when the check box is clicked by the inspector, the generation unit 44 acquires the layer corresponding to the clicked check box, and generates the OCT angiography image 71. The specific layer selected in the OCT angiography image 71 may be only one layer or a plurality of layers.

  Further, the display control means 46 may highlight the layers constituting the OCT angiographic image 71 or a plurality of layer boundaries defining the layers on the tomographic image 72. For example, the display control means 46 displays a plurality of layer boundaries defining the layers constituting the OCT angiographic image 71 brighter than the other layer boundaries. In this way, it is possible to easily grasp the layers constituting the OCT angiography image 71 which is the front image of the fundus.

  Note that the display control unit 46 displays the two-dimensional OCT angiography image on the display unit 70 as the OCT angiography image 71, but may display the three-dimensional OCT angiography image on the display unit 70. . For example, the generation unit 44 generates a three-dimensional OCT angiography image of a layer specified by the inspector using the three-dimensional volume data of the motion contrast feature amount. Then, the display control means 46 causes the display unit 70 to display a three-dimensional OCT angiography image. The display control means 46 may display a three-dimensional OCT angiography image instead of a two-dimensional OCT angiography image, or may display both OCT angiography images side by side. When two-dimensional and three-dimensional OCT angiographic images are displayed on the display unit 70, when a predetermined layer is selected by the inspector, both OCT angiographic images are synchronized by the generation unit 44 and the display control unit 46. Will be updated.

  The line A-A 'of the OCT angiography image 71 can be set at an arbitrary position in the Y direction. For example, when the examiner moves the line A-A 'using the operation means, the tomographic image 72 corresponding to the line A-A' is displayed.

  Returning to FIG. 5, in step S404, the examiner determines whether the threshold is appropriate by looking at the OCT angiography image displayed on the display unit 70, and if the examiner determines that the threshold value is unacceptable, the examiner determines in step S405 that the examiner has a failure. Changes the threshold using the operation means. Then, the calculation unit 43 performs the threshold processing of the motion contrast feature amount in step S402 again, and the generation unit 44 generates the OCT angiography image again. Each time the threshold value is changed, steps S402 and S403 are repeatedly executed. That is, the calculating unit 43 calculates a motion contrast value each time the threshold value is changed by the changing unit, and the generating unit 44 generates a motion contrast image each time the threshold value is changed by the changing unit. Further, the display control means 46 updates the motion contrast image displayed on the display means every time the threshold value is changed by the change means. The examiner updates the OCT angiography image every time the threshold value is changed, so that an appropriate threshold value can be easily grasped.

  If the examiner determines in step S404 that the threshold is OK, the generation process of the OCT angiography image in step S400 of FIG. 5 ends.

  According to the above-described embodiment, the threshold value to be compared with the intensity of the tomographic image can be changed, so that a blood vessel can be accurately imaged.

  In the above-described embodiment, the slide bar 73 is used to make the threshold variable. However, the present invention is not limited to this, and the apparatus may be configured so that a numerical value of the threshold can be set in a text box, or a drop-down list may be used. A configuration in which a preset threshold is selected may be adopted.

(Modification)
In the above embodiment, a description has been given of generating a two-dimensional OCT angiography image based on the detection result of the layer structure in step S401. However, the present invention is not limited to this, and the layer structure may not be detected. That is, in step S403, an OCT angiography image may be generated from data in an arbitrary range specified by the examiner of the three-dimensional volume data of the motion contrast feature. That is, step S401 is not an essential process.

  FIG. 13 is a diagram showing three-dimensional volume data of a motion contrast feature amount. Further, an area A indicates a range (Xd, Yd, Zd) to be displayed on the display unit 70. This range is input by the inspector via the GUI, for example. For example, the examiner inputs coordinates of a range to be displayed on the display unit 70. The generation means 44 extracts the motion contrast feature in the range (Xd, Yd, Zd) input by the examiner from the three-dimensional volume data of the motion contrast feature, and generates an OCT angiographic image. The OCT angiography image generated by the generation unit 44 may be a two-dimensional OCT angiography image projected or integrated in the depth direction Z, or may be a three-dimensional OCT angiography image.

(Second embodiment)
In the second embodiment, an aspect different from that of the first embodiment regarding the setting of the threshold will be described.

  The second embodiment is characterized in that in step S400 in FIG. 4, the threshold value is changed for each layer using the segmentation result of the retinal layer. In view of the structure of the retina of the human eye, considering that the blood vessel density differs for each retinal layer in the depth direction, it is preferable to make the threshold value for blood vessel detection variable for each layer.

  FIG. 9 shows the flow of the processing steps for generating an OCT angiographic image according to the present embodiment. The difference from the first embodiment in FIG. 5 is that the threshold processing of the motion contrast feature value in step S402 is performed after the segmentation data is generated, that is, after step S401.

  In step S402, the calculation unit 43 performs a threshold process on the intensity averaged image and the three-dimensional volume data of the motion contrast feature amount obtained in step S340 for each layer detected by the segmentation. Specifically, the calculating unit 43 acquires from the memory an intensity averaged image corresponding to a B scan at a certain Y position and a motion contrast feature amount. Then, when the average intensity at each pixel (position) in the B scan is equal to or smaller than the threshold value with respect to the threshold value set for each layer, the calculation unit 43 calculates the value of the motion contrast feature amount corresponding to the pixel. Set to 0. It should be noted that the motion contrast feature value may be set to a value near 0 instead of completely 0. If the average intensity is larger than the threshold, the calculation unit 43 maintains the value of the motion contrast feature amount corresponding to the pixel.

Here, regarding the setting of the threshold value, the threshold value may be changed by the slide bar 73 for each of a plurality of layers with respect to the tomographic image 72 displayed on the display unit 70. FIG. 10 is an example of the display unit 70 according to the second embodiment. By providing a GUI for receiving a change in the threshold value for each layer, as in a slide bar 73 shown in FIG. Here, the breakdown of the six layers is the aforementioned Layer1: (1) nerve fiber layer (NFL)
Layer 2: (2) ganglion cell layer (GCL) + inner plexiform layer (IPL)
Layer 3: (3) Inner granular layer (INL) + outer plexiform layer (OPL)
Layer 4: (4) outer granular layer (ONL) + outer limiting membrane (ELM)
Layer 5: (5) Ellipsoid Zone (EZ) + Interdigitation Zone (IZ) + Retinal pigment epithelium (RPE)
Layer 6: (6) Choroid
Is equivalent to Note that the changing unit 45 receives the change of the threshold value via the slide bar 73 and changes the threshold value. That is, the changing unit 45 changes the threshold for each layer included in the subject. Here, the slide bar 73 shown in FIG. 10 is an example of a GUI for receiving a change in the threshold value. The classification of the layers is not limited to the above six types.

  According to the above-described embodiment, the threshold value to be compared with the intensity of the tomographic image can be changed, so that a blood vessel can be accurately imaged. For example, due to the structure of the eye, there are a region (layer) having a low blood vessel density and a dense region depending on the depth direction, and it is necessary to suppress false extraction of blood vessels due to the influence of noise, particularly in a rough region. Even in such a situation, according to the above-described embodiment, the threshold can be set for each layer, so that it is possible to accurately image a blood vessel according to the characteristics of the layer.

  In the above embodiment, the inspector changes the threshold via the GUI, but the threshold for each layer may be automatically set to a different value. For example, if the blood vessel density can be grasped in advance for each layer, the threshold value for each layer may be automatically set to a different value. That is, the changing unit 45 can automatically set the initial value of the threshold value for each layer based on the information of the blood vessel density for each layer. That is, a plurality of threshold values are provided according to the layers included in the subject. Note that information in which the position or name of the layer is associated with the threshold is stored in the memory in advance, and the changing unit 45 automatically sets the initial value of the threshold for each layer based on the association information stored in the memory. May be set.

  Note that the threshold value may be a discrete value for each layer, or may be a continuous value along the depth direction by complementation or the like.

(Modification)
In the second embodiment, the mode in which the threshold is changed for each layer in consideration of the blood vessel density in the depth direction has been described. However, the threshold is changed not only in the Z direction but also in the X and Y directions according to the blood vessel density. You may.
For example, in the macula shown in the OCT angiography image 71 in FIG. 10, there is a region having a low blood vessel density on the XY plane as represented by an avascular region (FAZ). For example, the display control unit 46 may divide the XY plane into a grid and display a GUI on which a threshold can be set for each area on the display unit 70. Then, the changing unit 45 receives the change of the threshold value by the inspector via the GUI, and changes the threshold value of each area on the XY plane. With this configuration, the threshold value can be set more finely, so that the blood vessel can be more accurately imaged.

  If the region B (ΔX, ΔY, ΔZ) in FIG. 13 is a region with a low blood vessel density, the examiner sets the region (ΔX, ΔY, ΔZ) via the GUI, and another region is set within the region. The threshold may be set higher than the area to suppress false extraction of blood vessels due to noise. Note that, in a two-dimensional region, a region having a low blood vessel density may be set by ΔX and ΔY, and in that region, a threshold may be increased as compared with other regions to suppress false extraction of blood vessels due to noise. The threshold value in the area B selected by the examiner can be changed by the slide bar 73 or the like.

  According to the above embodiment, the range in which the threshold is changed can be selected without being restricted by the layer boundary, so that the operability of the inspector can be improved.

  Further, according to the above embodiment, since the threshold value can be set more finely, it is possible to more accurately image a blood vessel.

(Third embodiment)
The embodiments described so far assume that the noise floor intensity does not change in the depth direction of the OCT tomographic image. However, when a raw interference signal is measured, the noise characteristics of the high frequency component and the low frequency component may be different. This means that the intensity distribution of the noise floor differs in the depth direction when the signal intensity is obtained by performing the Fourier transform on the interference signal. FIG. 11 shows an example of the signal strength of the noise floor. The signal strength of the noise floor differs between the shallow position (Z1) and the deep position (Z2) and is compared with the signal strength of the tomographic image data. In some cases, the threshold value cannot be ignored if it is fixed.

  The third embodiment is characterized in that when the intensity of the noise floor depends on the depth direction, the threshold value is automatically determined from the noise floor characteristics for each depth.

  Specifically, the changing unit 45 may determine the threshold based on a signal intensity distribution obtained from the signal intensity of the noise floor (noise distribution) measured a plurality of times as shown in FIG. For example, the changing unit 45 calculates an average value m (Z) by averaging the signal intensities of a plurality of noise floors for each depth. Then, the changing unit 45 determines a value exceeding the average value m (Z) by a predetermined value (ΔTh) as the threshold value Th. That is, the changing unit 45 changes the threshold according to the depth of the layer included in the subject. More specifically, the changing unit 45 changes the threshold based on the noise distribution in the depth direction of the subject. From different viewpoints, the threshold value changes according to the depth position of the subject.

  Although the threshold value Th is determined using the average value of the signal intensities of the noise floor measured a plurality of times, the present invention is not limited to this, and the median value of the signal intensities of the noise floor measured a plurality of times is determined. , The maximum value, and the minimum value may be used. The measurement of the signal strength of the noise floor need not be performed a plurality of times. Note that the acquisition unit 41 acquires an interference signal generated in a state where the shutter 85 is closed as a noise floor intensity signal.

  According to the above embodiment, the threshold can be automatically set in consideration of the change in the noise floor in the depth direction, so that it is possible to accurately image the blood vessel. More specifically, the noise characteristics on the OCT device are not always constant in the Z direction. At this time, if the same threshold value is set, the blood vessel extraction accuracy deteriorates at a depth position where the noise characteristic is deteriorated. As described above, there is a case where the drawing accuracy of the blood vessel is reduced due to a problem in the apparatus in the depth direction of the OCT tomographic image. Even in such a situation, according to the above-described embodiment, since the threshold value is determined in consideration of the change in the noise floor in the depth direction, it is possible to accurately image a blood vessel.

  Note that the threshold automatically determined based on the noise characteristics can be changed by the slide bar 73 shown in FIG. 10 and the like.

(Fourth embodiment)
In the fourth embodiment, the threshold is determined based on the roll-off characteristic derived from the OCT apparatus.

  The roll-off characteristic in the OCT apparatus system is a characteristic that the signal intensity decreases as the depth increases along the retina. For example, the signal intensity decreases by 5 dB at a depth of 1 mm.

FIG. 12 is a diagram illustrating an example of a roll-off characteristic of the OCT apparatus. The acquisition unit 41 can acquire the roll-off characteristic from the interference signal. In FIG. 12, the roll-off characteristic is shown as a function f (z). If the signal strength at Z = 0 and I _0, taking into account the roll-off characteristic f (z), the threshold value Th in the changing means 45 and the depth Z can be automatically set as in equation 4. That is, the changing unit 45 changes the threshold based on a change in the signal intensity of the tomographic image data in the depth direction of the subject.
_{Th (z) = Th 0 -k} (I 0 -f (Z)) ···· (4) where the coefficient k is a coefficient which can be arbitrarily set as a real number, for example, from 0 to 1. In Expression 3, when the value of the coefficient k is increased, the threshold value is decreased, and an effect of further increasing the detection sensitivity of the motion contrast feature is expected. However, the value of the coefficient k may be set in consideration of the influence of noise. The coefficient k may be changeable by a GUI such as the slide bar 73. Further, the changing unit 45 may automatically determine the coefficient k according to the blood vessel density based on the second embodiment. For example, the changing unit 45 decreases the coefficient k as the blood vessel density increases. The changing unit 45 may automatically determine the coefficient k based on the noise characteristics based on the third embodiment. That is, the coefficient k is increased as the position becomes deeper in the depth direction of the retina.

  According to the above embodiment, since the threshold value can be automatically set in consideration of the roll-off characteristic, it is possible to accurately image a blood vessel. More specifically, if the threshold value is set to one fixed value in spite of the existence of the roll-off characteristic, the extraction accuracy of the blood vessel is deteriorated at a deeper position where the signal intensity decreases. Even in such a situation, according to the above-described embodiment, since the threshold value is determined in consideration of the roll-off characteristic, it is possible to accurately image a blood vessel.

  Note that the threshold automatically determined based on the roll-off characteristic can be changed using the slide bar 73 shown in FIG. 10 and the like.

In the embodiment described above is based on the signal intensity I ₀ at Z = 0 but is not necessarily employed the signal strength at the position of Z = 0.

  For example, the signal strength at Z = 0 is a DC component of the interference signal, and the DC component may remain as noise and cannot be obtained stably. Therefore, intensity data around Z = 0 may be acquired, and I0 at Z = 0 may be determined by extrapolation.

  Note that the roll-off characteristic of the OCT apparatus is obtained by placing a reflection mirror instead of the subject and measuring the interference signal while shifting the coherence gate position in the Z direction. At this time, since the autocorrelation component remains as noise at the position of Z = 0 (coherence gate position), it is generally performed to obtain interference signal data from a position slightly deeper than Z = 0 (for example, about 150 μm). ing. Therefore, it is desirable that the intensity I0 at Z = 0 be determined by acquiring some intensity data at a position slightly deeper than Z = 0 and extrapolating it.

[Other Examples]
Although the embodiments have been described in detail, the present invention can take embodiments as a system, an apparatus, a method, a program, a recording medium (storage medium), or the like. Specifically, the present invention may be applied to a system including a plurality of devices (for example, a host computer, an interface device, an imaging device, a web application, and the like), or may be applied to a device including a single device. good.

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

REFERENCE SIGNS LIST 40 computer 41 acquisition unit 42 positioning unit 43 calculation unit 44 generation unit 45 change unit 46 display control unit 70 display unit

One of the disclosed image generation devices is:
A plurality of tomographic image data of the subject's eye obtained by scanning the substantially same position of the subject's eye a plurality of times with measurement light, and a comparison result between a representative value indicating a signal intensity in the plurality of tomographic image data and a threshold. Calculating means for calculating a motion contrast value based on the
Positioning means for positioning the plurality of tomographic image data before the motion contrast value is calculated,
A detection unit that detects a plurality of layer boundaries by performing a segmentation process using at least one tomographic image data of the plurality of tomographic image data,
Based on at least one layer and the motion contrast value among a plurality of layers classified based on the detected plurality of layer boundaries,
Generating means for generating a motion contrast front image of the subject's eye,
Changing means for changing the threshold from an initial value in accordance with an instruction from an examiner,
The generation means is based on at least one of the plurality of layers determined according to an instruction from an examiner and a motion contrast value calculated again using a threshold obtained by the change. Then, a motion contrast front image of the subject's eye is generated again.

Claims (20)

Acquisition means for acquiring a plurality of tomographic image data each indicating a tomographic image at substantially the same position of the subject, and a comparison result between a threshold value of the plurality of tomographic image data and a threshold value of the plurality of tomographic image data indicating signal strength. Calculating means for calculating a motion contrast value based on the
Generating means for generating a motion contrast image of the subject based on the motion contrast value,
Changing means for changing the threshold value,
An image generation apparatus comprising: Further comprising a display control means for displaying on the display means a display for accepting the change of the threshold value and the motion contrast image generated by the generating means,
The changing means receives the change of the threshold value via a display for receiving the change of the threshold value displayed on the display means, and changes the threshold value,
The calculating means calculates the motion contrast value each time the threshold value is changed by the changing means,
The generating means generates the motion contrast image each time the threshold is changed by the changing means,
2. The image generation apparatus according to claim 1, wherein the display control unit updates a motion contrast image displayed on the display unit every time the threshold value is changed by the change unit.   The calculating means calculates the motion contrast value based on the plurality of tomographic image data, and calculates the motion contrast value again based on a comparison result between a representative value indicating the signal intensity and a threshold value. The image generation device according to claim 1 or 2, wherein (Motion contrast value changes by comparing threshold and intensity)
The motion contrast value is a value that increases as the change in the subject between the plurality of tomographic image data increases,
The calculating means, the motion contrast value when the representative value indicating the signal strength is lower than the threshold, a value lower than the motion contrast value when the representative value indicating the signal strength is higher than the threshold The image generating apparatus according to claim 1, wherein   The apparatus according to claim 1, wherein the changing unit changes the threshold for each layer included in the subject.   The image generating apparatus according to claim 1, wherein the changing unit changes the threshold according to a depth of a layer included in the subject.   The apparatus according to claim 4, wherein the changing unit sets the threshold value lower in a deeper layer included in the subject.   The apparatus according to claim 1, wherein the changing unit changes the threshold based on a noise distribution in a depth direction of the subject.   The image generation apparatus according to claim 1, wherein the changing unit changes the threshold based on a change in signal intensity of the tomographic image data in a depth direction of the subject. The motion contrast value is three-dimensional data,
The apparatus according to claim 1, wherein the generating unit generates the two-dimensional motion contrast image by projecting or integrating the motion contrast value in a predetermined range in a depth direction of the subject in the depth direction. The image generation device according to any one of claims 9 to 9. The motion contrast value is three-dimensional data,
The apparatus according to claim 1, wherein the generation unit generates the three-dimensional motion contrast image based on the motion contrast value in a predetermined range in a depth direction of the subject. The image generation device according to any one of the preceding claims. The motion contrast value is three-dimensional data,
The apparatus further includes a detection unit configured to detect a layer boundary of a tomogram included in the subject from the tomographic image data,
The generation unit generates the two-dimensional motion contrast image by projecting or integrating the motion contrast value in a depth direction of the subject based on a layer boundary detected by the detection unit. The image generation device according to claim 1.   13. The image generation apparatus according to claim 1, wherein the representative value is an average value of signal intensities of the plurality of tomographic image data.   The image generation method according to claim 1, wherein the motion contrast value is one of a variance value, a decorrelation value, and a difference value between the plurality of tomographic image data.   14. The image generating apparatus according to claim 13, further comprising a positioning unit that positions the plurality of tomographic image data before calculating the motion contrast value.   The image generation apparatus according to claim 1, wherein the subject is a fundus. By scanning substantially the same position of the subject a plurality of times with the measurement light, an obtaining step of obtaining a plurality of tomographic image data each indicating a tomographic image of the subject,
A calculation step of calculating a motion contrast value based on a comparison result between a threshold value and a representative value of the plurality of tomographic image data and the plurality of tomographic image data indicating signal strength,
A generation step of generating a motion contrast image of the subject based on the motion contrast value,
A changing step of changing the threshold,
An image generation method, comprising:   A program for causing a computer to execute each step of the image generation method according to claim 17. Acquisition means for acquiring a plurality of tomographic image data each indicating a tomographic image at substantially the same position of the subject, and a comparison result between a threshold value of the plurality of tomographic image data and a threshold value of the plurality of tomographic image data indicating signal strength. Calculating means for calculating a motion contrast value based on the
Generating means for generating a motion contrast image of the subject based on the motion contrast value,
The image generating apparatus according to claim 1, wherein the threshold value changes according to a depth position of the subject. Acquisition means for acquiring a plurality of tomographic image data each indicating a tomographic image at substantially the same position of the subject, and a comparison result between a threshold value of the plurality of tomographic image data and a threshold value of the plurality of tomographic image data indicating signal strength. Calculating means for calculating a motion contrast value based on the
Generating means for generating a motion contrast image of the subject based on the motion contrast value,
The image generation apparatus according to claim 1, wherein the threshold is provided with a plurality of values according to a layer included in the subject.