Oct apparatus and oct signal processing program

Abstract

A control unit of this optical coherence tomography (OCT) apparatus executes a change amount calculation step (S6) and a normalization step (S7). In the change amount calculation step, the control unit calculates a change amount between a first complex OCT signal Cn and a second complex OCT signal Cn +1 acquired at different times from the same location on a sample of biological tissue. In the normalization step, the control unit generates motion contrast data by normalizing the calculated change amount on the basis of the magnitude of the first complex OCT signal Cn and the second complex OCT signal Cn +1.

Description

OCT device and OCT signal processing program

[0001] The present disclosure relates to an optical coherence tomography (OCT) device and an OCT signal processing program that generate motion contrast data of biological tissue by processing OCT signals acquired based on the principles of OCT.

[0002] Conventionally, a technique for acquiring motion contrast data of biological tissue (e.g., the fundus of a test eye) based on the principles of OCT has been proposed. Motion contrast data is data obtained by processing multiple OCT signals acquired at different times from the same position on the biological tissue. The motion contrast data expresses information on the movement of the biological tissue (e.g., the movement of blood flow within blood vessels in the biological tissue). Note that data indicating the position of blood vessels in the biological tissue (angiography data) is an example of motion contrast data.

[0003] A complex OCT signal expressed by a complex number is generally used as the OCT signal. The complex OCT signal can be expressed in polar form using amplitude (absolute value) and phase (angle).

[0004] Various methods for generating motion contrast data have been proposed. For example, in Patent Document 1, an OCT apparatus processes multiple OCT signals acquired at different times from the same position on biological tissue and generates first image data that visualizes phase difference information in the multiple OCT signals. The OCT apparatus also processes the same multiple OCT signals and generates second image data that visualizes information including the amplitudes of the multiple OCT signals. The OCT apparatus generates motion contrast data based on information from the first image data and information from the second image data, thereby compensating for the weaknesses of both data with the strengths of the other, thereby achieving a high-quality image.

[0005] JP 2015-131107 A

[0006] When complex OCT signals are acquired at different times for multiple positions in biological tissue, both the amplitude characteristics and phase characteristics differ between signals at positions where blood vessels are not present (hereinafter referred to as "non-vascular positions"), signals at positions where blood vessels are present (hereinafter referred to as "vascular positions"), and noise. Therefore, generating motion contrast data using both amplitude and phase information is more likely to improve the quality of the generated data than using only one of amplitude and phase information. Patent Document 1 also discloses a technique for generating motion contrast data using both phase information and amplitude information of an OCT signal. However, even when using the method described in Patent Document 1, there are cases where good motion contrast data is not generated.

[0007] A typical object of the present disclosure is to provide an OCT apparatus and an OCT signal processing program that are capable of more appropriately acquiring motion contrast data of biological tissue.

[0008] An OCT apparatus provided by a typical embodiment of the present disclosure includes an OCT unit that detects an OCT signal due to a reference light and a measurement light irradiated onto a biological tissue of a subject, and a control unit that processes the OCT signal to generate motion contrast data in the biological tissue, and the control unit generates a first complex OCT signal C obtained from the same position on the biological tissue at different times. ｎ and the second complex OCT signal C ｎ＋１ a change amount calculation step of calculating a change amount between the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１ and a normalization step of generating the motion contrast data by normalizing based on the magnitude of

[0009] An OCT signal processing program provided by a typical embodiment of the present disclosure is an OCT signal processing program executed by an OCT signal processing device that processes an OCT signal generated by a reference light and a measurement light irradiated onto a biological tissue of a subject, and the OCT signal processing program is executed by a control unit of the OCT signal processing device to generate a first complex OCT signal C obtained from the same position on the biological tissue at different times. ｎ and the second complex OCT signal C ｎ＋１ a change amount calculation step of calculating a change amount between the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１ and normalizing the OCT signal based on the magnitude of the motion contrast data to generate the motion contrast data.

[0010] The OCT device and OCT signal processing program according to the present disclosure make it easier to obtain motion contrast data of biological tissue more appropriately.

[0011] The OCT device exemplified in the present disclosure includes an OCT unit and a control unit. The OCT unit detects an OCT signal generated by a reference light and a measurement light irradiated onto the biological tissue of a subject. The control unit processes the OCT signal to generate motion contrast data of the biological tissue. The control unit executes a change amount calculation step and a normalization step. In the change amount calculation step, the control unit calculates a first complex OCT signal C obtained from the same position on the biological tissue at different times. ｎ and the second complex OCT signal C ｎ＋１ In the normalization step, the control unit calculates the amount of change between the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１ The motion contrast data is generated by normalizing the image based on the magnitude of the

[0012] Here, the background of the technology disclosed herein will be described. When complex OCT signals are acquired at different times for each of multiple positions in biological tissue, the characteristics of the signal at a position where no blood vessels exist (hereinafter referred to as a "non-vascular position"), the signal at a position where blood vessels exist (hereinafter referred to as a "vascular position"), and the noise are all different. As shown in FIG. 9 , when multiple complex OCT signals are acquired at non-vascular positions, the amplitude of each signal tends to be large, the amplitude change between the multiple signals tends to be small, and the phase change between the multiple signals also tends to be small. When multiple complex OCT signals are acquired at vascular positions, the amplitude of each signal, the amplitude change between the multiple signals, and the phase change between the multiple signals all tend to be large. Furthermore, when focusing on the noise of each of multiple OCT signals acquired from the same position at different times, the amplitude of each noise tends to be small, but the amplitude change between the multiple noises and the phase change between the multiple noises tend to be large.

[0013] As described above, both the amplitude characteristics and the phase characteristics differ between the signal at the non-vascular position, the signal at the vascular position, and noise. Therefore, generating motion contrast data using both amplitude and phase information is more likely to improve the quality of the generated data than using only one of amplitude and phase information. Patent Document 1 also discloses a technique for generating motion contrast data using the difference (amount of change) between a first vector based on phase information and amplitude information of a first OCT signal and a second vector based on phase information and amplitude information of a second OCT signal. The difference between the two vectors in Patent Document 1 is an example of the amount of change between two OCT signals.

[0014] However, the variation between the first complex OCT signal and the second complex OCT signal is easily affected by the sensitivity of the complex OCT signal. Therefore, if the variation between multiple OCT signals is used without normalizing it by signal magnitude, strong signals may appear as artifacts in motion contrast data in high-intensity regions, even when there is no actual subject movement. For example, if a motion contrast image of the fundus is generated using the variation between multiple OCT signals, artifacts may appear in high-intensity regions, such as the nerve fiber layer (NFL) and retinal pigment epithelium (RPE), where brightness increases. In this case, it becomes difficult to distinguish the artifacts in the high-intensity regions from actual vascular regions.

[0015] Therefore, as exemplified in Patent Document 1, it is assumed that first motion contrast data generated based on the amount of change between multiple OCT signals is multiplied by second motion contrast data that is independent of the magnitude of the OCT signals. In this case, as described above, the sensitivity of the first motion contrast data is high. On the other hand, the sensitivity of the second motion contrast data is inevitably low. Therefore, when the two data are multiplied, although artifacts in high-brightness areas may be reduced, the overall sensitivity decreases. As a result, there is a high possibility that actually connected vascular regions will be disconnected.

[0016] In contrast, according to the technology exemplified in the present disclosure, first, in the change amount calculation step, first complex OCT signals C ｎ and the second complex OCT signal C ｎ＋１ The amount of change calculated in the change amount calculation step is an amount of change that takes into account both phase information and amplitude information. Next, in the normalization step, ｎ and the second complex OCT signal C ｎ＋１The motion contrast data is generated by normalizing the amount of change between the two complex OCT signals based on the magnitudes of the two complex OCT signals. As a result, the amount of change calculated in the amount of change calculation step is normalized while maintaining the influence of both phase information and amplitude information, thereby generating motion contrast data. Therefore, the quality of the motion contrast data is improved compared to when only one of amplitude and phase information is used. Furthermore, high sensitivity is also more easily maintained, unlike when first motion contrast data generated based on the amount of change between multiple OCT signals is multiplied by second motion contrast data that is independent of the magnitudes of the OCT signals. As a result, better motion contrast data is generated.

[0017] Alternatively, it may be possible to first normalize each of the first and second complex OCT signals by signal magnitude and then calculate the amount of change between the magnitude-normalized values. However, if each of the two complex OCT signals is normalized by magnitude before calculating the amount of change, amplitude information is lost at that point, and motion contrast data based only on phase information is generated. Motion contrast data based only on phase information is prone to noise. In particular, when generating motion contrast images of still images, it is more desirable to use both amplitude information and phase information. In contrast, the technology disclosed herein uses both phase information and amplitude information to generate motion contrast data with high sensitivity.

[0018] In the change amount calculation step, the control unit calculates the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１ Complex difference of |C ｎ -C ｎ＋１ | may be calculated as the amount of change. In this case, the amount of change between the first complex OCT signal and the second complex OCT signal C is calculated appropriately while taking into consideration both the phase information and the amplitude information.

[0019] In the normalization step, the control unit normalizes the first complex OCT signal C ｎ Absolute value of |C ｎ | and the second complex OCT signal C ｎ＋１Absolute value of |C ｎ＋１ |The sum of |C ｎ |+|C ｎ＋１ | as the first complex OCT signal C ｎ and the first complex OCT signal C ｎ＋１ In this case, the control unit can appropriately normalize the amount of change calculated in the amount of change calculation step while maintaining the influence of both the phase information and the amplitude information.

[0020] However, it is also possible to change the specific calculation method of the change amount in the change amount calculation step and the specific normalization method in the normalization step. For example, in the above example, ｎ -C ｎ＋１ |to|C ｎ |+|C ｎ＋１ By dividing by |, it is normalized so that the maximum value is 1. However, it is also possible to normalize so that the maximum value is 1 and the minimum value is 0. As an example, m=||C ｎ |+|C ｎ＋１ ||, M = |C ｎ |+|C ｎ＋１ | and (|C ｎ -C ｎ＋１ |-m) / (M-m), normalization may be performed so that the maximum value is 1 and the minimum value is 0. Furthermore, the process of generating motion contrast data may include a process of calculating at least one of the square of the complex OCT signal and the square of the complex difference.

[0021] The control unit outputs the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１ The control unit may perform a phase difference correction step of correcting the phase difference of each of the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１A change amount calculation step and a normalization step may be performed for the two complex OCT signals. Ideally, the phase difference should be small in areas where blood vessels are not present. However, in reality, even in areas where blood vessels are not present, the phase difference between A-scan lines in each B-scan image generated by each complex OCT signal often becomes large due to fluctuations in the living body. In this case, the quality of the generated motion contrast data decreases. Therefore, correcting the phase difference between each of the two complex OCT signals makes it easier to generate motion contrast data of higher quality.

[0022] FIG. 1 is a block diagram showing a schematic configuration of an OCT device 1. FIG. 2 is an explanatory diagram for explaining an example of a method for acquiring an interference signal for a two-dimensional measurement region 55 on biological tissue. FIG. 3 is an explanatory diagram for explaining an example of a method for acquiring interference signals of a plurality of frames at different times from the same scanning line. FIG. 4 is a flowchart of OCT signal processing executed by the OCT device 1 (OCT signal processing device). FIG. 5 is a diagram showing an example of a comparison result between a B-scan image before phase difference correction and a B-scan image after phase difference correction. FIG. 6 is a diagram showing an example of a result of detecting layers and boundaries from a B-scan image. ｎ , the second complex OCT signal C ｎ＋１ 1 is a diagram showing an example of a relationship between the complex difference of two signals on the complex plane. FIG. 2 is a diagram showing an example of an Enface image generated based on motion contrast data. FIG. 3 is an explanatory diagram for explaining the differences in characteristics between a signal at a non-vascular position, a signal at a vascular position, and noise. FIG. 4 is a graph comparing the value of a normalized complex difference with the value obtained by method Ar when the phase difference is changed while the amplitude value is fixed.

[0023] A typical embodiment according to the present disclosure will be described below. As an example, the OCT apparatus 1 of this embodiment can process OCT signals acquired using biological tissue at the fundus of a subject's eye E as a specimen. However, at least some of the techniques exemplified in this disclosure can also be applied when processing OCT signals from biological tissue other than the fundus of the subject's eye E or biological tissue other than the subject's eye E (e.g., skin, digestive organs, brain, or blood vessels (including cardiovascular vessels)). OCT data is data acquired based on the principles of optical coherence tomography (OCT).

[0024] The schematic configuration of an OCT apparatus 1 according to this embodiment will be described with reference to Fig. 1. The OCT apparatus 1 includes an OCT unit 10 and a control unit 30. The OCT unit 10 includes an OCT light source 11, a coupler (light splitter) 12, a measurement optical system 13, a reference optical system 20, a light receiving element 22, and a front observation optical system 23.

[0025] The OCT light source 11 emits light (OCT light) for acquiring an OCT signal. The coupler 12 splits the OCT light emitted from the OCT light source 11 into measurement light and reference light. The coupler 12 of this embodiment also combines and causes interference between the measurement light reflected by the subject's biological tissue (in this embodiment, the fundus tissue of the subject's eye E) and the reference light generated by the reference optical system 20. That is, the coupler 12 of this embodiment serves both as a branching optical element that branches the OCT light into measurement light and reference light, and as a combining optical element that combines the reflected light of the measurement light with the reference light. It is also possible to change the configuration of at least one of the branching optical element and the combining optical element. For example, elements other than a coupler (e.g., a circulator, a beam splitter, etc.) may be used.

[0026] The measurement optical system 13 guides the measurement light split by the coupler 12 to the subject and returns the measurement light reflected by the subject to the coupler 12. The measurement optical system 13 includes a scanning unit 14, an irradiation optical system 16, and a focus adjustment unit 17. The scanning unit 14 is driven by a driving unit 15 to scan (deflect) the measurement light in a two-dimensional direction intersecting the optical axis of the measurement light. In this embodiment, two galvanometer mirrors capable of deflecting the measurement light in different directions are used as the scanning unit 14. However, another device for deflecting light (e.g., at least one of a polygon mirror, a resonant scanner, an acousto-optical element, etc.) may also be used as the scanning unit 14. The irradiation optical system 16 is located downstream of the scanning unit 14 in the optical path (i.e., on the subject side) and irradiates the measurement light onto the subject's tissue. The focus adjustment unit 17 adjusts the focus of the measurement light by moving optical components (e.g., lenses) included in the irradiation optical system 16 in a direction along the optical axis of the measurement light.

[0027] The reference optical system 20 generates reference light and returns it to the coupler 12. In this embodiment, the reference optical system 20 generates the reference light by reflecting the reference light split by the coupler 12 using a reflective optical system (e.g., a reference mirror). However, the configuration of the reference optical system 20 can also be changed. For example, the reference optical system 20 may transmit the light incident from the coupler 12 without reflecting it and return it to the coupler 12. The reference optical system 20 includes an optical path length difference adjustment unit 21 that changes the optical path length difference between the measurement light and the reference light. In this embodiment, the optical path length difference is changed by moving the reference mirror in the optical axis direction. Note that the configuration for changing the optical path length difference may be provided in the optical path of the measurement optical system 13.

[0028] The light-receiving element 22 detects an interference signal by receiving interference light between the measurement light and the reference light generated by the coupler 12. In this embodiment, the principle of Fourier-domain OCT is adopted. In Fourier-domain OCT, the spectral intensity of the interference light (spectral interference signal) is detected by the light-receiving element 22, and a complex OCT signal is acquired by Fourier transforming the spectral intensity data. Examples of Fourier-domain OCT that can be adopted include spectral-domain OCT (SD-OCT) and swept-source OCT (SS-OCT). It is also possible to adopt, for example, time-domain OCT (TD-OCT).

[0029] In this embodiment, SD-OCT is employed. In the case of SD-OCT, for example, a low-coherence light source (broadband light source) is used as the OCT light source 11, and a spectroscopic optical system (spectrometer) that separates the interference light into individual frequency components (individual wavelength components) is provided near the light-receiving element 22 in the optical path of the interference light. In the case of SS-OCT, for example, a wavelength-scanning light source (tunable light source) that changes the emission wavelength at high speed over time is used as the OCT light source 11. In this case, the OCT light source 11 may include a light source, a fiber ring resonator, and a wavelength-selective filter. Examples of wavelength-selective filters include a filter that combines a diffraction grating and a polygon mirror, and a filter that uses a Fabry-Perot etalon.

[0030] Furthermore, in this embodiment, three-dimensional OCT data (e.g., a three-dimensional tomographic image) is acquired by scanning a measurement light spot within a two-dimensional measurement region using the scanning unit 14. However, the principle for acquiring three-dimensional OCT data can be changed. For example, three-dimensional OCT data may be acquired using the principle of line-field OCT (hereinafter referred to as "LF-OCT"). In LF-OCT, measurement light is simultaneously irradiated onto an irradiation line extending in a one-dimensional direction in tissue, and the reflected light of the measurement light and the interference light of the reference light are received by a one-dimensional light-receiving element (e.g., a line sensor) or a two-dimensional light-receiving element. Three-dimensional OCT data is acquired by scanning the measurement light in a direction intersecting the irradiation line within the two-dimensional measurement region. Alternatively, three-dimensional OCT data may be acquired using the principle of full-field OCT (hereinafter referred to as "FF-OCT"). In FF-OCT, a measurement light is irradiated onto a two-dimensional measurement area on tissue, and the interference light between the reflected light of the measurement light and the reference light is received by a two-dimensional light-receiving element. In this case, the OCT apparatus 1 does not need to include the scanning unit 14.

[0031] The front observation optical system 23 is provided to capture a front observation image of a biological tissue of a subject (in this embodiment, the fundus of the subject's eye E) in real time. The front observation image in this embodiment is a two-dimensional image of the tissue when viewed from a direction along the optical axis of the OCT measurement light (the front direction). In this embodiment, a scanning laser ophthalmoscope (SLO) is used as the front observation optical system 23. However, the front observation optical system 23 may be configured with a configuration other than an SLO (for example, an infrared camera that captures a front image by irradiating a two-dimensional imaging range with infrared light all at once).

[0032] Furthermore, the OCT device 1 can acquire (generate) an enface image, which is a two-dimensional front image of tissue viewed from the direction along the optical axis of the measurement light (front direction), based on the acquired three-dimensional OCT data. When an enface image is acquired in real time, the acquired enface image can also be used as the aforementioned front observation image. In this case, the front observation optical system 23 can be omitted. The enface image data can be, for example, integrated image data in which brightness values ​​are integrated in the depth direction (Z direction) at each position in the X and Y directions, integrated values ​​of spectral data at each position in the X and Y directions, brightness data at each position in the X and Y directions at a certain depth direction, or brightness data at each position in the X and Y directions in any layer of the retina (e.g., the retinal surface). The OCT device 1 of this embodiment can also generate an enface image from motion contrast data. Motion contrast data is data obtained by processing multiple OCT signals acquired at different times from the same position on biological tissue. The motion contrast data represents information on the movement of biological tissue (for example, the movement of blood flow in blood vessels in biological tissue). In this embodiment, an enface image of a specific layer is generated based on the motion contrast data, thereby generating an angiography image (blood vessel image) that indicates the positions of blood vessels included in the specific layer.

[0033] The control unit 30 is responsible for various controls of the OCT apparatus 1. The control unit 30 includes a CPU 31, a RAM 32, a ROM 33, and a non-volatile memory (NVM) 34. The CPU 31 is a controller that performs various controls. The RAM 32 temporarily stores various information. The ROM 33 stores programs executed by the CPU 31, various initial values, etc. The NVM 34 is a non-transitory storage medium that can retain its contents even when the power supply is cut off. An OCT signal processing program for executing OCT signal processing (see FIG. 4 ), which will be described later, may be stored in the NVM 34.

[0034] A microphone 36, a monitor 37, and an operation unit 38 are connected to the control unit 30. The microphone 36 inputs sound. The monitor 37 is an example of a display unit that displays various images. The operation unit 38 is operated by a user to input various operation instructions to the OCT apparatus 1. The operation unit 38 may be various devices, such as a mouse, a keyboard, a touch panel, or a foot switch. Note that various operation instructions may be input to the OCT apparatus 1 by inputting sound into the microphone 36. In this case, the CPU 31 may determine the type of operation instruction by performing voice recognition processing on the input sound.

[0035] In this embodiment, an integrated OCT device 1 in which the OCT unit 10 and the control unit 30 are built into a single housing is illustrated. However, it goes without saying that the OCT device 1 may include multiple devices housed in different housings. For example, the OCT device 1 may include an optical device incorporating the OCT unit 10 and a PC connected to the optical device via a wired or wireless connection. In this case, the control unit of the optical device and the control unit of the PC may both function as the control unit 30 of the OCT device 1. Furthermore, the OCT device 1 of this embodiment functions both as the OCT unit 10 that acquires interference signals about biological tissue and as an OCT signal processing device that processes the acquired interference signals or OCT signals. However, an OCT signal processing device may be used separately from the OCT device 1 that acquires the interference signals. In this case, the OCT signal processing device may acquire the interference signals or OCT signals about biological tissue acquired by the OCT device 1 via wired communication, wireless communication, a network, a removable storage device, or the like, and process the acquired signals to generate motion contrast data. In this case, the OCT signal processing described below may be performed by a control unit of the OCT signal processing device.

[0036] 2 and 3 , an example of a method by which the OCT apparatus 1 acquires an interference signal for biological tissue will be described. First, the CPU 31 controls the front observation optical system 23 to start capturing a two-dimensional front image of the biological tissue (in this embodiment, the fundus of the subject's eye E) from which an interference signal is to be acquired. In the example shown in Fig. 2 , the optic disc (hereinafter sometimes referred to as "disc") 51, macula 52, and fundus blood vessels 53 of the subject's eye E are captured in the two-dimensional front image 50. The two-dimensional front image 50 is repeatedly and intermittently captured and displayed as a moving image on the monitor 37.

[0037] The CPU 31 acquires an interference signal for a measurement region 55 on biological tissue when a trigger signal for starting acquisition of the interference signal is generated. In this embodiment, the CPU 31 controls the driving of the scanning unit 14 by the driving unit 15, and causes the measurement light spot to scan within the two-dimensional measurement region 55, thereby acquiring an interference signal for the measurement region 55. As an example, in this embodiment, as shown in FIG. 3 , a plurality of linear scanning lines (scan lines) 58 for scanning the spot are set at equal intervals within the measurement region 55, and the measurement light spot is scanned on each scanning line 58, thereby acquiring an interference signal for the two-dimensional measurement region 55.

[0038] Specifically, the CPU 31 acquires at least two frames of interference signals from the same position on the biological tissue (the same scanning line 58 in the example shown in FIG. 3 ) at different times. In the example shown in FIG. 3 , the CPU 31 first scans the first scanning line 58 of the multiple scanning lines 58 with the measurement light, thereby acquiring an interference signal detected by the light-receiving element 22. Hereinafter, the direction in which the scanning lines 58 extend is referred to as the X direction. Scanning each scanning line 58 with the measurement light in the X direction once is referred to as a "B scan." A two-dimensional image generated by a B scan is referred to as a "B-scan image." In the B-scan image, each of multiple pixel rows extending in the direction along the optical axis of the measurement light is referred to as an "A-scan image." Hereinafter, one frame of interference signal will be described as an interference signal acquired by one B scan. The Z direction is referred to as the direction along the optical axis of the measurement light. The Y direction is a direction intersecting both the X direction and the Z direction (in this embodiment, a direction perpendicular to the X direction).

[0039] When the first B-scan for the first scanning line 58 is completed, the CPU 31 acquires a second frame of interference signals by executing a second B-scan on the first scanning line 58. As a result, as shown in Fig. 3, two frames of interference signals are acquired at different times from the first scanning line 58. Note that the CPU 31 can also acquire three or more frames of interference signals from the same position (for example, on the same scanning line 58).

[0040] Note that, if it is possible to acquire interference signals of multiple frames at different times from the same scanning line 58 by scanning the measurement light once on the scanning line 58, there is no need to scan the measurement light multiple times on the same scanning line 58. For example, if two measurement light beams whose optical axes are shifted by a predetermined interval are scanned at once, there is no need to scan the measurement light multiple times on the same scanning line 58.

[0041] Upon completing acquisition of interference signals for multiple frames from the first scanning line 58, the CPU 31 moves the position where the B scan is performed parallel to the Y direction and executes processing for acquiring interference signals for multiple frames from the second scanning line 58. The above processing is executed for each of the multiple scanning lines 58, thereby acquiring interference signals for the two-dimensional measurement region 55. Note that the directions of the first B scan and the second B scan on the same scanning line 58 may be reversed, or multiple B scans may be repeated in the same direction.

[0042] <OCT Signal Processing> OCT signal processing performed by an OCT signal processing device (OCT device 1 in this embodiment) will be described with reference to Figures 4 to 8. In the OCT signal processing, an interference signal acquired from biological tissue is processed by the OCT unit 10 of the OCT device 1 to generate motion contrast data of the biological tissue. The CPU 31 of the OCT device 1 performs the OCT signal processing shown in Figure 4 in accordance with an OCT signal processing program stored in the NVM 34.

[0043] 4, the CPU 31 acquires an interference signal obtained from the biological tissue by the OCT unit 10 (S1). The CPU 31 then performs a Fourier transform on the interference signal obtained in S1 to obtain a complex OCT signal (S2). As described above, in this embodiment, the first interference signal I is obtained from each of a plurality of positions on the biological tissue at different times. ｎ and the second interference signal I ｎ＋１ The first interference signal I ｎ is Fourier transformed to obtain the first complex OCT signal C ｎ (Amplitude A ｎ , phase θ ｎ ) is obtained. ｎ＋１ is Fourier transformed to obtain a second complex OCT signal C ｎ＋１ (Amplitude A ｎ＋１ , phase θ ｎ＋１ ) is obtained.

[0044] The CPU 31 calculates the first complex OCT signal C obtained at different times from the same position on the biological tissue. ｎ and the second complex OCT signal C ｎ＋１In this embodiment, the CPU 31 performs image registration (S3) of multiple images of the same scene (first complex OCT signal C ｎ and a second complex OCT signal C ｎ＋１ In order to properly generate motion contrast data indicating tissue movement (blood flow in this embodiment), it is necessary to compare signals acquired at different times from the same position. However, due to the movement of the biological tissue during imaging, etc., the first complex OCT signal C ｎ and the position where the second complex OCT signal C ｎ＋１ Therefore, the CPU 31 may acquire the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１ By performing the registration, the quality of the motion contrast data is improved.

[0045] The CPU 31 receives the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１ The phase difference between the A-scan lines is corrected (S4). Ideally, the phase difference should be small in a region where no blood vessels exist (non-vascular region). However, in reality, even in a region where no blood vessels exist, the phase difference between the A-scan lines in each B-scan image generated by each complex OCT signal is often large due to fluctuations in the living body. In this case, the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１Even if the alignment is performed, the quality of the generated motion contrast data will be reduced. In contrast, reducing the phase difference in the non-vascular region by the process of S4 makes it easier to generate motion contrast data of higher quality. The specific method of the process of S4 can be selected as appropriate. For example, the CPU 31 may calculate and integrate the complex conjugate product for each pixel of the A-scan to calculate the deflection angle. The calculated deflection angle becomes the phase difference of the entire A-scan. The CPU 31 may correct the phase difference by moving the OCT complex signal at time t by the calculated phase difference. Figure 5 shows an example of a comparison result between a B-scan image before phase difference correction and a B-scan image after phase difference correction.

[0046] The CPU 31 generates the plurality of images (first complex OCT signal C ｎ and a second complex OCT signal C ｎ＋１ A segmentation process is then performed to detect at least one of the layers and boundaries of biological tissue (in this embodiment, the layers and boundaries of the fundus tissue) from at least a portion of the B-scan image (S5). The results of the segmentation process obtained in S5 are used, for example, to generate an enface image of one or more specific layers in the process of S8, which will be described later. Figure 6 shows an example of the results of detecting multiple layers and boundaries from a B-scan image.

[0047] As an example, this embodiment uses a mathematical model trained by a machine learning algorithm. The mathematical model is pre-trained with multiple training data sets including B-scan images so that, when a B-scan image is input, it outputs a detection result of layers and boundaries shown in the input B-scan image. The CPU 31 inputs the B-scan image into the mathematical model to obtain a detection result of layers and boundaries in the B-scan image. However, other methods (e.g., methods using known image processing) can also be used for the segmentation processing method. Furthermore, in S5, the CPU 31 may detect layers and boundaries in an averaged image obtained by adding (or averaging) the multiple images aligned in S3. In this case, the noise in the B-scan image from which layers and boundaries are to be detected is reduced compared to the noise in the B-scan image before addition. This makes it easier to detect layers and boundaries with higher accuracy.

[0048] The CPU 31 receives the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１ The amount of change calculated in S6 is the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１ is not only the change in amplitude of the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１ The change amount calculated in S6 is not the change amount only in the phase of the two complex OCT signals. In other words, the change amount calculated in S6 is the change amount between the two complex OCT signals. Therefore, the change amount calculated in S6 reflects both the amplitude information and the phase information of the two complex OCT signals.

[0049] As an example, in S6 of this embodiment, the CPU 31 calculates the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１ Complex difference of |C ｎ -C ｎ＋１ | is calculated as the amount of change between the two complex OCT signals. As shown in FIG. 7 , the complex OCT signal can be expressed on a complex plane with one axis (horizontal axis Re) as the real axis and the other axis (vertical axis Im) as the imaginary axis. As shown in FIG. 7 , the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１The complex difference of Φ reflects both the amplitude and phase information of the two complex OCT signals. ｎ is the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１ The complex difference can be calculated by the following (Equation 1). However, instead of the complex difference itself, the result of some further calculation using the complex difference may be used as the amount of change between the two complex OCT signals.

[0050] Here, the first complex OCT signal C calculated in S6 ｎ and the second complex OCT signal C ｎ＋１ It is also possible to generate motion contrast data using the amount of change (complex difference in this embodiment) between

[0049] and

[0150] . However, since the amount of change calculated in S6 is not normalized by the magnitude of the signal, artifacts are likely to appear in areas with high brightness even if there is no actual movement of the subject.

[0051] Therefore, the CPU 31 converts the amount of change calculated in S6 into the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１ , and motion contrast data is generated using the normalized value (S7). As a result, the amount of change calculated in S6 is normalized while maintaining the influence of both the phase information and the amplitude information, thereby generating motion contrast data. Note that the processes of S1 to S7 are repeatedly performed for each of the multiple scan lines 58 (see FIG. 2), thereby generating motion contrast data for the entire two-dimensional measurement region 55.

[0052] An example of the specific process of S7 will be described. The complex difference shown in (Equation 1) is expressed as "Φ ｎ When "=±π", the maximum value shown in (Equation 2) is reached.

[0053] "A ｎ +A ｎ＋１ =|C ｎ |+|C ｎ＋１ Therefore, as shown in (Equation 3), the complex difference calculated in S6 is expressed as "|Cｎ |+|C ｎ＋１ By dividing by "|", it is possible to normalize the maximum value to "1". However, it is also possible to change the processing method in S7. For example, the normalization method in S7 may be changed as appropriate depending on the method for calculating the amount of change in S6.

[0054] Furthermore, the CPU 31 applies smoothing, noise removal, etc. to the motion contrast data generated in the processes of S6 and S7. For example, the motion contrast data may be filtered by at least one of a Gaussian filter, a box filter, a bilateral filter, etc. Alternatively, for example, after filtering the numerator and denominator of (Equation 3) with various filters, the numerator may be divided by the denominator.

[0055] The CPU 31 generates an enface image (angiography image) of one or more specific layers based on the segmentation result acquired in S5 (S8). As an example, in the process of S8, the CPU 31 may generate a cross-sectional vascular image based on motion contrast data generated for each scan line 58. The CPU 31 may identify a specific layer from the cross-sectional vascular image based on the segmentation result, and generate an enface image of the specific layer by integrating the pixel values ​​of the identified specific layer in the Z direction or by taking the maximum pixel value of the specific layer in the Z direction. It goes without saying that the CPU 31 may generate enface images for all layers of the fundus.

[0056] (Explanation of Acquired Motion Contrast Data) The characteristics of motion contrast data (data obtained by normalized complex difference) generated by OCT signal processing of this embodiment will be described. First, the technical background will be described with reference to FIG. 9 . As shown in FIG. 9A , when multiple complex OCT signals are acquired at a non-vascular position, the amplitude of each signal tends to be large, the amplitude change between the multiple signals tends to be small, and the phase change between the multiple signals also tends to be small. As shown in FIG. 9B , when multiple complex OCT signals are acquired at a vascular position, the amplitude of each signal, the amplitude change between the multiple signals, and the phase change between the multiple signals all tend to be large. Furthermore, as shown in FIG. 9C , when focusing on each noise in multiple OCT signals acquired from the same position at different times, the amplitude of each noise tends to be small, but the amplitude change between the multiple noises and the phase change between the multiple noises both tend to be large. As described above, both the amplitude characteristics and the phase characteristics differ between the signal at the non-vascular position, the signal at the vascular position, and the noise. Therefore, if motion contrast data is generated using only one of the amplitude and phase information, it is likely to be difficult to appropriately distinguish between signals at non-vascular locations, signals at vascular locations, and noise.

[0057] In contrast, in the OCT signal processing of this embodiment, the amount of change calculated in S6 is normalized in S7 while maintaining the influence of both the phase information and the amplitude information, thereby generating motion contrast data. That is, motion contrast data that reflects both the phase information and the amplitude information is generated. Therefore, the quality of the motion contrast data is improved compared to when only one of the amplitude and phase information is used.

[0058] Furthermore, the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１The variation between the OCT signals (in this embodiment, the variation calculated by the process in S6) is easily affected by the sensitivity of the complex OCT signal. Therefore, if the variation between multiple signals is used to generate motion contrast data without normalization, strong signals in high-brightness regions may appear as artifacts in the motion contrast data even when there is no actual subject movement. In this case, it becomes difficult to distinguish between artifacts in high-brightness regions and actual vascular regions. Therefore, we consider multiplying first motion contrast data generated based on the variation between multiple OCT signals with second motion contrast data that is independent of the magnitude of the OCT signals. In this case, the sensitivity of the first motion contrast data is high. On the other hand, the sensitivity of the second motion contrast data is inevitably low. Therefore, when the two data are multiplied, although artifacts in high-brightness regions may be reduced, the overall sensitivity decreases. As a result, there is a high possibility that actually connected vascular regions will be disconnected.

[0059] In contrast, in the OCT signal processing of this embodiment, the amount of change calculated in S6 is properly normalized in S7 to generate motion contrast data while maintaining high sensitivity, making it easier to generate better motion contrast data.

[0060] Furthermore, the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１ It is also possible to first normalize each of the two complex OCT signals by signal magnitude, and then calculate the amount of change in the magnitude-normalized values. However, if each of the two complex OCT signals is normalized by magnitude before calculating the amount of change, amplitude information is lost at that point, and motion contrast data based only on phase information is generated. Motion contrast data based only on phase information is prone to noise. In particular, when generating motion contrast images of still images, it is more desirable to use both amplitude information and phase information. In contrast, the OCT signal processing of this embodiment generates motion contrast data that reflects both phase information and amplitude information and has high sensitivity.

[0061] Furthermore, the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１ There is also known a method (hereinafter referred to as "method Ar") in which the length of the arc formed on the complex plane by is calculated based on (Equation 4) and motion contrast data is generated based on the calculation result.

[0062] In (Equation 4), both amplitude and phase difference are used. However, in Method Ar, the phase difference Φ ｎ In particular, with method Ar, if the phase difference is small, the motion contrast value will be small even if the amplitude difference is very large, and good motion contrast data may not be obtained.

[0063] FIG. 10 is a graph comparing the change in motion contrast data (data based on normalized complex difference) generated by the OCT signal processing of this embodiment with the change in motion contrast data based on method Ar when the phase difference is changed while the amplitude value is fixed. In FIGS. 10A and 10B, the vertical axis represents the normalized data value, and the horizontal axis represents the phase difference. As shown in FIG. 10, when comparing the data based on method Ar for a large amplitude difference (FIG. 10A) and a small amplitude difference (FIG. 10B) at the same phase difference, the value in FIG. 10B, where the amplitude difference is small, is conversely larger than the value in FIG. 10A, where the amplitude difference is large. This characteristic is undesirable for motion contrast data used to visualize signal changes. Furthermore, in the data based on method Ar, the value of the data when the phase difference is "0" is "0" both when the amplitude difference is large (FIG. 10A) and when the amplitude difference is small (FIG. 10B). In other words, in the data obtained by method Ar, when the phase difference is 0, the value becomes 0 regardless of the amplitude difference. As described above, the data obtained by method Ar is sensitive to the phase difference.

[0064] In contrast, when focusing on data based on normalized complex differences, when the amplitude difference is large (as in FIG. 10A ), the value is always large regardless of the phase difference, and the value increases or decreases gradually as the phase difference increases or decreases. On the other hand, when the amplitude difference is small (as in FIG. 10B ), the value increases or decreases significantly as the phase difference increases or decreases, and approaches “0” only when both the amplitude difference and the phase difference become small. As described above, the motion contrast data generated by the OCT signal processing of this embodiment is data that appropriately reflects both the amplitude difference and the phase difference.

[0065] The techniques disclosed in the above embodiments are merely examples. Therefore, it is possible to change the techniques exemplified in the above embodiments. For example, it is possible to execute only some of the techniques exemplified in the above embodiments. Furthermore, in the processes of S6 and S7 in the above embodiments, the complex difference |C ｎ -C ｎ＋１ |to|C ｎ |+|C ｎ＋１ By dividing by |, it is normalized so that the maximum value is 1. However, it is also possible to normalize so that the maximum value is 1 and the minimum value is 0. As an example, ｎ |+|C ｎ＋１ ||", "M = |C ｎ |+|C ｎ＋１ |" and calculate the following (Equation 5), normalization may be performed so that the maximum value is 1 and the minimum value is 0. Furthermore, the process of calculating at least one of the square of the complex OCT signal and the square of the complex difference may be included in the process of generating motion contrast data.

[0066] The process of calculating the amount of change between multiple complex OCT signals in S6 in Fig. 4 is an example of a "change amount calculation step." The process of normalizing the amount of change in S7 is an example of a "normalization step." The process of correcting the phase difference in S4 is an example of a "phase difference correction step."

Claims

1. An OCT device comprising: an OCT unit that detects an OCT signal by a reference light and a measurement light irradiated onto a biological tissue of a subject; and a control unit that processes the OCT signal to generate motion contrast data in the biological tissue, the control unit being configured to: generate a first complex OCT signal C obtained at different times from the same position on the biological tissue; ｎ and the second complex OCT signal C ｎ＋１ a change amount calculation step of calculating a change amount between the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１ and a normalization step of generating the motion contrast data by normalizing the motion contrast data based on the magnitude of the motion contrast data.

2. The OCT apparatus according to claim 1, wherein the control unit calculates the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１ Complex difference of |C ｎ -C ｎ＋１ | as the amount of change.

3. The OCT apparatus according to claim 1 or 2, wherein the control unit, in the normalization step, ｎ Absolute value of |C ｎ | and the second complex OCT signal C ｎ＋１ Absolute value of |C ｎ＋１ | of | C ｎ |+|C ｎ＋１ | the first complex OCT signal C ｎ and the first complex OCT signal C ｎ＋１ The OCT apparatus is characterized in that the amount of change is normalized as the magnitude of the change.

4. An OCT apparatus according to any one of claims 1 to 3, wherein the control unit is configured to: ｎ and the second complex OCT signal C ｎ＋１ a phase difference correction step of correcting the phase difference of each of the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１ The OCT apparatus is characterized in that the change amount calculation step and the normalization step are performed on the basis of the above.

5. An OCT signal processing program executed by an OCT signal processing device that processes an OCT signal generated by a reference light and a measurement light irradiated onto a biological tissue of a subject, the OCT signal processing program being executed by a control unit of the OCT signal processing device, thereby obtaining a first complex OCT signal C obtained at different times from the same position on the biological tissue. ｎ and the second complex OCT signal C ｎ＋１ a change amount calculation step of calculating a change amount between the first complex OCT signal C ｎ and the second complex OCT signal C ｎ＋１ a normalization step of generating the motion contrast data by normalizing the motion contrast data based on the magnitude of the motion contrast data; and

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