A medical image artifact suppression method, system, terminal and medium

Abstract

The application discloses an artifact suppression method, system, terminal and medium of medical images, and the method comprises the following steps: acquiring a medical image obtained by scanning a measured person; determining a heartbeat-related time-varying signal of the measured person according to the medical image; and increasing the scanning times according to the heartbeat-related time-varying signal to suppress the artifact of the medical image. By determining the heartbeat-related time-varying signal and increasing the scanning times, the artifact of the medical image caused by the heartbeat can be greatly reduced, including the bright line artifact signal phenomenon of the fundus OCTA.

Description

Technical Field

[0001] This application relates to the field of medical technology, and more specifically, to a method, system, terminal, and medium for suppressing artifacts in medical images. Background Technology

[0002] Medical imaging plays an increasingly important role in current medical diagnosis; however, various interferences often lead to inaccurate or low-quality images during the current medical image acquisition process. For example, the periodic vasoconstriction and vasodilation caused by the human heartbeat can create artifacts in some medical images related to vasoconstriction and vasodilation.

[0003] OCTA is a non-invasive, novel fundus imaging technique that can identify retinal vascular structures at high resolution. Due to its fast and clear imaging capabilities, OCTA offers unique advantages in the management, follow-up, and monitoring of retinal vascular changes and diseases, as well as in assessing treatment effectiveness.

[0004] During retinal OCT imaging, the acquisition time for one frame of a B-scan image is approximately 5ms to 50ms. During this period, the periodic vasoconstriction and vasodilation caused by the heartbeat can lead to uncontrollable eye movements. These eye movements cause OCTA artifacts, manifesting as bright stripe artifacts, image misalignment, missing blood vessels, stretching or distortion, and uneven brightness. OCTA artifacts and image quality issues can easily lead to misdiagnosis during medical examinations.

[0005] Currently, high-speed ophthalmoscopes are used to monitor eye movements in real time and feed the images back to the OCT scanning system for fundus tracking, which can eliminate the problems of discontinuity and fragmentation in OCT images. However, due to the frame rate limitations of ophthalmoscopes, the tracking timeliness is insufficient to solve artifacts such as OCTA bright lines caused by heartbeats. Summary of the Invention

[0006] In view of the deficiencies in the prior art, the purpose of this application is to provide a method, system, terminal and medium for suppressing artifacts in medical images.

[0007] One aspect of this application provides a method for suppressing artifacts in medical images, comprising:

[0008] Acquire medical images of the subject by scanning, and determine the subject's heart rate-related time change signal based on the medical images;

[0009] The number of scans is increased based on the heart rate-related time variation signal to suppress artifacts in medical images.

[0010] Optionally, the medical image includes: B-scan image; determining the subject's heart rate-related time change signal based on the medical image includes:

[0011] Based on the B-scan image, the heart rate-related time change signal of the subject is demodulated, wherein the heart rate-related time change signal includes the timing of the peaks and troughs of eye movement displacement caused by heartbeat.

[0012] Optionally, increasing the number of scans based on the heartbeat-related time change signal includes:

[0013] Based on the timing of the peaks and troughs of eye movement displacement caused by the heartbeat, determine the time points corresponding to the peaks and troughs of eye movement displacement caused by the heartbeat.

[0014] When scanning the subject, the number of scans is increased according to the time points corresponding to the peaks and troughs of the eye movement displacement.

[0015] Optionally, when scanning the subject, increasing the number of scans based on the time points corresponding to the peaks and troughs of the eye movement displacement includes:

[0016] When performing an OCT scan on the fundus of the subject, at the B-scan scan positions corresponding to the time points corresponding to the peaks and troughs, a first number and a second number of adjacent B-scan scan positions are selected.

[0017] The number of OCT scans is increased at the selected first and second number of B-scan scan locations.

[0018] Optionally, the first quantity and the second quantity are the same and both are M. Further, M = (frequency bandwidth coefficient * period of heartbeat-related time change signal) / B-scan scan period of OCT scanning system.

[0019] Optionally, demodulating the subject's heart rate-related time-varying signal includes:

[0020] Obtain the centroid axial position of the B-scan image;

[0021] A spectral analysis is performed on the axial position of the center of gravity along time, and the maximum dominant frequency signal is obtained in the spectral analysis as the heartbeat-related time variation signal.

[0022] A second aspect of this application provides a medical image artifact suppression system, comprising:

[0023] First determining module: acquires medical images obtained from scanning the subject, and determines the subject's heart rate-related time change signal based on the medical images;

[0024] Scan control module: Increases the number of scans based on the heart rate-related time change signal to suppress artifacts in medical images.

[0025] A third aspect of this application provides a terminal, comprising:

[0026] At least one memory for storing program instructions;

[0027] At least one processor is configured to invoke program instructions stored in the memory and execute the steps of the above-described method for suppressing artifacts in medical images according to the obtained program instructions.

[0028] A fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method for suppressing artifacts in medical images.

[0029] The artifact suppression method for medical images described in this application can greatly reduce artifacts caused by heartbeat by increasing the number of scans near the time point of vasoconstriction and vasodilation. For example, increasing the number of OCTA scans near the time point of vasoconstriction and vasodilation can greatly reduce the false signal phenomenon of bright lines in fundus OCTA caused by heartbeat, thereby reducing disease misdiagnosis in the medical examination process. Attached Figure Description

[0030] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0031] Figure 1 A schematic diagram of OCTA image artifacts caused by heartbeat;

[0032] Figure 2 A flowchart of a method for suppressing artifacts in medical images provided as an exemplary embodiment of this application;

[0033] Figure 3 This is a diagram showing the correspondence between heart rate-related time signals and B-scan scan sequences in an exemplary embodiment of this application.

[0034] Figure 4 This is a flowchart illustrating the scanning and feedback control operation of an exemplary embodiment of this application;

[0035] Figure 5 This is a comparison diagram showing the effect before and after removal of artifacts caused by OCTA image center jump in an exemplary embodiment of this application;

[0036] Figure 6 A block diagram of a medical image artifact suppression system provided for an exemplary embodiment of this application. Detailed Implementation

[0037] The present application will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present application, but do not limit the present application in any way. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present application. These all fall within the protection scope of the present application.

[0038] This application provides a method for suppressing artifacts in medical images, including: acquiring medical images of a scanned subject; determining the subject's heart rate-related time change signal based on the medical images; and increasing the number of scans based on the heart rate-related time change signal to suppress artifacts in the medical images. By increasing the number of scans based on the heart rate-related time change signal, artifacts caused by heartbeats can be significantly reduced.

[0039] In one possible embodiment, the medical image includes a B-scan image. Of course, in other embodiments, it could also be other medical images that may exhibit artifacts due to heartbeat.

[0040] like Figure 1 The image shows OCTA image artifacts caused by heartbeats. The white lines represent the displacement peaks and troughs corresponding to vascular contraction and dilation, respectively, and their locations in the 3D OCTA scan. Heartbeats cause displacements of up to 100μm in the B-scan image. Repeated OCT scans result in OCTA images with bright stripe artifacts, discontinuous vascular images, and uneven signal intensity. To address these issues, high-speed ophthalmoscopes are used to monitor eye movements in real time and feed this information back to the OCT scanning system, enabling fundus tracking and eliminating discontinuities and breaks in the OCT images. However, since the frame rate of ophthalmoscopes is generally limited to a maximum of 50fps, the tracking timeliness is insufficient to resolve the bright stripe artifacts caused by heartbeats in OCTA. Therefore, OCTA artifacts and image quality issues may still lead to misdiagnosis during medical examinations.

[0041] To address issues such as motion artifacts caused by heartbeats in OCTA images, this application proposes a method for suppressing artifacts in medical images that suppress bright line artifacts in ophthalmic OCTA.

[0042] Figure 2 A flowchart illustrating a method for suppressing ophthalmic OCTA bright line spurious signals, provided as an exemplary embodiment of this application. In this embodiment, the method for suppressing OCTA bright line spurious signals includes steps S100-S200:

[0043] S100: Acquire medical images of the subject obtained from scanning, and determine the subject's heart rate-related time change signal based on the medical images;

[0044] Among them, the time-related change signal of heartbeat can include the timing of the peaks and troughs of eye movement caused by heartbeat, or the timing of vasoconstriction and vasodilation, which are equivalent.

[0045] Specifically, medical imaging can include B-scan images, such as OCT and OCTA B-scan images, which can acquire OCT B-scan images of the subject's fundus and determine the subject's heart rate-related time change signals based on the B-scan images.

[0046] In this step, OCT B-scan images of the subject's fundus can be pre-acquired using a standard scanning method. A standard scanning method means that the same number of scans is performed at all locations or time points during the OCT B-scan scan. For the subject, it is important to maintain a stable physical condition during the scan, avoiding extreme physical states, to prevent the B-scan images from indicating that the subject's heart rate-related time-varying signals are not normal or regular heart rate changes.

[0047] In this step, determining the subject's heart rate-related temporal variation signal based on B-scan images is crucial for controlling the scanning parameters at the heart rate-related vasoconstriction and vasodilation time points in subsequent steps, thus resolving motion artifacts and other issues caused by heartbeat in OCTA images. There are many possible methods for determining the subject's heart rate-related temporal variation signal based on B-scan images, such as image processing methods, waveform analysis methods, and machine learning methods.

[0048] In one possible implementation, the subject's heart rate-related time variation signal can be determined based on the timing of the peaks and troughs of the eye movement displacement caused by the heartbeat. Therefore, this can be achieved through the following methods, specifically including steps S101-S102:

[0049] S101, Based on the pre-acquired B-scan image, demodulate the subject's heartbeat-related time change signal, which includes the peak and trough timing of eye movement displacement caused by heartbeat;

[0050] To more accurately demodulate the temporal variation signal related to the subject's heartbeat, a preferred embodiment can employ spectral analysis. Specifically, this preferred embodiment includes: acquiring the centroidal axial position of the B-scan image, performing spectral analysis on the acquired centroidal axial position over time, and extracting the amplitude, frequency, and phase of the maximum dominant frequency signal in the spectral analysis to obtain the peak and trough timing of the eye movement displacement caused by the heartbeat.

[0051] In the preferred embodiment described above, the centroid axial position of the pre-real-time acquired B-scan image is obtained, and spectral analysis is performed on the obtained centroid axial position. Spectral analysis involves decomposing the periodic signal into a combination of sine waves with different frequencies, amplitudes, and initial phases to obtain the amplitude A0, frequency f0, and initial phase φ0 of the maximum dominant frequency signal. Existing technologies can be used for spectral analysis, such as Fourier transform, wavelet transform, etc. The specific method can be chosen based on the actual situation and is not limited here.

[0052] In the preferred embodiment described above, obtaining the centroid axial position of the B-scan image can be achieved through algorithms such as grayscale distribution analysis and edge detection. For example, the grayscale centroid method can be used. The grayscale centroid method is an algorithm based on the distribution of grayscale values ​​in an image, used to calculate the centroid position of a region or object in an image. By converting the image to a grayscale image, calculating the grayscale centroid, and extracting the centroid axial position, the centroid position information of the region or object in the image can be obtained. Specifically, in one embodiment, for each OCT B-Scan image, the centroid axial position of the B-scan image can be obtained by calculating the grayscale centroid through the following steps:

[0053] S1011, Convert image to grayscale: Convert the original RGB image to a grayscale image, with grayscale values ​​typically ranging from 0 (black) to 255 (white).

[0054] S1012, Calculate the grayscale centroid: Calculate the grayscale centroid of the grayscale image. The grayscale centroid is a parameter used to describe the position of the centroid of the entire image or a portion of the image region; it reflects the distribution of pixels with the same grayscale value. The grayscale centroid can be obtained by calculating the geometric center of the pixel corresponding to each grayscale value.

[0055] S1013, Determine the centroid axis position: After calculating the grayscale centroid, the centroid position is further obtained. The axis in the centroid axis position refers to the direction perpendicular to the image, which is the centroid axis.

[0056] In practical applications, the gray-scale centroid method may require image preprocessing, such as filtering and denoising, to avoid the influence of noise and interference on the calculation results. Furthermore, when calculating the gray-scale centroid, the handling of edge pixels can be considered according to actual needs to avoid their potential impact on the calculation results and improve the accuracy of the determined centroid axial position of the B-scan image.

[0057] In the above embodiments of this application, all the obtained centroid positions can be used as or fitted into a waveform in terms of time sequence. This waveform reflects the original heartbeat-related time variation signal. Preferably, considering that the original heartbeat-related time variation signal may contain noise and other interference factors, the maximum dominant frequency signal can be extracted through spectrum analysis as the final heartbeat-related time variation signal to reduce interference fluctuations.

[0058] Of course, the above is only one possible method for obtaining the centroid axial position of B-scan images in this application. In other embodiments, other steps or methods can also be used to achieve this, and it is not limited to the grayscale centroid method implementation steps described above.

[0059] S102, Based on the obtained timing of the peaks and troughs of the eye movement displacement caused by the heartbeat, determine the time points of vasoconstriction and vasodilation of the subject.

[0060] In this step, after obtaining the timing of the peaks and troughs caused by the heartbeat, the timing of vasoconstriction and vasodilation in the subject is determined based on their intrinsic relationship with the timing of vasoconstriction and vasodilation. The timing of the peaks and troughs of eye movement displacement caused by the heartbeat can be regarded as the trajectory of eye movement under the influence of the heartbeat. Specifically, when the heart contracts, blood flows to various parts of the body, including the head and eyes. This may cause slight dilation of blood vessels in the eyes, resulting in an increase in eye movement displacement, which can be regarded as a peak. When the heart relaxes, blood flows back to the heart, including from the head and eyes. This may cause slight constriction of blood vessels in the eyes, resulting in a decrease in eye movement displacement, which can be regarded as a trough. Therefore, the timing of the peaks and troughs of eye movement displacement caused by the heartbeat reflects the influence of the heart's contraction and relaxation cycle on the eyes. Based on this, this embodiment can obtain the peak and trough time sequence of eye movement displacement caused by heartbeat through B-scan images to determine the time points of vasoconstriction and vasodilation of the subject. This method does not require much computing resources and time, and the cost is relatively low. When the quality of the obtained B-scan images is high, the accuracy of the results is high.

[0061] S200, the number of scans is increased based on the heart rate-related time change signal obtained in S100 to suppress artifacts in medical images.

[0062] To overcome the limitations of existing fundus microscopes, which typically have a maximum frame rate of 50fps and insufficient tracking timeliness to address the OCTA bright line spurious signal problem caused by heartbeat, this step involves performing a formal OCTA scan on the subject's fundus after the heartbeat-related time change signal is determined in S100. The OCTA scanning process is controlled by increasing the number of scans based on the heartbeat-related time change signal. This effectively solves the OCTA bright line spurious signal problem caused by heartbeat and avoids misdiagnosis of diseases during medical testing due to OCTA artifacts and image quality issues.

[0063] Similarly, when performing a formal OCTA scan on the subject's fundus, the subject should be kept in a stable physical state as much as possible, and in a state similar to that during the pre-scan, especially in terms of heart rate-related status. This is to ensure that the subject's heart rate-related time change signals can be reliably determined in this step, and to further ensure the effectiveness of the measure of increasing the number of OCTA scans based on the subject's heart rate-related time change signals.

[0064] In one possible implementation, corresponding to S100, the number of OCTA scans is increased near the time points of vasoconstriction and vasodilation. This can be achieved by increasing the number of OCTA scans near the time points corresponding to the peaks and troughs of eye movement displacement, respectively.

[0065] Specifically, the number of OCTA scans is increased near the time points corresponding to the peaks and troughs of eye movement caused by heartbeats. That is, when performing OCTA scans on the same subject's fundus, different scan counts are set for different times (corresponding to heartbeat patterns). Specifically, during OCTA scans of the subject's fundus, the number of scans near the time points corresponding to the peaks and troughs of eye movement caused by heartbeats is controlled at N1, and the number of scans at other locations is controlled at N2; where N1 / N2 is greater than 1. In other words, referring to the pre-scan parameters, during the actual OCTA scan, under the same scanning conditions, the number of scans near the time points (corresponding scan positions) corresponding to the peaks and troughs of eye movement caused by heartbeats is increased compared to other times, thereby obtaining more images to suppress bright line artifacts. N2 can be determined according to general OCTA scan parameters, while N1 can be set according to actual needs. By increasing the number of scans at these locations, the reliability of the data can be increased, the influence of noise and artifacts can be reduced, and more accurate results can be obtained.

[0066] Figure 3 This diagram illustrates the correspondence between the centerbeat correlation time signal and the B-scan scan sequence in an exemplary embodiment of this application. (Refer to...) Figure 3As shown, the graph illustrates the correspondence between the periodic heartbeat signal and the B-scan scan sequence along time intervals t1, t2, t3, t4, and t5. In the graph, 0.15T represents the duration of the peak, and T is the period of the heartbeat-related time-varying signal. One period generally corresponds to a complete heartbeat signal, which includes peaks and troughs, representing the vasoconstriction and vasodilation associated with the heartbeat. The graph shows that, according to the B-scan sequence number on the vertical axis: t1-t2, B-scans 1 and 2 each scanned twice; from t2-t5, B-scans 3, 4, and 5 increased to four scans.

[0067] To more accurately determine the locations near the time points corresponding to the peaks and troughs of eye movement caused by heartbeats, thus enabling more precise scan control, during OCT scans of the subject's fundus, a first and second number of adjacent B-scan scan locations are selected at the time points corresponding to the peaks and troughs, respectively. The number of OCT scans is then increased at these selected first and second number of B-scan scan locations. Preferably, the first and second numbers can be the same.

[0068] In a preferred embodiment, increasing the number of OCTA scans near the time points corresponding to the peaks and troughs caused by heartbeats can be performed according to the following steps:

[0069] S201, select M neighboring B-scan positions at the time points corresponding to the peaks and troughs;

[0070] S202, Increase the number of OCTA scans at the selected M B-scan locations;

[0071] Where M is: (frequency bandwidth coefficient * period of heartbeat-related time change signal) / B-scan scanning period of OCT scanning system, which can be expressed as the following formula:

[0072]

[0073] In the formula, T is the period of the heartbeat-related time change signal, t is the B-scan scanning period of the OCT scanning system, and F is the frequency bandwidth coefficient, F<1. The specific value can be adjusted according to the actual detection situation, and the typical value is F=0.15.

[0074] In this step, the number of OCTA scans is increased at M B-scan positions near the peak and trough time points. For example, in one embodiment, the number of B-scan scans N at the same position in the original OCTA scan can be increased to 2N. Specifically, the original OCTA scan used the same number of scans N to perform B-scan scans on all positions. However, to solve the problem of OCTA bright line pseudo-signals caused by heartbeats, different number of scans are used for different positions. That is, the number of scans at the M B-scan positions near the peak and trough time points is 2N, while the number of scans at other positions remains N. The final OCTA image is obtained through this scanning method.

[0075] Figure 4 This is a flowchart illustrating the scanning and feedback control operation of an exemplary embodiment of this application. In the above embodiment, after obtaining the heartbeat-related time-varying signal, the signal is fed back to the OCT scanning system to achieve automatic adjustment of the scanning parameters. Specifically, the centroid axial position of the pre-acquired B-scan image is obtained, and spectral analysis is performed over time to obtain the amplitude, frequency, and phase of the maximum dominant frequency signal, which is then fed back to the OCT scanning system. Based on this, referring to... Figure 4 As shown, in a specific embodiment, the following steps can be followed:

[0076] M100, acquiring B-scan images: Using a standard scanning method, an OCT scanning system is used to acquire B-scan images of the subject's fundus;

[0077] M200, Determine the centroid axis position: Process the B-scan image to obtain the centroid axis position of the B-scan image. For example, the grayscale centroid method can be used to determine the centroid axis position of the B-scan image.

[0078] M300, Spectrum Analysis: Performs spectrum analysis on the centroid axis position of the acquired B-scan image, that is, decomposes the heartbeat-related periodic signals representing all centroid axis positions along time into combinations of sine waves with different frequencies, amplitudes, and initial phases, and extracts spectrum information. For example, this can be achieved through the Fast Fourier Transform (FFT) algorithm.

[0079] M400 extracts the maximum dominant frequency signal: From the spectral information obtained through spectrum analysis, it extracts the amplitude, frequency, and phase information of the maximum dominant frequency signal. This can be achieved, for example, through algorithms such as peak detection or threshold detection on the spectrum.

[0080] Through the above steps, the timing of vasoconstriction and vasodilation related to the heartbeat of the subject is determined (the timing of the peak and trough of the eye movement displacement caused by the heartbeat).

[0081] M500 Feedback Input Control: The amplitude, frequency, and phase information of the extracted maximum main frequency signal are fed back into the OCT scanning system. Based on this feedback information, the number of scans is adjusted. That is, during the actual OCTA image acquisition and scanning, the number of scan repetitions is increased near the time point of vasoconstriction and vasodilation in the subject to optimize the scan quality.

[0082] Through the M100-M500 of the above embodiments, feedback control of the OCT scanning system based on spectrum analysis can be realized, thereby improving scanning quality and efficiency.

[0083] The embodiments described above in this application, by pre-acquiring OCT B-scan images of the subject, determine the axial position of the center of gravity and further demodulate the subject's heartbeat-related time-varying signals, including frequency and contraction / dilation timing. During the actual OCTA image acquisition and scanning, based on the acquired heartbeat-related time-varying signals, the vasoconstriction / dilation time points are further determined. Near these vasoconstriction / dilation time points, the OCT scanning system increases the number of scan repetitions, thereby resolving artifacts such as bright lines caused by heartbeats in the OCTA scan.

[0084] Figure 5 The image shown is a comparison of the effects before and after removing artifacts caused by the midshot in a retinal OCTA image, according to an exemplary embodiment of this application. (Refer to...) Figure 5 As shown, the right image is the image obtained from a normal scan, and the left image is the image obtained from a scan using the method described in this application embodiment. The comparison clearly shows that this application embodiment, based on the heartbeat-related time-varying signal, increases the number of scan repetitions in the OCT scanning system near the time points of vasoconstriction and vasodilation, effectively resolving artifacts such as bright lines in OCTA caused by heartbeat.

[0085] Based on the same technical concept, this application provides a medical image artifact suppression system to address artifact issues in medical images. The system includes: a first determining module, which acquires medical images obtained from scanning a subject and determines the subject's heart rate-related time-varying signal based on the medical images; and a scanning control module, which increases the number of scans based on the heart rate-related time-varying signal to suppress medical image artifacts. Increasing the number of scans by using the heart rate-related time-varying signal can significantly reduce artifacts caused by heartbeats.

[0086] In one possible embodiment, the medical image includes: a B-scan image. Specifically, Figure 6 A block diagram of a medical image artifact suppression system provided for an exemplary embodiment of this application. (Refer to...) Figure 6 As shown, the artifact suppression system based on medical images includes:

[0087] First determining module 100: acquires medical images obtained from scanning the subject, and determines the subject's heart rate-related time change signal based on the medical images;

[0088] Scan control module 200: Increases the number of scans based on the heart rate-related time change signal to suppress artifacts in OCTA images.

[0089] In the aforementioned medical imaging artifact suppression system, in order to acquire the subject's heart rate-related time change signal to further determine the heart rate-related vasoconstriction and vasodilation time points, in a possible implementation, the first determining module may include:

[0090] The first determination submodule: Based on the B-scan image, demodulate the subject's heart rate-related time change signal, which includes the peak and trough time sequence of eye movement displacement caused by heartbeat;

[0091] The second determining submodule: Based on the timing of the peaks and troughs caused by the heartbeat, determine the time points of vasoconstriction and vasodilation of the subject.

[0092] In the above embodiments of this application, the scanning control module increases the number of OCTA scans near the time points of vasoconstriction and vasodilation. In one possible implementation, the number of OCTA scans is increased near the time points corresponding to the peaks and troughs caused by the heartbeat, as determined by the time point determination submodule, in order to suppress artifacts such as OCTA bright line spurious signals.

[0093] In the above embodiments of this application, the scanning control module increases the number of OCTA scans near the time points corresponding to the peaks and troughs caused by the heartbeat. In one possible implementation, when performing OCTA scans on the fundus of the subject, the number of scans near the time points corresponding to the peaks and troughs is controlled to be N1, and the number of scans at other locations is N2; wherein, N1 / N2 is greater than 1.

[0094] To improve scan control, in one possible implementation, the scan control module increases the number of OCTA scans near the time points corresponding to the peaks and troughs caused by the heartbeat. This includes: selecting M neighboring B-scan positions at the time points corresponding to the peaks and troughs; and increasing the number of OCTA scans at the selected M B-scan positions. Here, M is: (frequency bandwidth coefficient * period of the heartbeat-related time-varying signal) / B-scan scan period of the OCT scan system. This method allows for accurate selection of the scan positions where the number of OCTA scans is increased.

[0095] In order to obtain accurate heart rate-related time change signals, in one possible implementation, the demodulation submodule demodulates the heart rate-related time change signals of the subject, including: acquiring the centroid axis position of the B-scan image, and performing spectral analysis on the centroid axis position along time, taking the amplitude, frequency and phase of the maximum dominant frequency signal in the spectral analysis, and obtaining the peak and trough time sequence of eye movement displacement caused by heartbeat.

[0096] Based on the above embodiments, after determining the vasoconstriction and vasodilation time points of the subject according to the timing of the peaks and troughs caused by the heartbeat, the feedback module feeds back the determined vasoconstriction and vasodilation time points related to the subject's heartbeat to the OCT scanning system, which can realize the automatic adjustment of scanning parameters.

[0097] Specifically, in a preferred embodiment, it can be operated in the following manner:

[0098] First, the first determining module: During the pre-real-time acquisition of OCT B-scan images of the subject, the time points of vasoconstriction and vasodilation of the subject are determined, which means demodulating the subject's heartbeat-related time change signal, i.e., the peak and trough timing of eye movement displacement caused by heartbeat. This specific process can be implemented through the first determining submodule and the second determining submodule mentioned above.

[0099] Then, based on the vasoconstriction and vasodilation time points of the subjects determined above, that is, the corresponding peak and trough time sequence of eye movement displacement caused by heartbeat, M neighboring B-scans are selected at the time points corresponding to the peak and trough, where M can be represented as:

[0100]

[0101] T is the period of the heart rate-related time-varying signal, t is the B-scan scanning period of the OCT scanning system; F is the frequency bandwidth coefficient, which can be adjusted appropriately according to the actual detection situation, with a typical value of F = 0.15.

[0102] Finally, the scanning control module controls the OCTA scanning process, increasing the number of OCTA scans at M B-scan positions near the peak and trough time points; for example, increasing the number of B-scan scans N at the same position in the original OCTA to 2N.

[0103] In the above embodiments, when the first determining module performs pre-real-time acquisition of OCT B-scan images of the subject, it demodulates the subject's heart rate-related time-varying signals. This can be achieved by acquiring the centroid axial position of the pre-real-time acquired B-scan images and performing spectral analysis. Further, the method for acquiring the centroid axial position includes, but is not limited to, the gray-scale centroid method, which calculates the gray-scale centroid for each OCT B-Scan image. Spectral analysis is performed on the acquired centroid axial position, decomposing the periodic signal into a combination of sine waves with different frequencies, amplitudes, and initial phases. The amplitude, frequency f0, and phase φ0 of the maximum dominant frequency signal are obtained, thereby revealing the time points corresponding to the peaks and troughs.

[0104] The implementation techniques of each module in the above-described embodiment of the system for suppressing OCTA bright line spurious signals can be referred to the steps of the embodiment of the method for suppressing OCTA bright line spurious signals, and will not be repeated here.

[0105] Based on the same concept described above, another embodiment of this application provides a terminal, including:

[0106] At least one memory for storing program instructions;

[0107] At least one processor is configured to call program instructions stored in the memory and execute the above-mentioned steps for suppressing artifacts in medical images according to the obtained program instructions, namely: acquiring medical images obtained by scanning the subject; determining the subject's heart rate-related time change signal based on the medical images; and increasing the number of scans based on the heart rate-related time change signal to suppress artifacts in the medical images.

[0108] Optionally, the memory is used to store programs; the memory may include volatile memory, such as random-access memory (RAM), such as static random-access memory (SRAM), double data rate synchronous dynamic random-access memory (DDR SDRAM), etc.; the memory may also include non-volatile memory, such as flash memory. The memory is used to store computer programs (such as application programs, functional modules, etc. that implement the above methods), computer instructions, etc., and the aforementioned computer programs, computer instructions, etc., can be partitioned and stored in one or more memories. Furthermore, the aforementioned computer programs, computer instructions, data, etc., can be accessed by the processor.

[0109] The aforementioned computer programs, computer instructions, etc., can be stored in partitions within one or more memory locations. Furthermore, the aforementioned computer programs, computer instructions, data, etc., can be accessed by a processor.

[0110] A processor is used to execute a computer program stored in memory to implement the various steps of the methods involved in the above embodiments. For details, please refer to the relevant descriptions in the preceding method embodiments.

[0111] The processor and memory can be separate structures or integrated structures. When the processor and memory are separate structures, they can be coupled together via a bus.

[0112] Based on the same concept described above, in another embodiment of this application, a computer-readable storage medium is provided, on which a computer program is stored. When executed by a processor, the computer program implements the steps of suppressing artifacts in medical images as described in any of the above embodiments, namely: acquiring medical images obtained by scanning a subject; determining the heart rate-related time change signal of the subject based on the medical images; and increasing the number of scans based on the heart rate-related time change signal to suppress artifacts in the medical images.

[0113] Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transfer of computer programs from one place to another. Storage media can be any available medium accessible to a general-purpose or special-purpose computer. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. Alternatively, the ASIC can reside in a user device. Of course, the processor and storage medium can also exist as discrete components in a communication device.

[0114] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0115] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0116] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0117] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0118] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0119] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method of artifact suppression of medical images, characterized by, include: Acquire medical images of the subject by scanning, and determine the subject's heart rate-related time change signal based on the medical images; The number of scans is increased based on the heart rate-related time variation signal to suppress artifacts in medical images; The medical images include: B-scan images; determining the subject's heart rate-related time-varying signals based on the medical images includes: Based on the B-scan image, the heart rate-related time change signal of the subject is demodulated, wherein the heart rate-related time change signal includes the time sequence of eye movement displacement peaks and troughs caused by heartbeat; The step of increasing the number of scans based on the heartbeat-related time change signal includes: Based on the timing of the peaks and troughs of eye movement displacement caused by the heartbeat, determine the time points corresponding to the peaks and troughs of eye movement displacement caused by the heartbeat. When scanning the subject, the number of scans is increased according to the time points corresponding to the peaks and troughs of the eye movement displacement.

2. The method according to claim 1, characterized in that, The step of increasing the number of scans during the scanning of the subject, based on the time points corresponding to the peaks and troughs of the eye movement displacement, includes: When performing an OCT scan on the fundus of the subject, at the B-scan scan positions corresponding to the time points corresponding to the peaks and troughs, a first number and a second number of adjacent B-scan scan positions are selected. The number of OCT scans is increased at the selected first and second number of B-scan scan locations.

3. The method according to claim 2, characterized in that, The first quantity and the second quantity are the same and both are M.

4. The method according to claim 3, characterized in that, The M = (frequency bandwidth coefficient) (Period of heart rate-related time variation signal) / B-scan scan cycle of OCT scanning system.

5. The method according to claim 1, characterized in that, The demodulated heart rate-related time-varying signal of the subject includes: Obtain the centroid axial position of the B-scan image; A spectral analysis is performed on the axial position of the center of gravity along time, and the maximum dominant frequency signal is obtained in the spectral analysis as the heartbeat-related time variation signal.

6. A medical imaging artifact suppression system, characterized in that, include: First determining module: acquires medical images obtained from scanning the subject, and determines the subject's heart rate-related time change signal based on the medical images; Scan control module: Increases the number of scans based on the heart rate-related time change signal to suppress artifacts in medical images; The medical images include: B-scan images; determining the subject's heart rate-related time-varying signals based on the medical images includes: Based on the B-scan image, the heart rate-related time change signal of the subject is demodulated, wherein the heart rate-related time change signal includes the time sequence of eye movement displacement peaks and troughs caused by heartbeat; The step of increasing the number of scans based on the heartbeat-related time change signal includes: Based on the timing of the peaks and troughs of eye movement displacement caused by the heartbeat, determine the time points corresponding to the peaks and troughs of eye movement displacement caused by the heartbeat. When scanning the subject, the number of scans is increased according to the time points corresponding to the peaks and troughs of the eye movement displacement.

7. A terminal, characterized in that, include: At least one memory for storing program instructions; At least one processor is configured to invoke program instructions stored in the memory and execute the steps of the method described in any one of claims 1-5 according to the obtained program instructions.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method described in any one of claims 1-5.

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