A dynamic image generation method and system

Abstract

Embodiments of the present specification provide a dynamic image generation method and system. The method comprises obtaining scan data of a target object in a scan time period, the scan time period exceeding one motion cycle of the target object; rearranging the scan data to generate rearranged data, a total variation (TV) in a time direction of the rearranged data being lower than a total variation in a time direction of the scan data; reconstructing multiple images of the target object based on the rearranged data; and rearranging the reconstructed multiple images according to scan time to generate a dynamic image of the target object.

Description

Technical Field

[0001] This specification relates to the field of medical imaging, and in particular to a method and system for dynamic image reconstruction. Background Technology

[0002] In recent years, medical imaging technology has been widely used in clinical examinations and medical diagnosis. For example, magnetic resonance imaging (MRI) is a medical imaging technique used to acquire images of the anatomical structures and / or physiological processes of a target object. Among these, dynamic medical imaging methods, such as cardiac magnetic resonance imaging (CMR), are a routine clinical cardiac examination that can obtain physiological parameters of the heart, including anatomy, function, perfusion, and metabolism. MR cardiac cine technology is one of the routine CMR examination sequences. It uses a cine-like approach to continuously display multiple cardiac images at different times within a single cardiac cycle on a single plane, allowing direct observation of myocardial wall motion. It is mainly used for evaluating local and overall cardiac function (ejection fraction, stroke volume, myocardial mass, systolic wall thickening rate, etc.) and is a routine CMR examination sequence. MR cardiac cine utilizes ECG-gated and segmented acquisition imaging techniques to produce high-quality dynamic images. MR cardiac cine technology takes advantage of the periodicity of cardiac motion. Data acquisition typically lasts for multiple cardiac cycles. In each cardiac cycle, a portion of the k-space data for each image is acquired. This technology combines MRI and electrocardiography (ECG) for detection, integrating data from different heartbeats for imaging. Because of the large amount of data acquired, high-quality dynamic images can be obtained. However, this technology has several significant drawbacks: 1) patients need to hold their breath for an extended period; 2) it cannot be used by patients with arrhythmias; and 3) it cannot be used if a reliable ECG signal is unavailable.

[0003] To overcome the aforementioned drawbacks, real-time dynamic MR cardiac cine imaging is an alternative. The data acquisition method for real-time dynamic cardiac cine imaging involves acquiring data for one image within a defined time interval, then moving on to the next. This time interval is the temporal resolution of real-time dynamic imaging, typically slightly higher than 40 milliseconds. Because the acquisition time for each image is very short, very little data is acquired; the k-space is far from full, requiring imaging algorithms to fill in the missing data before an image can be output. The advantages of this imaging method are that it does not require prolonged breath-holding by the patient, and it can be used for patients with irregular heart rates. The disadvantages are that the spatial resolution of the images is usually low, or noise and artifacts are relatively high. It is difficult to simultaneously achieve optimal results for the three important metrics: temporal resolution, spatial resolution, and image quality. Therefore, a system and method are needed that can obtain high-quality dynamic images while balancing temporal and spatial resolution. Summary of the Invention

[0004] This specification provides a method for generating dynamic images. The method includes: acquiring scan data of a target object within a scan time period, the scan time period exceeding one motion cycle of the target object; rearranging the scan data to generate rearranged data, the total variation of the rearranged data in the time direction being lower than the total variation of the scan data in the time direction; reconstructing multiple images of the target object based on the rearranged data; and rearranging the reconstructed multiple images according to the scan time to generate a dynamic image of the target object.

[0005] In some embodiments, the method further includes: acquiring the motion state of the target object, wherein the motion state of the target object is determined based on a detection signal of a reference object associated with the target object.

[0006] In some embodiments, rearranging the scan data to generate rearranged data includes: rearranging the scan data based on the motion state of the target object to generate rearranged data.

[0007] In some embodiments, the rearranged data is within half of a first motion cycle.

[0008] In some embodiments, the method further includes: acquiring reference information, the reference information including a second motion cycle and the motion state of the target object.

[0009] In some embodiments, rearranging the scan data to generate rearranged data includes: rearranging the scan data based on the second motion cycle and the motion state of the target object to generate rearranged data.

[0010] In some embodiments, the rearranged data is within a second motion cycle.

[0011] In some embodiments, the method further includes: performing phase correction on the scan data.

[0012] Another aspect of this specification provides a dynamic image generation system. The system includes: an acquisition module, a rearrangement module, a reconstruction module, and a dynamic image generation module; wherein, the acquisition module is used to acquire scan data of a target object within a scanning time period, the scanning time period exceeding one motion cycle of the target object; the rearrangement module is used to rearrange the scan data to generate rearranged data, the total variation of the rearranged data in the time direction being lower than the total variation of the scan data in the time direction; the reconstruction module is used to reconstruct multiple images of the target object based on the rearranged data; and the dynamic image generation module is used to rearrange the reconstructed multiple images according to the scan time to generate a dynamic image of the target object.

[0013] This specification also provides a dynamic image generation system. The system includes a processor, characterized in that the processor is configured to perform the dynamic imaging method as described in any one of claims 1-8. Attached Figure Description

[0014] This specification will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting; in these embodiments, the same reference numerals denote the same structures, wherein:

[0015] Figure 1 This is an exemplary flowchart of a dynamic image generation method according to some embodiments of this specification.

[0016] Figure 2A This is an exemplary flowchart illustrating the rearrangement of scanned data according to some embodiments of this specification.

[0017] Figure 2B This is a schematic diagram illustrating the rearrangement of scan data to half of a first motion cycle based on the motion state of the target object, according to some embodiments of this specification.

[0018] Figure 3A This is an exemplary flowchart illustrating the rearrangement of scanned data according to some embodiments of this specification.

[0019] Figure 3B This is a schematic diagram illustrating the rearrangement of scan data to the second motion cycle based on the second motion cycle and the motion state of the target object, according to some embodiments of this specification.

[0020] Figure 4 This is an exemplary block diagram of an imaging system according to some embodiments of this specification.

[0021] Figure 5 This is an exemplary structural diagram of an imaging device according to some embodiments of this specification. Detailed Implementation

[0022] To more clearly illustrate the technical solutions of the embodiments in this specification, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some examples or embodiments of this specification. For those skilled in the art, these drawings can be applied to other similar scenarios without creative effort. Unless obvious from the context or otherwise specified, the same reference numerals in the drawings represent the same structures or operations.

[0023] It should be understood that the terms “system,” “device,” “unit,” and / or “module” used herein are one way to distinguish different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0024] As indicated in this specification and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of expressly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0025] Flowcharts are used in this specification to illustrate the operations performed by the system according to embodiments of this specification. The related descriptions are provided to aid in a better understanding of the medical imaging methods and / or systems. It should be understood that preceding or subsequent operations are not necessarily performed precisely in sequence. Instead, steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0026] This application provides a method for generating dynamic images, which involves acquiring scan data of a target object within at least one scan time period, the scan time period exceeding one motion cycle of the target object. The scan data is rearranged (first rearrangement) based at least on the motion state of the target object, generating rearranged data such that the total variation (TV) of the rearranged data in the time direction is lower than the total variation in the time direction of the scan data. Based on the rearranged data, multiple images of the target object are reconstructed. The reconstructed multiple images are then rearranged according to scan time (second rearrangement) to generate a dynamic image of the target object. The second rearrangement is equivalent to the reverse operation of the first rearrangement. Through rearrangement, the temporal variation between the image frames corresponding to the rearranged data is reduced, i.e., the motion amplitude of the target object is smaller, the motion is smoother, motion artifacts are reduced, and optimal image quality is obtained while maintaining temporal and spatial resolution.

[0027] Figure 1 This is an exemplary flowchart of a dynamic image generation method according to some embodiments of this specification.

[0028] The entity performing the dynamic image generation method 100 may include a scanning device and / or a processing device. In some embodiments, the scanning device may be a medical imaging device. The medical imaging device can be used to scan a target object within a detection area to obtain scan data of the target object.

[0029] In some embodiments, the medical imaging device may be a non-invasive biomedical imaging device for disease diagnosis or research purposes. For example, the medical imaging device may include a single-modal scanner and / or a multimodal scanner. A single-modal scanner may include, for example, a magnetic resonance imaging (MRI) scanner, a computed tomography (CT) scanner, a positron emission tomography (PET) scanner, an ultrasound scanner, an ultrasound scanner, an X-ray scanner, an optical coherence tomography (OCT) scanner, an ultrasound (US) scanner, an intravascular ultrasound (IVUS) scanner, a near-infrared spectroscopy (NIRS) scanner, a far-infrared (FIR) scanner, or any combination thereof. A multimodal scanner may include, for example, a magnetic resonance imaging-single-photon emission computed tomography (MRI-SPECT) scanner, a magnetic resonance imaging-X-ray imaging (MRI-X-ray) scanner, a magnetic resonance imaging-digital subtraction angiography (MRI-DSA) scanner, a positron emission tomography-computed tomography (PET-CT) scanner, a positron emission tomography-X-ray imaging (PET-X-ray) scanner, etc. The scanners described above are for illustrative purposes only and are not intended to limit the scope of this application. As used herein, the term “imaging modality” or “modality” broadly refers to imaging methods or techniques for collecting, generating, processing, and / or analyzing imaging information of a target object.

[0030] For ease of explanation, this specification uses MRI as an example to specifically illustrate the dynamic image generation method, but does not limit the application of this dynamic image generation method to other imaging methods, such as CT, PET, etc. Exemplarily, the scanning device in this specification is an MRI scanner. In some embodiments, the MRI scanner may include, for example, a magnet, one or more gradient coils, one or more radio frequency (RF) coils, a scanning bed, etc. The magnet can be used to generate a static magnetic field during scanning. The gradient coils can generate magnetic field gradients relative to the magnetic field in the X, Y, and / or Z directions (or axes). In some embodiments, the gradient coils may include X-direction coils, Y-direction coils, Z-direction coils, etc. The RF coils can transmit RF pulse signals to the target object being examined (e.g., the heart) and / or receive magnetic resonance (MR) data from it. In some embodiments, the RF coils may include an RF transmitting coil and an RF receiving coil. The RF transmitting coil can transmit RF pulse signals, and the RF receiving coil can receive MR data transmitted from the target object. In some embodiments, the RF transmitting coil and the RF receiving coil can be integrated into a single coil, for example, a transmit / receive coil. In some embodiments, the RF coil can be of various types, including, for example, a QD quadrature coil, a phase array coil, etc. In some embodiments, the RF coil may vary depending on the part of the user's body being examined, including, for example, a cardiac coil, a chest coil, etc. In some embodiments, depending on function and size, the RF coil may include, but is not limited to, volumetric coils, local coils, cage coils, transverse electromagnetic coils, surface coils, saddle coils, solenoid coils, flexible coils, etc., or any combination thereof. The scanning bed can be used to position the user for scanning. For example, the user may lie supine, on their side, or prone on the scanning bed.

[0031] In some embodiments, depending on the type of magnet, the MRI scanner may be a permanent magnet MRI scanner, a superconducting electromagnetic MRI scanner, or a resistive electromagnetic MRI scanner, etc. In some embodiments, depending on the magnetic field strength, the MRI scanner may be a high-field MRI scanner, a medium-field MRI scanner, or a low-field MRI scanner, etc. In some embodiments, the MRI scanner may be a closed-aperture (cylindrical) type, an open-aperture type, etc.

[0032] In some embodiments, the processing device may be a part of a system integrated into an electronic device (e.g., the aforementioned scanning device, such as an MRI scanner), a standalone electronic device, or a device hosted on a cloud server. For example, the processing device may be a control panel of the aforementioned scanning device (such as an MRI scanner), a personal computer, a laptop computer, a smartphone, a tablet computer, or a portable wearable device. In some embodiments, the dynamic image generation method 100 may be executed by the imaging system 400.

[0033] In some embodiments, the dynamic image generation method 100 may include:

[0034] Step 110: Acquire scan data of the target object within a scan time period, wherein the scan time period exceeds one motion cycle of the target object. In some embodiments, step 110 may be performed by the acquisition module 410.

[0035] The target object undergoes periodic movement (e.g., cyclical reciprocating movement) during the scanning time period. In some embodiments, the target object may include biological and / or non-biological objects. For example, the target object may include the human body or specific parts thereof, such as the heart, chest cavity, abdomen, etc., or combinations thereof. As another example, the target object may be a man-made component of living or non-living organic and / or inorganic matter, such as an artificial heart, artificial blood vessels, etc.

[0036] The motion cycle of the target object refers to the process by which the target object, undergoing periodic motion, moves from the starting point of the current cycle to the starting point of the next cycle. The motion cycle of the target object is denoted as T. T can be 0.5s (seconds), 1s, 1.5s, 2s, 3s, 5s, 10s, 20s, 30s, etc. Taking the heart as an example, within one motion cycle, the heart gradually begins to relax from the end of systole (when the heart volume is at its minimum), reaches the end of diastole (when the heart volume is at its maximum), and then contracts again until it returns to the end of systole. The motion cycle (also called the cardiac cycle) of a normal human heart is 0.6s to 1.2s.

[0037] The scanning time period can be set by the user or determined by the imaging system 400 according to default settings. For example, the user can set the scanning time period to 5s, 10s, 15s, 20s, 30s, 40s, 50s, 1min, 2min, 5min, 10min, etc. The scanning time period exceeds one motion cycle of the target object. For example, the scanning time period includes, for example, 1.1, 1.2, 1.3, 1.5, 1.8, 2, 3, 5, 10, 20 or more motion cycles of the target object. Correspondingly, the length of the scanning time period is equal to or close to 1.1 times, 1.2 times, 1.3 times, 1.5 times, 1.8 times, 2 times, 3 times, 5 times, 10 times, 20 times or more of the motion cycle of the target object.

[0038] The scan data is generated by an MRI scanner scanning the target object during the scan time period. The scan data corresponds to an image of the target object (also known as a raw image). The raw image includes a set of raw image frames. This set of raw image frames can be generated by reconstructing the scan data. For example, a set of raw image frames obtained by reconstructing the scan data is shown in a partial embodiment of step 210 in Figure 2. During the acquisition of the scan data by the MRI scanner, within a specific time interval, the MRI scanner completes the acquisition of scan data corresponding to one raw image frame, and then moves on to the acquisition of scan data corresponding to the next raw image frame, until all scan data is acquired. The specific time interval is the temporal resolution of dynamic imaging. In some embodiments, the specific time interval is relatively short (e.g., slightly higher than 40 milliseconds). Because the acquisition time for the scan data corresponding to each raw image frame is short, less data is acquired, and the k-space cannot be fully acquired. The MR scan data is downsampled data.

[0039] In some embodiments, the scan data is data acquired in real time during the scan period. For example, the scan data may be raw data (such as MR data) generated in real time by scanning a target object using an MRI scanner during the scan period. The acquisition module 410 can acquire the raw data in real time. In some embodiments, the scan data may be raw data stored in a storage device (e.g., a cloud storage device). The acquisition module 410 can acquire the scan data directly or via a network.

[0040] In some embodiments, the acquisition module 410 may perform preliminary processing on the acquired scan data. This preliminary processing may include data correction, noise reduction, etc. For example, phase correction may be performed on the data. Due to the stability issues of MRI scanners, MR signals may exhibit phase drift. Exemplarily, this can be achieved by reconstructing a complex image of the scan data, establishing a phase difference between different image points in the complex image using the average phase value of image points from a first surrounding region of the relevant image point, and performing phase correction based on the degree of correspondence between the phase difference and a predetermined phase value. By performing phase correction on the scan data, the accuracy of the scan data rearrangement in step 120 can be ensured.

[0041] Step 120: The scan data is rearranged to generate rearranged data. In some embodiments, step 120 may be performed by the rearrangement module 420.

[0042] The scan data acquired in step 110 corresponds to the original image, which includes a set of original image frames. Each original image frame in this set corresponds to a portion of the scan data, and the portions of scan data are arranged in a first order along the time axis. For example, the scan data includes a first portion of scan data, a second portion of scan data, and a third portion of scan data. The first portion of scan data, the second portion of scan data, and the third portion of scan data correspond to the first original image frame, the second original image frame, and the third original image frame, respectively. The first portion of scan data, the second portion of scan data, and the third portion of scan data are arranged sequentially (i.e., in the first order) along the time axis. Accordingly, the first original image frame, the second original image frame, and the third original image frame can reflect the movement process of the target object over time.

[0043] The rearrangement module 420 can rearrange the scanned data in the time direction (first rearrangement). During the rearrangement process, the arrangement order of each part of the scanned data (e.g., the first order) is adjusted so that the arrangement order of each part of the scanned data becomes a second order, thereby generating rearranged data. The second order is different from the first order. After rearranging to the second order, the total variation (TV) value of the rearranged data in the time direction is lower than the TV value of the scanned data in the time direction. The TV value of the rearranged data in the time direction refers to the sum of the absolute values ​​of the differences (i.e., the sum of the differences of corresponding pixels) between each image frame in the image corresponding to the rearranged data (e.g., the reconstructed image generated in step 130, which includes a set of reconstructed image frames) and one or more adjacent image frames in the time direction after rearrangement. The TV value of the scanned data in the time direction refers to the sum of the absolute values ​​of the differences (i.e., the sum of the differences of corresponding pixels) between each image frame in the image corresponding to the scanned data (e.g., the original image reconstructed from the scanned data, which includes a set of original image frames) and one or more adjacent image frames in the time direction.

[0044] By rearranging the data so that the TV value of the rearranged data in the time direction is lower than that of the scanned data in the time direction, the time-direction variation between the image frames corresponding to the rearranged data can be smaller. That is, the motion amplitude of the target object is smaller and the motion is smoother. Therefore, motion artifacts can be reduced, better imaging quality can be obtained, and optimal image quality can be obtained while ensuring temporal and spatial resolution.

[0045] For example, the rearranged data includes a first portion of scan data, a third portion of scan data, and a second portion of scan data arranged sequentially along the time axis. The TV value of the rearranged data arranged in a second order in the time direction, i.e., the first portion of scan data, the third portion of scan data, and the second portion of scan data arranged sequentially in the time direction, is lower (smaller) than the TV value of the scan data arranged in a first order in the time direction, i.e., the first portion of scan data, the second portion of scan data, and the third portion of scan data arranged sequentially in the time direction.

[0046] In some embodiments, the scan data can be rearranged at least partially based on the motion state of the target object. The motion state of the target object can include the motion amplitude (or motion position) of the target object or a portion thereof (i.e., a part of the target object) at different times. In some embodiments, the motion state of the target object can be determined based on the scan data or the condition of a reference object. In some embodiments, the motion state of the target object can be determined based on reference information. In some embodiments, during the rearrangement process, in addition to the change in order (e.g., from a first order to a second order), the time corresponding to each part of the scan data also changes. For example, the rearrangement module 420 can rearrange scan data exceeding one motion cycle of the target object (e.g., 1.5 motion cycles, 2 motion cycles, 3 motion cycles, etc.) to a specific time period (e.g., 1 motion cycle, 0.75 motion cycles, 0.5 motion cycles, etc.). For a detailed description of the rearrangement of the scan data, please refer to other parts of this specification, for example, Figures 2A-3B Its description will not be repeated here.

[0047] Step 130: Based on the rearranged data, reconstruct multiple images of the target object. In some embodiments, step 130 may be performed by reconstruction module 430.

[0048] The reconstruction module 430 can reconstruct the rearranged data using at least one reconstruction algorithm to generate multiple reconstructed images of the target object. The at least one reconstruction algorithm includes compressed sensing imaging algorithms, parallel imaging algorithms, SENSE (Sensitivity Encoding) imaging algorithms, GRAPPA (Gene Relized Autocalibrating Patially Parallel Acquisitions) imaging algorithms, etc.

[0049] For example, the reconstruction module 430 can reconstruct the rearranged data using a compressed sensing imaging algorithm to generate multiple reconstructed images of the target object. The compressed sensing imaging method obtains the reconstructed image of the target object by iteratively optimizing an objective function. In some embodiments, the number of iterations is related to the objective function and a preset threshold. In each iteration, the reconstruction module 430 can determine the value of the objective function and compare it with the preset threshold. When the value of the objective function is lower than the preset threshold, the iteration process terminates, and the resulting image is the reconstructed image of the target object. The preset threshold can be set by the user or determined according to the default settings of the imaging system 400.

[0050] In some embodiments, the objective function includes at least two terms. The first term is a data consistency term (also known as the L2 term), used to ensure consistency between the reconstructed image and the scan data acquired in step 110. The smaller the difference between the acquired scan data and the reconstructed image, the higher the consistency. The second term is a regularization term (also known as the L1 term), which is the absolute value taken after performing a certain sparse transformation on the reconstructed image. In some embodiments, the sparse transformation is performed by subtracting the current reconstructed image from one or more adjacent frames (e.g., two, three, four, five, etc.) of the image, i.e., the TV value.

[0051] For example, the objective function is shown in equation (1):

[0052] argmin d ‖DFCd-S‖ 2 +λ‖Td‖ 1 (1)

[0053] Where, argmin d ‖DFCd-S‖ 2 For data consistency terms, i.e., L2 terms, λ‖Td‖ 1Here, d represents the reconstructed image (including a set of reconstructed image frames), C is the coil sensitivity function, F represents the inverse Fourier transform, D represents the k-space sampling operator, S is the scan data acquired in step 110, T represents the time dimension TV, DFCd is the k-space data corresponding to the reconstructed image, Td is the difference between the current image and neighboring images (e.g., one or more adjacent frames) (e.g., the sum of the absolute values ​​of the differences between each corresponding pixel in the current image and neighboring images), and the weighting coefficient λ is a weighting parameter (also called the regularization coefficient) that controls the relative intensity of the L1 term. The value of λ is between 0 and 1. The weighting coefficient λ can be set by the user or determined according to the default settings of the imaging system 400. For example, λ can be set by the user based on experience. When the weighting coefficient λ is small, the image has a low signal-to-noise ratio and many artifacts, but the motion of the target object is well preserved; when the weighting coefficient λ is large, the image has a high signal-to-noise ratio and few artifacts, but the target object is poorly preserved.

[0054] Step 140: The reconstructed multiple images are rearranged according to scan time to generate a dynamic image of the target object. In some embodiments, step 140 can be performed by the dynamic image generation module 440.

[0055] In step 120, during the rearrangement of the scanned data (first rearrangement), the order of the scanned data (e.g., the first order) is adjusted to a second order, thereby generating the rearranged data. The dynamic image generation module 440 can rearrange the reconstructed image frames according to the scan time (i.e., the data acquisition time) (second rearrangement), restoring the second order of the reconstructed image frames to the first order. The second rearrangement is equivalent to the reverse operation of the first rearrangement. According to the foregoing example, the reconstructed image frames include a first reconstructed image frame, a third reconstructed image frame, and a second reconstructed image frame arranged sequentially in the time direction. The dynamic image generation module 440 can rearrange the reconstructed images (i.e., the first reconstructed image frame, the third reconstructed image frame, and the second reconstructed image frame) according to the scan time to generate a dynamic image. The dynamic image includes a first reconstructed image frame, a second reconstructed image frame, and a third reconstructed image frame arranged in chronological order. The dynamic image can reflect the movement process of the target object over time. Since the TV value of the rearranged data in the time direction is lower than the TV value of the scanned data in the time direction, the dynamic image has higher quality than the original image. In some embodiments, the dynamic image generation module 440 can also restore the time corresponding to each reconstructed image frame. Since the rearrangement module 420 changes the time corresponding to each part of the scan data during the rearrangement process in step 120—for example, in step 120, the rearrangement module 420 rearranges the scan data of two motion cycles of the target object into one motion cycle—the dynamic image generation module 440 can restore the reconstructed images arranged within one motion cycle to two motion cycles while simultaneously restoring the second order of the reconstructed image frames to the first order.

[0056] It should be noted that the above description of method 100 is for illustrative purposes only and does not limit the scope of this specification. Those skilled in the art can make various modifications and changes to method 100 under the guidance of this specification. However, these modifications and changes remain within the scope of this specification.

[0057] Figure 2A This is an exemplary flowchart illustrating the rearrangement of scanned data according to some embodiments of this specification.

[0058] In some embodiments, process 200 may be executed by rearrangement module 420. In some embodiments, the motion state of the target object may be determined based on the scan data or the condition of a reference object. Based on the motion state of the target object, the scan data is rearranged. Specifically:

[0059] Step 210: Obtain the motion state of the target object.

[0060] In some embodiments, the motion state of the target object can be determined based on the scan data. Specifically, the original image of the target object can be reconstructed based on the scan data obtained in step 110. Methods for reconstructing the original image include, but are not limited to, sequence-based imaging algorithms, compressed sensing-based imaging algorithms, parallel imaging algorithms, and deep learning-based imaging algorithms. The reconstructed original image includes a set of original image frames arranged in a first order along the time direction. For each original image frame, a target object or a portion thereof can be identified. Recognition algorithms can be used to identify the target object or a portion thereof based on features of the target object in the original image frames (e.g., contour, shape, size, edges, grayscale values, etc., or combinations thereof). Exemplary recognition algorithms may include scale-invariant feature transform (SIFT) algorithms, speed-up robust feature (SURF) algorithms, features from accelerated segment test (FAST) algorithms, binary robust independent elementary features (BRIEF) algorithms, oriented FAST and rotated BRIEF (ORB) algorithms, or combinations thereof. After identifying the target object or a portion thereof in each original image frame, the motion amplitude (or motion position) of the target object or its portion in that original image frame can be determined. The motion amplitude (or motion position) of the target object or its portion is determined relative to a preset point, a preset line, and / or a preset plane. For example, when the target object is the heart, the position of a certain point on the myocardium (i.e., a part or area of ​​the myocardium) at the end of cardiac contraction is set as the preset point. The motion amplitude (or motion position) of this point on the myocardium when it reaches the preset point can be set to 0. Thus, the motion amplitude (or motion position) of this point on the myocardium relative to the preset point during cardiac movement can be calculated as the motion amplitude (or motion position) of the heart. Based on the time corresponding to each original image frame, the motion amplitude (or motion position) of the target object at each time can be obtained, thereby determining the motion state of the target object.

[0061] In some embodiments, the motion state of the target object can also be determined by monitoring the condition of a reference object. The reference object is associated with the target object. The motion state of the target object can be determined based on detection signals obtained from monitoring the condition of the reference object.

[0062] For example, when the target object is the heart, the reference object can be blood flow in one or more organs of the human body. By monitoring the blood flow status (e.g., velocity or volume) in these organs using detection signals, the cardiac motion state can be determined. For instance, during the generation of scan data, a laser probe can be placed on the patient's finger. The laser probe can monitor the blood flow at the finger using the laser Doppler effect. In some embodiments, the detection signal of the laser probe can be included in the scan data. Based on the signal from the laser probe, the cardiac motion state (e.g., amplitude (or position)) can be determined. Specifically, fluctuations in the signal amplitude of the laser probe can reflect the amplitude (or position) of the cardiac motion. As another example, during the generation of scan data, real-time images or videos of the patient's face can be acquired. Based on these real-time images or videos, the blood flow status of the patient's face can be monitored. Specifically, with the periodic contraction and relaxation of the heart, the blood flow pumped to the capillaries of the patient's face also changes periodically, resulting in periodic changes in the patient's facial color. Computer vision technology is used to analyze real-time images or videos of the patient's face to identify facial color (e.g., the intensity of red) and thus determine the blood flow status of the patient's face. Based on the color of the patient's face, the cardiac motion status (e.g., amplitude (or position)) can be determined. Specifically, the intensity of red on the patient's face can reflect the amplitude (or position) of cardiac motion.

[0063] Step 220: Based on the motion state of the target object, rearrange the scan data to generate rearranged data.

[0064] In this embodiment, the rearrangement module 420 can rearrange the scanned data based on the motion state, that is, the motion amplitude (or motion position) of the target object at different times corresponding to each part of the scanned data (hereinafter referred to as the motion amplitude (or motion position) corresponding to each part of the scanned data). During the rearrangement process, the motion amplitude (or motion position) corresponding to each part of the scanned data does not change, only the arrangement order of each part of the scanned data in the time direction is changed from the first order to the second order. After rearranging to the second order, the TV value of the rearranged data in the time direction is lower than the TV value of the scanned data in the time direction, making the difference in the motion amplitude of the target object smaller.

[0065] The rearrangement module 420 can rearrange the scan data based on the magnitude of the motion amplitude (or motion position). In some embodiments, the scan data can be rearranged in ascending order of the motion amplitude (or motion position). In some embodiments, the scan data can be rearranged in descending order of the motion amplitude (or motion position). During the ascending or descending arrangement, scan data corresponding to similar motion amplitudes (or motion positions) are rearranged to adjacent positions, so that the TV value of the rearranged data in the time direction is lower than the TV value of the scan data in the time direction. This results in smaller changes in the time direction between the image frames corresponding to the rearranged data, that is, the motion amplitude of the target object is smaller and the motion is smoother. Therefore, motion artifacts can be reduced, better imaging quality can be obtained, and optimal image quality can be obtained while ensuring temporal and spatial resolution.

[0066] In some embodiments, the time corresponding to each part of the scan data also changes. For example, the rearrangement module 420 can rearrange scan data that exceeds one motion cycle of the target object (e.g., 1.5 motion cycles, 2 motion cycles, 3 motion cycles, etc.) into half of the first motion cycle. In some embodiments, the first cycle is equal to the motion cycle of the target object.

[0067] For example, Figure 2B The diagram illustrates how scan data is rearranged to half of the first motion cycle based on the motion state of the target object. The horizontal axis represents time, and the vertical axis represents the motion amplitude (or position) of the target object. The scan data includes scan data 235 from two motion cycles of the target object, where the scan data from the first cycle is represented by circles, and the scan data from the second cycle is represented by squares. Based on the motion state of the target object (i.e., the motion amplitude (or position) corresponding to each part of the scan data, represented by discrete points in the diagram), the rearrangement module can rearrange the scan data 335 from the two motion cycles to half of the first motion cycle to generate rearranged data 245. During the rearrangement process, the motion amplitude (or position) corresponding to each part of the scan data remains unchanged; only the temporal order of the scan data is changed from a first order to a second order. Figure 2B As shown, the scan data is rearranged in descending order of motion amplitude (or motion position) values. The TV value in the time direction of the rearranged data 245 is lower than that of the scan data 235 in the time direction. For example, the TV value of the scan data 235 is 7.4, while the TV value of the rearranged data 245 is 3.7. Therefore, the motion of the target object becomes slower after rearrangement. When reconstructing the image of the target object based on the rearranged data, the difference between adjacent images becomes smaller, thus obtaining a better reconstructed image without affecting the accuracy of the motion.

[0068] It should be noted that the above description of method 200 is for illustrative purposes only and does not limit the scope of this specification. Those skilled in the art can make various modifications and changes to method 200 under the guidance of this specification. However, these modifications and changes are still within the scope of this specification. In some embodiments, the first period may also be greater than or less than the movement period of the target object. For example, the first period may be 0.5 times, 0.8 times, 1.2 times, 1.5 times, etc., of the movement period of the target object.

[0069] Figure 3A This is an exemplary flowchart illustrating the rearrangement of scanned data according to some embodiments of this specification.

[0070] In some embodiments, process 300 can be executed by rearrangement module 420. In some embodiments, motion information of the target object can be obtained based on reference information. Based on the motion information of the target object, the scan data is rearranged. Specifically:

[0071] Step 310: Obtain reference information, which includes the second motion cycle and the motion state of the target object.

[0072] In some embodiments, the reference information may be obtained from a reference (monitoring) device. The reference device may be part of the scanning device or independent of the scanning device. The reference device may be an electrocardiogram (ECG) signal acquisition device, or other devices (e.g., a strap for monitoring respiratory movements, radar, or image monitoring equipment) used to determine the second motion cycle and monitor the motion state of the target object or a portion thereof. In some embodiments, the reference device may include at least one motion sensor (e.g., an infrared sensor, microwave sensor, laser sensor, accelerometer, piezoelectric sensor, capacitive sensor, inductive sensor, etc.). For example, the target object is the heart, and the reference device may include an ECG / blood pressure monitor, an ECG machine, an electronic blood pressure monitor, a smart bracelet, a stethoscope, etc., and the reference device may generate a motion atlas (e.g., an ECG). The motion atlas includes the heart's motion cycle (i.e., the second motion cycle) and motion state.

[0073] In some embodiments, the reference information may be acquired simultaneously with the scan data. For example, when the scanning device scans the target object and acquires the scan data, the reference device may acquire the reference information at the same time. In some embodiments, the reference information may also be acquired before or after acquiring the scan data. For example, after the scanning device scans the target object and acquires the scan data, the reference device begins acquiring the reference information.

[0074] Step 320: Based on the second motion cycle and the motion state of the target object, rearrange the scan data to generate rearranged data.

[0075] In this embodiment, the rearrangement module 420 can rearrange the scan data based on the second motion cycle and the motion state of the target object, i.e., the motion amplitude (or motion position) corresponding to each part of the scan data. During the rearrangement process, the motion amplitude (or motion position) corresponding to each part of the scan data does not change; only the arrangement order of the scan data in the time direction is changed from the first order to the second order. After rearranging to the second order, the TV value of the rearranged data in the time direction is lower than the TV value of the scan data in the time direction, making the difference in the motion amplitude of the target object smaller. At the same time, during the rearrangement process, the rearrangement module 420 refers to the second motion cycle and rearranges the scan data that exceeds one motion cycle of the target object (e.g., 1.5 motion cycles, 2 motion cycles, 3 motion cycles, etc.). For example, scan data that exceeds one motion cycle of the target object can be rearranged into the second motion cycle. In some embodiments, the second motion cycle is equal to the motion cycle of the target object.

[0076] The rearrangement module 420 rearranges the scan data to corresponding positions within the second motion cycle based on the motion amplitude (or motion position) of the target object corresponding to each part of the scan data and its position within the motion cycle of the target object. For example, for scan data containing two motion cycles A and B of the target object, the scan data at 1 / 4 (time direction) of motion cycle A and 1 / 3 (time direction) of motion cycle B are rearranged to 1 / 4 and 1 / 3 of the second motion cycle, respectively. Scan data corresponding to the same or similar positions in different motion cycles of the target object are rearranged to adjacent positions within the same cycle (i.e., the second motion cycle), making the TV value of the rearranged data lower than the TV value of the scan data in the time direction. This results in smaller changes in the time direction between the image frames corresponding to the rearranged data, meaning the motion amplitude of the target object is smaller and the motion is smoother. Therefore, motion artifacts can be reduced, better imaging quality can be obtained, and optimal image quality can be obtained while ensuring temporal and spatial resolution.

[0077] For example, Figure 3BThe diagram illustrates the rearrangement of scan data into the second motion cycle based on the second motion cycle and the motion state of the target object. The horizontal axis represents time, and the vertical axis represents the motion amplitude (or position) of the target object. The scan data includes scan data 335 from two motion cycles of the target object, where the scan data from the first cycle is represented by circles, and the scan data from the second cycle is represented by squares. Based on reference information, the rearrangement module can rearrange the scan data 335 from the two motion cycles into the second motion cycle to generate rearranged data 345. During the rearrangement process, the motion amplitude (or position) corresponding to each part of the scan data remains unchanged; only the temporal order of the scan data parts changes from a first order to a second order. Simultaneously, referring to the second motion cycle, scan data exceeding one motion cycle of the target object (e.g., 1.5 motion cycles, 2 motion cycles, 3 motion cycles, etc.) is rearranged. The TV value of the rearranged data 345 in the temporal direction is lower than the TV value of the scan data 335 in the temporal direction. For example, the TV value of scan data 335 is 7.4, while the TV value of rearranged data 345 is 2.0. Therefore, the movement of the target object becomes slower after rearrangement. When reconstructing the image of the target object based on the rearranged data, the difference between adjacent images becomes smaller, thus obtaining a better reconstructed image without affecting the accuracy of the motion.

[0078] It should be noted that the above description of method 300 is for illustrative purposes only and does not limit the scope of this specification. Those skilled in the art can make various modifications and changes to method 300 under the guidance of this specification. However, these modifications and changes are still within the scope of this specification. In some embodiments, the second period may be greater than or less than the movement period of the target object. For example, the second period may be 0.5 times, 0.8 times, 1.2 times, 1.5 times, 1.8 times, etc., the movement period of the target object.

[0079] Figure 4 This is an exemplary block diagram of an imaging system according to some embodiments of this specification.

[0080] like Figure 4 As shown, the imaging system 400 may include an acquisition module 410, a rearrangement module 420, a reconstruction module 430, and a dynamic image generation module 440. In some embodiments, the imaging system 400 may be implemented by an imaging device 500 (such as a processor 520).

[0081] The acquisition module 410 can acquire the scan data of the target object within a scanning time period, wherein the scanning time period exceeds one motion cycle of the target object.

[0082] The rearrangement module 420 can rearrange the scanned data to generate rearranged data. In some embodiments, the rearrangement module 420 can obtain the motion state of the target object based on the scanned data or the state of a reference object. Based on the motion state of the target object, the scanned data is rearranged to generate rearranged data. In some embodiments, the rearrangement module 420 can obtain reference information, which includes a second motion cycle and the motion state of the target object. Based on the second motion cycle and the motion state of the target object, the scanned data is rearranged to generate rearranged data.

[0083] The reconstruction module 430 can reconstruct multiple images of the target object based on the rearranged data.

[0084] The dynamic image generation module 440 can rearrange multiple reconstructed images according to the scanning time to generate a dynamic image of the target object.

[0085] It should be noted that the above description of the imaging system and its modules is for convenience only and should not limit this application to the scope of the embodiments described. It is understood that those skilled in the art, after understanding the principle of the system, may arbitrarily combine the modules or construct subsystems connected to other modules without departing from this principle. In some embodiments, Figure 4 The acquisition module 410, rearrangement module 420, reconstruction module 430, and dynamic image generation module 440 disclosed herein can be different modules within a single system, or a single module can implement the functions of two or more of the aforementioned modules. For example, the modules can share a single storage module, or each module can have its own separate storage module. Such variations are all within the scope of protection of this application.

[0086] Figure 5 This is an exemplary structural diagram of an imaging device 500 according to some embodiments of this specification. Figure 5 As shown, the imaging device 500 may include a memory 510, a processor 520, and a communication bus. The memory 510 and the processor 520 can communicate with each other via the communication bus. The processor 520 can be used to execute the dynamic imaging method provided in any of the above embodiments of this application.

[0087] In some embodiments, the processor 520 may be implemented as a central processing unit, server, terminal device, or any other possible processing device. In some embodiments, the aforementioned central processing unit, server, terminal device, or other processing device may be implemented on a cloud platform. In some embodiments, the aforementioned central processing unit, server, or other processing device may be interconnected with various terminal devices, and the terminal devices may perform information processing tasks or partial information processing tasks.

[0088] In some embodiments, memory 510 (or a computer-readable storage medium) may store data and / or instructions (such as computer instructions). In some embodiments, memory 510 may store computer instructions that processor 520 (or a computer) can read to execute the dynamic imaging method provided in any embodiment of this specification. In some embodiments, the storage device may include mass storage, removable storage, volatile read-write storage, read-only storage (ROM), and any combination thereof. In some embodiments, the storage device may be implemented on a cloud platform.

[0089] The beneficial effects that the embodiments of this specification may bring include, but are not limited to: (1) making the phase of the scanned data more accurate; (2) making the temporal variation between the image frames corresponding to the rearranged data smaller, that is, making the motion amplitude of the target object smaller and the motion smoother, reducing motion artifacts; (3) obtaining the optimal image quality while ensuring temporal and spatial resolution. It should be noted that different embodiments may produce different beneficial effects. In different embodiments, the beneficial effects that may be produced can be any one or a combination of the above, or any other possible beneficial effects.

[0090] The basic concepts have been described above. Obviously, for those skilled in the art, the detailed disclosure above is merely illustrative and does not constitute a limitation of this specification. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this specification. Such modifications, improvements, and corrections are suggested in this specification and therefore remain within the spirit and scope of the exemplary embodiments described herein.

[0091] Furthermore, this specification uses specific terms to describe embodiments thereof. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic associated with at least one embodiment of this specification. Therefore, it should be emphasized and noted that references to "an embodiment," "one embodiment," or "an alternative embodiment" in different locations throughout this specification do not necessarily refer to the same embodiment. Moreover, certain features, structures, or characteristics in one or more embodiments of this specification can be appropriately combined.

[0092] Furthermore, unless expressly stated in the claims, the order of processing elements and sequences, the use of numbers and letters, or other names described in this specification are not intended to limit the order of the processes and methods described herein. Although various examples have been discussed in the foregoing disclosure of some embodiments of the invention that are currently considered useful, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments; rather, the claims are intended to cover all modifications and equivalent combinations that conform to the spirit and scope of the embodiments described herein. For example, while the system components described above can be implemented using hardware devices, they can also be implemented solely using software solutions, such as installing the described system on existing servers or mobile devices.

[0093] Similarly, it should be noted that, in order to simplify the description disclosed herein and thus aid in the understanding of one or more embodiments of the invention, the foregoing description of embodiments in this specification may sometimes combine multiple features into a single embodiment, drawing, or description thereof. However, this method of disclosure does not imply that the subject matter of this specification requires more features than those mentioned in the claims. In fact, the embodiments contain fewer features than all the features of a single embodiment disclosed above.

[0094] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of embodiments are modified in some examples with the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of range in some embodiments of this specification are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

[0095] For each patent, patent application, patent application publication, and other material, such as articles, books, specifications, publications, and documents, referenced in this specification, the entire contents of which are incorporated herein by reference. This excludes historical application documents that are inconsistent with or conflict with the content of this specification, as well as documents that limit the broadest scope of the claims in this specification (currently or subsequently appended to this specification). It should be noted that in the event of any inconsistency or conflict between the descriptions, definitions, and / or terminology used in the supplementary materials to this specification and the content of this specification, the descriptions, definitions, and / or terminology used in this specification shall prevail.

[0096] Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments described herein. Other variations may also fall within the scope of this specification. Therefore, alternative configurations of the embodiments described herein are intended to be illustrative rather than limiting, and should be considered consistent with the teachings of this specification. Accordingly, the embodiments described herein are not limited to those explicitly introduced and described herein.

Claims

1. A dynamic image generation method characterized by, The method comprises: acquiring scan data of a target object in a scan time period, the scan time period exceeding one motion cycle of the target object; rearranging the scan data to generate rearranged data, the total variation of the rearranged data in a time direction being lower than the total variation of the scan data in the time direction; the rearranging the scan data to generate rearranged data further comprises: acquiring a motion state of the target object, the motion state comprising a motion amplitude; and rearranging the scan data to generate the rearranged data based on ascending or descending order of values of the motion amplitude of the target object; reconstructing multiple images of the target object based on the rearranged data; and rearranging the reconstructed multiple images by scan time to generate a dynamic image of the target object.

2. The dynamic image generation method according to claim 1, characterized by, The motion state of the target object is determined based on a detection signal of a reference object associated with the target object.

3. The dynamic image generation method according to claim 1, characterized by, The rearranged data is within half of the first motion cycle.

4. The dynamic image generation method according to claim 1, characterized by, The method further comprises: acquiring reference information, the reference information comprising a second motion cycle and a motion state of the target object.

5. The dynamic image generation method according to claim 4, characterized by, The rearranging the scan data to generate rearranged data comprises: rearranging the scan data to generate the rearranged data based on the second motion cycle and the motion state of the target object.

6. The dynamic image generation method according to claim 5, characterized by, The rearranged data is within the second motion cycle.

7. The dynamic image generation method according to any one of claims 1-6, characterized by, The method further comprises: performing phase correction on the scan data.

8. A dynamic image generation system characterized by comprising: The method comprises an acquiring module, a rearranging module, a reconstructing module and a dynamic image generating module; wherein, the acquiring module is configured to acquire scan data of a target object in a scan time period, the scan time period exceeding one motion cycle of the target object; the rearranging module is configured to rearrange the scan data to generate rearranged data, the total variation of the rearranged data in a time direction being lower than the total variation of the scan data in the time direction; the rearranging module is further configured to: acquire a motion state of the target object, the motion state comprising a motion amplitude; and rearrange the scan data to generate the rearranged data based on ascending or descending order of values of the motion amplitude of the target object; the reconstructing module is configured to reconstruct multiple images of the target object based on the rearranged data; and the dynamic image generating module is configured to rearrange the reconstructed multiple images by scan time to generate a dynamic image of the target object.

9. A dynamic image generation system, characterized by comprising: The method comprises a processor, and the processor is configured to perform the dynamic imaging method according to any one of claims 1-7.

Images