Magnetic resonance imaging method, apparatus, computer equipment and storage medium

Abstract

The present application relates to a magnetic resonance imaging method, apparatus, computer device, and storage medium. The method comprises: setting multiple radial sampling trajectories in K-space; wherein the multiple radial sampling trajectories include a first radial sampling trajectory and at least one second radial sampling trajectory, wherein the second radial sampling trajectory is obtained by rotating the first radial sampling trajectory according to a preset step angle; acquiring magnetic resonance signals according to the multiple radial sampling trajectories, and filling the acquired magnetic resonance signals into K-space; and reconstructing an image based on the filled data in the K-space to obtain a magnetic resonance image. Using this method, a magnetic resonance image that meets the user's needs can be obtained without the user holding their breath.

Description

Technical Field

[0001] The present application relates to the field of magnetic resonance technology, and in particular to a magnetic resonance imaging method, apparatus, computer equipment, and storage medium. Background Art

[0002] Magnetic resonance imaging (MRI) imaging technology is one of the most advanced medical imaging methods today and has been increasingly widely used in clinical practice and scientific research.

[0003] Currently, MRI images are easily affected by the patient's respiratory motion, which can produce motion artifacts. Therefore, patients are required to hold their breath multiple times during the scan to prevent respiratory motion from affecting the image quality. However, if the patient cannot hold their breath, or if the breath-holding time is insufficient, the image quality requirements cannot be met. Summary of the Invention

[0004] Based on this, it is necessary to provide a magnetic resonance imaging method, apparatus, computer equipment and storage medium that can meet the imaging quality requirements without the user holding their breath to address the above technical problems.

[0005] A magnetic resonance imaging method, the method comprising:

[0006] Setting a plurality of radial sampling trajectories in the K space; wherein the plurality of radial sampling trajectories include a first radial sampling trajectory and at least one second radial sampling trajectory, wherein the second radial sampling trajectory is obtained by rotating the first radial sampling trajectory according to a preset step angle;

[0007] Magnetic resonance signals are collected according to multiple radial sampling trajectories, and the collected magnetic resonance signals are filled into the K space;

[0008] Image reconstruction is performed based on the filling data in the K space to obtain a magnetic resonance image.

[0009] In one embodiment, the setting of the plurality of radial sampling trajectories in the K-space includes:

[0010] Get the number of rotations and step angles;

[0011] Determine a first spoke passing through the center of the K space in the K space, and determine the first spoke as a first radial sampling trajectory;

[0012] The first radial sampling trajectory is rotated according to the rotation number and the step angle to obtain at least one second radial sampling trajectory.

[0013] In one embodiment, the process of obtaining the step angle includes:

[0014] Obtain the user setting parameters and calculate the step angle according to the mapping relationship between the step angle and the user setting parameters.

[0015] In one embodiment, the image reconstruction based on the filling data in the K-space to obtain the magnetic resonance image includes:

[0016] After scanning the target object, the filling data in the K space is processed in stages to obtain the filling data corresponding to each stage;

[0017] Image reconstruction is performed based on the filling data corresponding to each phase to obtain the magnetic resonance image corresponding to each phase.

[0018] In one embodiment, after scanning the target object, the filling data in the K space is processed in stages to obtain filling data corresponding to each stage, including:

[0019] Perform image reconstruction based on the filling data in the K space and the preset time resolution to obtain multiple reconstructed images;

[0020] Performing density conversion processing on multiple reconstructed images to obtain an arterial input function curve;

[0021] According to the arterial input function curve and the preset duration of each phase, the filling data in the K space is processed in phases to obtain the filling data corresponding to each phase.

[0022] In one embodiment, the image reconstruction is performed based on the filling data in the K-space and the preset time resolution to obtain multiple reconstructed images, including:

[0023] Dividing the filling data in the K space into a plurality of sub-filling data according to a preset time resolution;

[0024] Image reconstruction is performed according to each sub-filling data to obtain a reconstructed image corresponding to each sub-filling data.

[0025] In one embodiment, the image reconstruction based on the filling data in the K-space to obtain the magnetic resonance image includes:

[0026] Based on the filled data in the K space, undersampled data of unfilled positions in the K space are obtained through iterative processing;

[0027] Image reconstruction is performed based on the filling data and under-sampling data in the K space to obtain a magnetic resonance image.

[0028] A magnetic resonance imaging apparatus, comprising:

[0029] a sampling trajectory setting module, configured to set a plurality of radial sampling trajectories in the K space; wherein the plurality of radial sampling trajectories includes a first radial sampling trajectory and at least one second radial sampling trajectory, wherein the second radial sampling trajectory is obtained by rotating the first radial sampling trajectory according to a preset step angle;

[0030] a signal acquisition module, configured to acquire magnetic resonance signals according to the plurality of radial sampling trajectories and fill the acquired magnetic resonance signals into the K space;

[0031] The image reconstruction module is used to perform image reconstruction according to the filling data in the K space to obtain a magnetic resonance image.

[0032] In one embodiment, the sampling trajectory setting module is specifically used to obtain the number of rotations and the step angle; determine the first spoke passing through the center of the K space in the K space, and determine the first spoke as the first radial sampling trajectory; rotate the first radial sampling trajectory according to the number of rotations and the step angle to obtain at least one second radial sampling trajectory.

[0033] In one embodiment, the sampling trajectory setting module is specifically configured to obtain user setting parameters and calculate the step angle according to a mapping relationship between the step angle and the user setting parameters.

[0034] In one embodiment, the image reconstruction module includes:

[0035] The phase division submodule is used to perform phase division processing on the filling data in the K space after scanning the target object, so as to obtain the filling data corresponding to each phase;

[0036] The image reconstruction submodule is used to reconstruct the image according to the filling data corresponding to each phase to obtain the magnetic resonance image corresponding to each phase.

[0037] In one embodiment, the above-mentioned phase division submodule is specifically used to perform image reconstruction based on the filling data in the K space and a preset time resolution to obtain multiple reconstructed images; perform concentration conversion processing on the multiple reconstructed images to obtain an arterial input function curve; and perform phase division processing on the filling data in the K space based on the arterial input function curve and the preset duration of each phase to obtain filling data corresponding to each phase.

[0038] In one embodiment, the phase division submodule is specifically used to divide the filling data in the K space into a plurality of sub-filling data according to a preset time resolution; and perform image reconstruction according to each sub-filling data to obtain a reconstructed image corresponding to each sub-filling data.

[0039] In one embodiment, the above-mentioned image reconstruction module is specifically used to iteratively process the filling data in the K space to obtain under-sampled data of the unfilled position in the K space; and perform image reconstruction based on the filling data and the under-sampled data in the K space to obtain a magnetic resonance image.

[0040] A computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0041] Setting a plurality of radial sampling trajectories in the K space; wherein the plurality of radial sampling trajectories include a first radial sampling trajectory and at least one second radial sampling trajectory, wherein the second radial sampling trajectory is obtained by rotating the first radial sampling trajectory according to a preset step angle;

[0042] Magnetic resonance signals are collected according to multiple radial sampling trajectories, and the collected magnetic resonance signals are filled into the K space;

[0043] Image reconstruction is performed based on the filling data in the K space to obtain a magnetic resonance image.

[0044] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0045] Setting a plurality of radial sampling trajectories in the K space; wherein the plurality of radial sampling trajectories include a first radial sampling trajectory and at least one second radial sampling trajectory, wherein the second radial sampling trajectory is obtained by rotating the first radial sampling trajectory according to a preset step angle;

[0046] Magnetic resonance signals are collected according to multiple radial sampling trajectories, and the collected magnetic resonance signals are filled into the K space;

[0047] Image reconstruction is performed based on the filling data in the K space to obtain a magnetic resonance image.

[0048] The magnetic resonance imaging method, apparatus, computer device, and storage medium described above set multiple radial sampling trajectories in K-space; acquire magnetic resonance signals according to the multiple radial sampling trajectories and fill the K-space with the acquired magnetic resonance signals; and reconstruct the image based on the filled-in data in the K-space to obtain a magnetic resonance image. Through the disclosed embodiments, the radial sampling trajectories fill the center of K-space multiple times, eliminating motion artifacts and making the magnetic resonance image motion-insensitive. Therefore, a magnetic resonance image that meets the user's needs can be obtained without the user holding their breath. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A diagram of an application environment of a magnetic resonance imaging method according to an embodiment;

[0050] Figure 2 is a schematic flow chart of a magnetic resonance imaging method according to an embodiment;

[0051] Figure 3 is a schematic diagram of a radial sampling trajectory in one embodiment;

[0052] Figure 4 FIG. 1 is a flow chart of steps for setting multiple radial sampling trajectories of K-space in one embodiment;

[0053] Figure 5 FIG. 1 is a flow chart of an image reconstruction step according to filling data in K space in one embodiment;

[0054] Figure 6 is a schematic diagram of magnetic resonance images of each phase in one embodiment;

[0055] Figure 7 is a schematic diagram of scanning a target object in one embodiment;

[0056] Figure 8 Schematic diagram of a flow chart of steps for obtaining filling data corresponding to each period in one embodiment;

[0057] Figure 9 A schematic diagram of an arterial input function curve corresponding to each phase in an embodiment;

[0058] Figure 10 is a structural block diagram of a magnetic resonance imaging device in one embodiment;

[0059] Figure 11 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0061] The magnetic resonance imaging method provided by this application can be applied to Figure 1The application environment shown is a magnetic resonance imaging system. The magnetic resonance imaging system 100 includes a bed 110, an MR scanner 120, and a processor 130. The MR scanner 120 includes a magnet, a radio frequency (RF) transmit coil, a gradient coil, and a RF receive coil. The bed 110 supports the target object 010. The RF transmit coil transmits RF pulses to the target object. The gradient coil generates a gradient field, which can be along a phase encoding direction, a slice selection direction, or a frequency encoding direction. The RF receive coil receives magnetic resonance signals. In one embodiment, the magnet of the MR scanner 120 can be a permanent magnet or a superconducting magnet. Depending on their function, the RF coils that comprise the RF unit can be divided into body coils and local coils. In one embodiment, the RF transmit coil and RF receive coil can be birdcage coils, solenoid coils, saddle coils, Helmholtz coils, array coils, loop coils, and the like. In one specific embodiment, the RF transmit coil is configured as a birdcage coil, and the local coil is configured as an array coil. The array coil can be configured in 4-channel, 8-channel, or 16-channel modes.

[0062] The magnetic resonance system 100 further includes a controller 140 and an output device 150. The controller 140 can simultaneously monitor or control the MR scanner 110, the processor 130, and the output device 150. The controller 140 can include one or a combination of a central processing unit (CPU), an application-specific integrated circuit (ASIC), an application-specific instruction set processor (ASIP), a graphics processing unit (GPU), a physics processing unit (PPU), a digital signal processor (DSP), a field-programmable gate array (FPGA), an ARM processor, and the like.

[0063] Output device 150, such as a display, can display the magnetic resonance image of the region of interest. Furthermore, output device 150 can also display the subject's height, weight, age, imaging site, and the operating status of MR scanner 110. Output device 150 can be a cathode ray tube (CRT) output device, a liquid crystal display (LCD), an organic light emitting diode (OLED), a plasma output device, or a combination thereof.

[0064] The MRI system 100 can be connected to a local area network (LAN), a wide area network (WAN), a public network, a private network, a proprietary network, a public switched telephone network (PSTN), the Internet, a wireless network, a virtual network, or any combination thereof.

[0065] In one embodiment, the processor 130 can control the MR scanner 120 to perform equally spaced or non-equally spaced sampling on the detection object (a part of the target object 010), and control the MR scanner 120 to obtain the magnetic resonance signal of the detection object, and perform Fourier transform on the magnetic resonance signal to obtain a magnetic resonance image of the detection object.

[0066] In one embodiment, Figure 2 As shown, a magnetic resonance imaging method is provided, which is applied to Figure 1 The magnetic resonance system in FIG. 1 is taken as an example to illustrate the method, which includes the following steps:

[0067] Step 201: Set multiple radial sampling trajectories in K space.

[0068] The plurality of radial sampling trajectories include a first radial sampling trajectory and at least one second radial sampling trajectory, wherein the second radial sampling trajectory is obtained by rotating the first radial sampling trajectory according to a preset step angle. Figure 3 As shown, assuming that the radial sampling trajectory in the horizontal direction is the first radial sampling trajectory, the radial sampling trajectories in other directions are all second radial sampling trajectories. In this embodiment, the first radial sampling trajectory is the first spoke, and the second radial sampling trajectory is a second spoke different from the first spoke. The first spoke and the plurality of second spokes form a spoke set with concentric rotation.

[0069] The processor obtains a preset step angle, and then generates a first radial sampling trajectory in the K space (or k space), and then rotates the first radial sampling trajectory according to the step angle to obtain multiple radial sampling trajectories in the K space.

[0070] The step angle may be pre-stored in the processor or input by the user before sampling, which is not limited in the embodiment of the present disclosure.

[0071] Step 202 : Magnetic resonance signals are collected according to a plurality of radial sampling trajectories, and the collected magnetic resonance signals are filled into the K space.

[0072] After setting / determining multiple radial sampling trajectories, the processor of the magnetic resonance system controls the MR scanner to acquire magnetic resonance signals according to the acquired radial sampling trajectories. Thereafter, the processor fills the magnetic resonance signals acquired by the MR scanner into K space.

[0073] Understandably, when using radial sampling trajectories for MRI signal acquisition, the center of K-space is padded multiple times (multiple sampling trajectories intersect at the center of K-space). Because the padded data at the center of K-space affects the contrast of the MRI image, this padded method can eliminate some motion artifacts, making the MRI image insensitive to motion.

[0074] Step 203: Perform image reconstruction based on the filling data in the K space to obtain a magnetic resonance image.

[0075] After the K-space is filled, the processor performs image reconstruction based on the filled data in the K-space to obtain a magnetic resonance image. For example, image reconstruction in the K-space can use a sensitivity encoding (SENSE) reconstruction method, a simultaneous acquisition of spatial harmonics (SMASH) method, a generalized self-calibrated partially parallel acquisition (GRAPPA) method, a machine learning-based reconstruction method, a compressed sensing algorithm, etc. The disclosed embodiments do not limit the image reconstruction method and can be set according to actual conditions.

[0076] Taking the compressed sensing algorithm as an example, the image reconstruction process may include: based on the filling data in the K space, iterative processing to obtain under-sampled data of the unfilled positions in the K space; and image reconstruction based on the filling data and under-sampled data in the K space to obtain a magnetic resonance image.

[0077] In K-space, locations along the radial sampling trajectory are filled, while locations outside the radial sampling trajectory are unfilled. The processor can iteratively process the filled data in K-space using a compressed sensing algorithm to obtain undersampled data for the unfilled locations. This undersampled data is then filled into K-space. The processor then reconstructs the image based on the filled and undersampled data in K-space to obtain a magnetic resonance image.

[0078] In the aforementioned magnetic resonance imaging method, multiple radial sampling trajectories are set in K-space; magnetic resonance signals are acquired according to the multiple radial sampling trajectories and the acquired magnetic resonance signals are filled into K-space; and image reconstruction is performed based on the filled data in K-space to obtain a magnetic resonance image. In the disclosed embodiments, the radial sampling trajectories are used to fill the center of K-space multiple times, thereby eliminating motion artifacts and making the magnetic resonance image insensitive to motion. Therefore, a magnetic resonance image that meets the user's needs can be obtained without the user having to hold their breath.

[0079] In one embodiment, Figure 4As shown, the step of setting multiple radial sampling trajectories of the K space may include:

[0080] Step 301: Obtain the number of rotations and the step angle.

[0081] Before signal acquisition, the user can input the number of rotations as required; correspondingly, the processor obtains the number of rotations input by the user.

[0082] The process of obtaining the step angle includes: obtaining user-set parameters and calculating the step angle based on the mapping relationship between the step angle and the user-set parameters. In actual application, the user inputs the user-set parameters according to needs, and the processor calculates the step angle based on the user-set parameters and the mapping relationship.

[0083] Among them, the step angle is The step angle can be set to a Fibonacci-like angle. Or, step angle The user sets the parameter N as a positive integer. In this embodiment, N is equal to the number of spokes.

[0084] For example, if the processor obtains the user setting parameter as 1, it can calculate the step angle as or The processor obtains the user setting parameter as 2, and can calculate the step angle as or

[0085] Step 302: determine a first spoke passing through the center of the K space in the K space, and determine the first spoke as a first radial sampling trajectory.

[0086] After obtaining the number of rotations and the step angle, the processor generates a straight line in K-space along any direction passing through the center of K-space as the first spoke. For example, a straight line passing through the origin of K-space can be generated horizontally in K-space, or a straight line passing through the origin of K-space can be generated vertically in K-space. This disclosed embodiment does not limit the generation direction. After the first spoke is generated, it is determined as the first radial sampling trajectory.

[0087] Step 303: Rotate the first radial sampling trajectory according to the rotation number and the step angle to obtain at least one second radial sampling trajectory.

[0088] After the first radial sampling trajectory is generated, the first radial sampling trajectory is rotated according to the number of rotations and the step angle to obtain at least one second radial sampling trajectory.

[0089] like Figure 3As shown, when the number of rotations is 2, 2 second radial sampling trajectories can be obtained; when the number of rotations is 7, 6 second radial sampling trajectories can be obtained. It can be understood that when the number of rotations is large enough, the K space is basically filled, and a magnetic resonance image with higher image quality can be obtained. Most importantly, at the set step angle, the entire K space data is approximately uniform at different numbers of rotations. The more uniform the K space data, the better the image quality. It can be obtained that at this step angle, starting from any point and continuously extracting data of any time period, the K space of this data segment is also approximately uniform, thereby meeting the requirements of automatic phase division and realizing dynamic enhanced scanning with free breathing.

[0090] In the process of setting multiple radial sampling trajectories of the K space, the number of rotations and the step angle are obtained; the first spoke passing through the center of the K space is determined in the K space, and the first spoke is determined as the first radial sampling trajectory; the first radial sampling trajectory is rotated according to the number of rotations and the step angle to obtain at least one second radial sampling trajectory. In the embodiment of the present disclosure, the step angle and The step angle has a mapping relationship with the user-set parameters. The step angle can avoid the second radial sampling trajectory obtained by the subsequent rotation from overlapping with the second radial sampling trajectory obtained by the previous rotation. The entire K-space data is approximately uniform under different rotation times. When the number of rotations is sufficient, the K-space is basically filled to meet the basic data volume requirements of parallel imaging, and a magnetic resonance image with imaging quality that meets user needs can be obtained.

[0091] In one embodiment, Figure 5 As shown, the above step of performing image reconstruction based on the filling data in the K space to obtain a magnetic resonance image may include:

[0092] Step 401 : After scanning the target object, the filling data in the K space is processed in phases to obtain filling data corresponding to each phase.

[0093] Phases can include the plain phase, arterial phase, portal venous phase, and delayed phase. The liver is characterized by dual blood supply from the hepatic artery and portal vein. Liver cancer is a highly vascular tumor, and its development is often accompanied by increased hepatic arterial blood flow and decreased portal venous blood flow. After contrast agent is injected into the patient, during the arterial phase, the contrast agent primarily reaches the liver via the arteries. Arterial blood transports the contrast agent to the liver parenchyma while also supplying the lesion. This perfusion of contrast enhances the lesion. Although the liver parenchyma is also filled with contrast agent from the hepatic artery, the portal vein is not yet filled with contrast agent. The large volume of blood from the portal vein dilutes the contrast agent delivered from the arteries, resulting in only mild enhancement of the liver parenchyma. Consequently, the enhanced lesion exhibits a significant density contrast against the background of the mildly enhancing liver parenchyma, resulting in enhanced appearance during the arterial phase. During the portal venous phase, a large volume of contrast-containing blood enters the liver from the spleen and digestive tract via the portal venous system, leading to significant enhancement of the liver parenchyma, while the lesion exhibits weaker enhancement compared to the liver parenchyma.

[0094] Optionally, the abdomen can be selected as the scanning area of ​​the target subject, as this scanning area is easily affected by respiratory motion. After performing a dynamic enhanced scan on the abdomen of the target subject, the processor obtains the filling data in the K space and then performs phase processing on the filling data in the K space according to the duration of each phase to obtain filling data corresponding to the plain scan phase, filling data corresponding to the arterial phase, filling data corresponding to the portal venous phase, and filling data corresponding to the delayed phase.

[0095] Step 402 : reconstructing an image based on the filling data corresponding to each phase to obtain a magnetic resonance image corresponding to each phase.

[0096] For each phase, image reconstruction is performed based on the filling data corresponding to the phase to obtain the magnetic resonance image corresponding to the phase. Figure 6 As shown, image reconstruction is performed based on the filling data corresponding to the plain scan period to obtain a magnetic resonance image corresponding to the plain scan period; image reconstruction is performed based on the filling data corresponding to the arterial phase to obtain a magnetic resonance image corresponding to the arterial phase; image reconstruction is performed based on the filling data corresponding to the portal venous phase to obtain a magnetic resonance image corresponding to the portal venous phase; image reconstruction is performed based on the filling data corresponding to the delayed phase to obtain a magnetic resonance image corresponding to the delayed phase.

[0097] like Figure 7 As shown, in the prior art, during the scanning of a target object, the target object is required to hold his breath multiple times. For example, the first breath-hold is required during the plain scan phase, the second breath-hold is required during the arterial phase after contrast agent injection, the third breath-hold is required during the portal venous phase, and the fourth breath-hold is required during the delayed phase. However, in the disclosed embodiment, due to the use of radial sampling trajectories to fill K-space, it is possible to obtain K-space filling data of any temporal resolution from any time point for image reconstruction, and thus obtain magnetic resonance images with good image quality. Therefore, during the scanning of the target object, the target object does not need to hold his breath.

[0098] In the above-described process of reconstructing the image based on the filling data in K-space to obtain a magnetic resonance image, after performing a dynamic enhancement scan on the target subject's abdomen, the filling data in K-space is phased to obtain filling data corresponding to each phase; and image reconstruction is performed based on the filling data corresponding to each phase to obtain a magnetic resonance image corresponding to each phase. The disclosed embodiments utilize radial sampling trajectories to fill K-space, thereby not only achieving high-quality magnetic resonance images without requiring the target subject to hold their breath, but also, because the phases are automatically divided based on the filling data in K-space, there is no need to monitor the flow of contrast agent, making it easier to obtain dynamic enhancement images.

[0099] In one embodiment, Figure 8 As shown, after performing dynamic enhanced scanning on the abdomen of the target object, the step of performing phase-by-phase processing on the filling data in the K space to obtain filling data corresponding to each phase may include:

[0100] Step 501 : performing image reconstruction according to the filling data in the K space and a preset time resolution to obtain a plurality of reconstructed images.

[0101] The processor divides the filling data in the K space into a plurality of sub-filling data according to a preset time resolution; performs image reconstruction according to each sub-filling data, and obtains a reconstructed image with a high time resolution corresponding to each sub-filling data.

[0102] For example, if the acquisition time of the filling data in K space is a and the preset time resolution is b, the filling data in K space is divided into a / b sub-filling data. Then, image reconstruction is performed based on each sub-filling data to obtain a reconstructed image corresponding to each sub-filling data.

[0103] Step 502: Perform density conversion processing on the multiple reconstructed images to obtain an arterial input function curve.

[0104] During contrast agent inflow, the T1 value of the tissue changes, thus affecting the signal value of the inflow area. Therefore, the processor can perform signal extraction on the abdominal aorta region (the abdominal aorta region can be manually marked before scanning or automatically identified and extracted) in multiple reconstructed images based on the enhancement effect of the liver parenchyma in different reconstructed images. This generates a curve of contrast agent concentration changes in the artery, namely the arterial input function (AIF) curve.

[0105] Step 503 : performing phase processing on the filling data in the K space according to the arterial input function curve and the preset duration of each phase to obtain filling data corresponding to each phase.

[0106] After the processor obtains the arterial input function curve, it can determine the marking point according to the peak value (contrast agent arrival time point) in the arterial input function curve. Then, the position of each phase and the corresponding acquisition data segment are determined according to the duration of each phase and the marking point. Optionally, the number of spokes contained in each phase is equal to the ratio of the duration of the phase to the designed time interval between two adjacent spokes. For example, the time interval between two adjacent spokes corresponds to a preset step angle. Figure 9 As shown, the K-space data is processed by phase, yielding K-space corresponding to the plain scan phase, the arterial phase, the portal venous phase, and the delayed phase. Reconstructing each K-space separately yields a magnetic resonance image for the corresponding phase. In this embodiment, the marker is identified 60 seconds after the scan, and the temporal resolution of the arterial phase is 10 seconds. Therefore, the data from 60 seconds to 70 seconds corresponds to the arterial phase contraction, and the number of spokes collected during this time period corresponds to the number of spokes corresponding to the arterial phase. If the time interval between two consecutive spokes collected within a plane is 100 milliseconds, then there are 10 / (10*1E-3) = 100 spokes in the arterial phase.

[0107] In another embodiment, a multi-slice (Simultaneous Multi-Slice, SMS) imaging technique can be used to collect AIF data of multiple slices of the target area, generate initial curves of the multiple slices, and use the average of the initial curves of the multiple slices as the arterial input function curve. For example, before the contrast agent is injected into the detection area / target area, a reference signal of each slice of the target area can be collected separately, and the target area includes multiple slices; after the contrast agent is injected into the target area, the AIF aliased signals of the multiple slices are simultaneously excited and collected; the AIF aliased signals are reconstructed using the reference signals of the multiple slices to obtain an AIF reconstructed image of each slice; the AIF reconstructed image of each slice is subjected to concentration conversion processing to obtain an initial curve of each slice, which is a curve of the change of the contrast agent concentration over time; the initial curves are averaged to obtain the AIF curve. In the embodiment of the present application, by averaging the initial curves of multiple slices, the error of the AIF curve can be reduced, the accuracy of the AIF curve of the target area can be improved, and the influence of blood flow on the AIF curve can be reduced. After performing a dynamic enhanced scan on the abdomen of the target subject, the filling data in the K-space is subjected to phase-by-phase processing to obtain filling data corresponding to each phase. Image reconstruction is then performed based on the filling data in the K-space and a preset time resolution to obtain multiple reconstructed images. Concentration conversion is performed on the multiple reconstructed images to obtain an arterial input function curve. Based on the arterial input function curve and the preset durations of each phase, the filling data in the K-space is subjected to phase-by-phase processing to obtain filling data corresponding to each phase. Through the disclosed embodiments, the arterial input function curve can be obtained based on the filling data in the K-space, and phase division can then be automatically performed based on the arterial input function curve. This allows for acquisition of dynamic enhanced images without monitoring the flow of contrast agent, and the phase division is relatively accurate.

[0108] It should be understood that although Figures 2 to 8 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. In addition, Figures 2 to 8 At least part of the steps may include multiple steps or multiple stages. These steps or stages are not necessarily performed at the same time, but can be performed at different times. The order of execution of these steps or stages is not necessarily one by one, but can be performed in turn or alternately with other steps or at least part of the steps or stages in other steps.

[0109] In one embodiment, Figure 10 As shown, a magnetic resonance imaging device is provided, comprising:

[0110] The sampling trajectory setting module 601 is configured to set a plurality of radial sampling trajectories in the K space; wherein the plurality of radial sampling trajectories includes a first radial sampling trajectory and at least one second radial sampling trajectory, wherein the second radial sampling trajectory is obtained by rotating the first radial sampling trajectory according to a preset step angle;

[0111] a signal acquisition module 602, configured to acquire magnetic resonance signals according to the plurality of radial sampling trajectories and fill the acquired magnetic resonance signals into the K space;

[0112] The image reconstruction module 603 is configured to perform image reconstruction based on the filling data in the K space to obtain a magnetic resonance image.

[0113] In one embodiment, the sampling trajectory setting module 601 is specifically used to obtain the number of rotations and the step angle; determine the first spoke passing through the center of the K space in the K space, and determine the first spoke as the first radial sampling trajectory; rotate the first radial sampling trajectory according to the number of rotations and the step angle to obtain at least one second radial sampling trajectory.

[0114] In one embodiment, the sampling trajectory setting module 601 is specifically configured to obtain user setting parameters and calculate the step angle according to a mapping relationship between the step angle and the user setting parameters.

[0115] In one embodiment, the image reconstruction module 603 includes:

[0116] The phase division submodule is used to perform phase division processing on the filling data in the K space after scanning the target object, so as to obtain the filling data corresponding to each phase;

[0117] The image reconstruction submodule is used to reconstruct the image according to the filling data corresponding to each phase to obtain the magnetic resonance image corresponding to each phase.

[0118] In one embodiment, the above-mentioned phase division submodule is specifically used to perform image reconstruction based on the filling data in the K space and a preset time resolution to obtain multiple reconstructed images; perform concentration conversion processing on the multiple reconstructed images to obtain an arterial input function curve; and perform phase division processing on the filling data in the K space based on the arterial input function curve and the preset duration of each phase to obtain filling data corresponding to each phase.

[0119] In one embodiment, the phase division submodule is specifically used to divide the filling data in the K space into a plurality of sub-filling data according to a preset time resolution; and perform image reconstruction according to each sub-filling data to obtain a reconstructed image corresponding to each sub-filling data.

[0120] In one embodiment, the image reconstruction module 603 is specifically configured to iteratively process the filled data in the K space to obtain undersampled data of unfilled positions in the K space; and perform image reconstruction based on the filled data and undersampled data in the K space to obtain a magnetic resonance image.

[0121] The specific definition of the magnetic resonance imaging apparatus can be found in the definition of the magnetic resonance imaging method above and will not be repeated here. Each module in the magnetic resonance imaging apparatus described above may be implemented in whole or in part through software, hardware, or a combination thereof. Each of the modules described above may be embedded in or independent of a processor in a computer device in hardware form, or may be stored in a computer device memory in software form, so that the processor can call and execute the corresponding operations of each module.

[0122] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 11 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a magnetic resonance imaging method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad provided on the computer device housing, or an external keyboard, touchpad or mouse.

[0123] Those skilled in the art will understand that Figure 11 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0124] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0125] Setting a plurality of radial sampling trajectories in the K space; wherein the plurality of radial sampling trajectories include a first radial sampling trajectory and at least one second radial sampling trajectory, wherein the second radial sampling trajectory is obtained by rotating the first radial sampling trajectory according to a preset step angle;

[0126] Magnetic resonance signals are collected according to multiple radial sampling trajectories, and the collected magnetic resonance signals are filled into the K space;

[0127] Image reconstruction is performed based on the filling data in the K space to obtain a magnetic resonance image.

[0128] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0129] Get the number of rotations and step angles;

[0130] Determine a first spoke passing through the center of the K space in the K space, and determine the first spoke as a first radial sampling trajectory;

[0131] The first radial sampling trajectory is rotated according to the rotation number and the step angle to obtain at least one second radial sampling trajectory.

[0132] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0133] Obtain the user setting parameters and calculate the step angle according to the mapping relationship between the step angle and the user setting parameters.

[0134] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0135] After scanning the target object, the filling data in the K space is processed into phases to obtain the filling data corresponding to each phase; wherein the phases include the plain scan phase, arterial phase, portal phase and delayed phase;

[0136] Image reconstruction is performed based on the filling data corresponding to each phase to obtain the magnetic resonance image corresponding to each phase.

[0137] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0138] Perform image reconstruction based on the filling data in the K space and the preset time resolution to obtain multiple reconstructed images;

[0139] Performing density conversion processing on multiple reconstructed images to obtain an arterial input function curve;

[0140] According to the arterial input function curve and the preset duration of each phase, the filling data in the K space is processed in phases to obtain the filling data corresponding to each phase.

[0141] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0142] Dividing the filling data in the K space into a plurality of sub-filling data according to a preset time resolution;

[0143] Image reconstruction is performed according to each sub-filling data to obtain a reconstructed image corresponding to each sub-filling data.

[0144] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0145] Based on the filled data in the K space, undersampled data of unfilled positions in the K space are obtained through iterative processing;

[0146] Image reconstruction is performed based on the filling data and under-sampling data in the K space to obtain a magnetic resonance image.

[0147] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0148] Setting a plurality of radial sampling trajectories in the K space; wherein the plurality of radial sampling trajectories include a first radial sampling trajectory and at least one second radial sampling trajectory, wherein the second radial sampling trajectory is obtained by rotating the first radial sampling trajectory according to a preset step angle;

[0149] Magnetic resonance signals are collected according to multiple radial sampling trajectories, and the collected magnetic resonance signals are filled into the K space;

[0150] Image reconstruction is performed based on the filling data in the K space to obtain a magnetic resonance image.

[0151] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0152] Get the number of rotations and step angles;

[0153] Determine a first spoke passing through the center of the K space in the K space, and determine the first spoke as a first radial sampling trajectory;

[0154] The first radial sampling trajectory is rotated according to the rotation number and the step angle to obtain at least one second radial sampling trajectory.

[0155] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0156] Obtain the user setting parameters and calculate the step angle according to the mapping relationship between the step angle and the user setting parameters.

[0157] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0158] After performing dynamic enhanced scanning on the target object, the filling data in the K space is processed into phases to obtain filling data corresponding to each phase; wherein the phases include the plain scan phase, arterial phase, portal phase and delayed phase;

[0159] Image reconstruction is performed based on the filling data corresponding to each phase to obtain the magnetic resonance image corresponding to each phase.

[0160] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0161] Perform image reconstruction based on the filling data in the K space and the preset time resolution to obtain multiple reconstructed images;

[0162] Performing density conversion processing on multiple reconstructed images to obtain an arterial input function curve;

[0163] According to the arterial input function curve and the preset duration of each phase, the filling data in the K space is processed in phases to obtain the filling data corresponding to each phase.

[0164] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0165] Dividing the filling data in the K space into a plurality of sub-filling data according to a preset time resolution;

[0166] Image reconstruction is performed according to each sub-filling data to obtain a reconstructed image corresponding to each sub-filling data.

[0167] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0168] Based on the filled data in the K space, undersampled data of unfilled positions in the K space are obtained through iterative processing;

[0169] Image reconstruction is performed based on the filling data and under-sampling data in the K space to obtain a magnetic resonance image.

[0170] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0171] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0172] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A magnetic resonance imaging method, characterized in that: The method comprises: Setting a plurality of radial sampling trajectories in the K space; wherein the plurality of radial sampling trajectories include a first radial sampling trajectory and a plurality of second radial sampling trajectories, wherein the second radial sampling trajectories are obtained by rotating the first radial sampling trajectory according to a preset step angle; Acquiring magnetic resonance signals according to the plurality of radial sampling trajectories, and filling the acquired magnetic resonance signals into the K space; Performing image reconstruction based on the filling data in the K space to obtain a magnetic resonance image; The setting of multiple radial sampling trajectories in the K space includes: Obtain the number of rotations and the user setting parameters, and calculate the step angle according to the mapping relationship between the step angle and the user setting parameters; the step angle is a Fibonacci angle; the step angle is There is a mapping relationship between the user setting parameters, the step angle Or, the step angle The user setting parameter N is a positive integer, and N is equal to the number of spokes; Determining a first spoke passing through the center of the K space in the K space, and determining the first spoke as the first radial sampling trajectory; The first radial sampling trajectory is rotated according to the rotation number and the step angle to obtain a plurality of second radial sampling trajectories, and the plurality of second radial sampling trajectories do not overlap.

2. The method according to claim 1, characterized in that The step of reconstructing an image based on the filling data in the K-space to obtain a magnetic resonance image includes: After scanning the target object, the filling data in the K space is processed in stages to obtain filling data corresponding to each stage; Image reconstruction is performed based on the filling data corresponding to each phase to obtain a magnetic resonance image corresponding to each phase.

3. The method according to claim 2, characterized in that After scanning the target object, the filling data in the K space is processed in stages to obtain filling data corresponding to each stage, including: Performing image reconstruction according to the filling data in the K space and a preset time resolution to obtain a plurality of reconstructed images; performing density conversion processing on the plurality of reconstructed images to obtain an arterial input function curve; According to the arterial input function curve and the preset duration of each phase, the filling data in the K space is processed in phases to obtain the filling data corresponding to each phase.

4. The method according to claim 3, characterized in that The image reconstruction is performed according to the filling data in the K space and the preset time resolution to obtain a plurality of reconstructed images, including: Dividing the filling data in the K space into a plurality of sub-filling data according to a preset time resolution; Image reconstruction is performed according to each of the sub-filling data to obtain a reconstructed image corresponding to each of the sub-filling data.

5. The method according to claim 1, wherein The image reconstruction is performed according to the filling data in the K space to obtain a magnetic resonance image, comprising: Iteratively processing the filled data in the K space to obtain undersampled data at unfilled locations in the K space; Image reconstruction is performed based on the filling data in the K space and the under-sampled data to obtain the magnetic resonance image.

6. A magnetic resonance imaging apparatus, characterized in that: The device comprises: A sampling trajectory setting module is used to set multiple radial sampling trajectories in the K space; wherein the multiple radial sampling trajectories include a first radial sampling trajectory and multiple second radial sampling trajectories, and the second radial sampling trajectories are obtained by rotating the first radial sampling trajectory according to a preset step angle; a signal acquisition module, configured to acquire magnetic resonance signals according to the plurality of radial sampling trajectories and fill the acquired magnetic resonance signals into the K space; An image reconstruction module, configured to perform image reconstruction based on the filling data in the K-space to obtain a magnetic resonance image; The sampling trajectory setting module is specifically used to obtain the number of rotations and the user setting parameters, and calculate the step angle according to the mapping relationship between the step angle and the user setting parameters; the step angle is a Fibonacci angle; the step angle is There is a mapping relationship between the user setting parameters, the step angle Or, the step angle The user sets a parameter N as a positive integer, where N is equal to the number of spokes; a first spoke passing through the center of the K space is determined in the K space, and the first spoke is determined as the first radial sampling trajectory; the first radial sampling trajectory is rotated according to the number of rotations and the step angle to obtain a plurality of second radial sampling trajectories, and the plurality of second radial sampling trajectories do not overlap.

7. The device according to claim 6, characterized in that The image reconstruction module comprises: A phase division submodule is used to perform phase division processing on the filling data in the K space after scanning the target object, so as to obtain filling data corresponding to each phase; The image reconstruction submodule is used to perform image reconstruction based on the filling data corresponding to each phase to obtain the magnetic resonance image corresponding to each phase.

8. The device according to claim 7, characterized in that The phase division submodule is specifically used to perform image reconstruction based on the filling data in the K space and a preset time resolution to obtain multiple reconstructed images; perform concentration conversion processing on the multiple reconstructed images to obtain an arterial input function curve; and perform phase division processing on the filling data in the K space based on the arterial input function curve and the preset duration of each phase to obtain the filling data corresponding to each phase.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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