Perfusion imaging method, apparatus, computer device, storage medium and program product

Abstract

The application relates to a perfusion imaging method, device, computer equipment, storage medium and program product. The method comprises the following steps: acquiring a structure image and a magnetic field distribution diagram corresponding to a to-be-labeled region on a blood vessel image; the to-be-labeled region comprises at least two blood vessel structures; determining a correction parameter according to the structure image and the magnetic field distribution diagram; the correction parameter is used for correcting a magnetic field where the to-be-labeled region is located; and perfusion imaging is performed on the blood vessel image according to the correction parameter to obtain a perfusion imaging result. Since the correction parameter can be accurately determined according to the structure image and the magnetic field distribution diagram corresponding to the to-be-labeled region, the correction parameter can be used to correct the uneven magnetic field where the at least two blood vessel structures in the to-be-labeled region are located, the phase accumulation generated in the to-be-labeled region can be offset, the labeling effect can be improved, perfusion imaging can be performed, and the imaging effect and the quality of the perfusion signal can be improved.

Description

Technical Field

[0001] This application relates to the field of medical technology, and in particular to a perfusion imaging method, apparatus, computer equipment, storage medium, and program product. Background Technology

[0002] With the development of medical technology, various types of magnetic resonance imaging techniques have emerged. For example, arterial spin labeling (ASL) technology can be used for perfusion imaging. In the process of using ASL technology, the arterial blood in the labeled area of ​​the subject needs to be labeled, and after the labeled arterial blood has flowed sufficiently into the imaging area of ​​the subject, the imaging area of ​​the subject is imaged to obtain the labeled image.

[0003] However, current methods for perfusion imaging using ASL technology suffer from poor imaging results. Summary of the Invention

[0004] Therefore, it is necessary to provide a perfusion imaging method, apparatus, computer equipment, storage medium, and program product that can improve the imaging effect of perfusion imaging using ASL technology in response to the above-mentioned technical problems.

[0005] In a first aspect, this application provides a perfusion imaging method, comprising:

[0006] Acquire the structural image and magnetic field distribution map corresponding to the region to be labeled on the vascular image; the region to be labeled includes at least two vascular structures;

[0007] Based on the structural image and the magnetic field distribution map, correction parameters are determined; these correction parameters are used to correct the magnetic field of the region to be labeled.

[0008] Perfusion imaging is performed on the vascular image according to the correction parameters to obtain perfusion imaging results.

[0009] In one embodiment, the structural image includes a first vascular structure and a second vascular structure, and the step of determining the correction parameters based on the structural image and the magnetic field distribution map includes:

[0010] The first and second blood vessel structures in the structural image are identified to determine the first position of the first blood vessel structure and the second position of the second blood vessel structure.

[0011] Based on the first position of the first vascular structure, the second position of the second vascular structure, and the magnetic field distribution map, the offset information of the first vascular structure and the second vascular structure relative to the standard frequency is determined; the offset information includes gradient and off-frequency.

[0012] The correction parameters are determined based on the offset information.

[0013] In one embodiment, determining the offset information of the first and second vascular structures relative to a standard frequency based on the first position of the first vascular structure, the second position of the second vascular structure, and the magnetic field distribution map includes:

[0014] Based on the first position of the first vascular structure and the second position of the second vascular structure, determine the vascular spacing and the vascular center deviation distance between the first vascular structure and the second vascular structure;

[0015] Based on the first mask image corresponding to the first blood vessel structure, the second mask image corresponding to the second blood vessel structure, and the magnetic field distribution map, the first frequency corresponding to the first blood vessel structure and the second frequency corresponding to the second blood vessel structure are determined.

[0016] The offset information is determined based on the blood vessel spacing, the blood vessel center deviation distance, the first frequency, and the second frequency.

[0017] In one embodiment, determining the first frequency corresponding to the first blood vessel structure and the second frequency corresponding to the second blood vessel structure based on the first mask image corresponding to the first blood vessel structure, the second mask image corresponding to the second blood vessel structure, and the magnetic field distribution map includes:

[0018] The first mask image and the magnetic field distribution map are multiplied to generate the first magnetic field distribution map corresponding to the first blood vessel structure, and the first magnetic field distribution map is phase analyzed to obtain the first frequency.

[0019] The second mask image and the magnetic field distribution map are multiplied to generate a second magnetic field distribution map corresponding to the second blood vessel structure. Phase analysis is then performed on the second magnetic field distribution map to obtain the second frequency.

[0020] In one embodiment, identifying the first and second vascular structures in the structural image and determining the first location of the first vascular structure and the second location of the second vascular structure includes:

[0021] Add a first identification box corresponding to the first blood vessel structure and a second identification box corresponding to the second blood vessel structure to the structural image;

[0022] Move the first marker frame to the location of the first blood vessel structure, and move the second marker frame to the location of the second blood vessel structure;

[0023] Based on the moved first and second marker frames, the first position of the first vascular structure and the second position of the second vascular structure are determined.

[0024] In one embodiment, performing perfusion imaging on the vascular image according to the correction parameters to obtain perfusion imaging results includes:

[0025] The magnetic field in the region to be imaged on the blood vessel image is homogenized to obtain homogenization parameters;

[0026] The magnetic field of the region to be marked is corrected according to the correction parameters.

[0027] After marking the region to be marked according to the corrected magnetic field, the region to be imaged is imaged according to the shimming parameters to obtain the perfusion imaging result.

[0028] Secondly, this application also provides a perfusion imaging device, comprising:

[0029] The acquisition module is used to acquire the structural image and magnetic field distribution map corresponding to the region to be labeled on the vascular image; the region to be labeled includes at least two vascular structures;

[0030] The determination module is used to determine correction parameters based on the structural image and the magnetic field distribution map; the correction parameters are used to correct the magnetic field of the region to be marked.

[0031] An imaging module is used to perform perfusion imaging on the blood vessel image according to the correction parameters to obtain perfusion imaging results.

[0032] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method in any of the embodiments of the first aspect described above.

[0033] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the steps of the method in any of the embodiments of the first aspect described above.

[0034] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the steps of the method in any of the embodiments of the first aspect described above.

[0035] The aforementioned perfusion imaging method, apparatus, computer equipment, storage medium, and program product acquire a structural image and magnetic field distribution map corresponding to a region to be labeled on a vascular image. The region to be labeled includes at least two vascular structures. Correction parameters are determined based on the structural image and magnetic field distribution map. These correction parameters are used to correct the magnetic field of the region to be labeled. Perfusion imaging is performed on the vascular image based on the correction parameters to obtain the perfusion imaging result. Since the embodiments of this application can accurately determine the correction parameters based on the structural image and magnetic field distribution map corresponding to the region to be labeled, these correction parameters can be used to correct the non-uniform magnetic field of at least two vascular structures in the region to be labeled, thereby canceling the phase accumulation generated in the region to be labeled, improving the labeling effect, and thus improving the imaging effect and the quality of the perfusion signal. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 This is a schematic diagram of arterial spin labeling perfusion in related technologies;

[0038] Figure 2 This is a diagram illustrating the application environment of the perfusion imaging method in one embodiment;

[0039] Figure 3 This is a flowchart illustrating a perfusion imaging method in one embodiment;

[0040] Figure 4 This is a flowchart illustrating the steps for determining calibration parameters in one embodiment;

[0041] Figure 5 This is a schematic diagram illustrating the determination of a first position, a second position, and offset information in an exemplary embodiment.

[0042] Figure 6 This is a flowchart illustrating the offset information determination steps in one embodiment;

[0043] Figure 7 This is a flowchart illustrating the perfusion imaging method in another embodiment;

[0044] Figure 8 This is a structural block diagram of a perfusion imaging device in one embodiment. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0046] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0047] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0048] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0049] With the development of medical technology, various types of magnetic resonance imaging (MRI) techniques have emerged. For example, arterial spin labeling (ASL) technology can be used for perfusion imaging. ASL sequences use arterial blood as an endogenous marker to achieve non-invasive measurement of perfusion levels in organs such as the brain and kidneys. In the ASL process, the magnetization vector of water in the arterial blood is flipped using pulses to label the arterial blood in the labeled area of ​​the subject. After the labeled arterial blood has fully flowed into the imaging area of ​​the subject, the area is imaged to obtain a labeled image. Simultaneously, an unlabeled control image of the arterial blood can be acquired for comparison. The difference between the control and labeled images is then processed to obtain the raw perfusion signal. Post-processing of the raw perfusion signal yields the corresponding perfusion information.

[0050] like Figure 1 As shown, Figure 1 This is a schematic diagram of arterial spin labeling perfusion in a related technique. Figure 1The image shown is a rat neck vascular TOF MIP (Time-of-Flight Maximum Intensity Projection) map. Taking brain perfusion as an example, the imaging area is located in the brain region, while the labeled area is located in the neck. The labeled arterial blood flow (i.e., Figure 1 Blood at the location indicated by the downward arrow in the marked area will flow sufficiently into the imaging area, where... Figure 1 The upward arrow indicates unlabeled arterial blood. In the default shimming region, the isocenter of the MRI scanner is located in the brain region, meaning that after routine shimming and calibration, the B0 field homogeneity in the brain region is relatively high. However, the labeling region is affected by cavities and special structures such as the esophagus and nasal cavity, making it difficult to guarantee magnetic field homogeneity. This results in partial resonance in the labeling region, and frequency differences between the left and right blood vessels. Therefore, additional phase accumulation occurs during labeling, leading to reduced flipping efficiency, poor labeling results, and affecting the intensity of the perfusion signal. It can also cause asymmetry in the perfusion signals between the left and right brain regions. Therefore, current methods using ASL technology for perfusion imaging suffer from poor imaging results.

[0051] After introducing the background technology of the perfusion imaging method provided in the embodiments of this application, the implementation environment involved in the perfusion imaging method provided in the embodiments of this application will be briefly described below. The perfusion imaging method provided in the embodiments of this application can be applied to, for example... Figure 2The computer device shown can be a terminal or a server. It includes a processor, memory, input / output interfaces, a communication interface, a display unit, and an input device. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements an injection imaging method. The display unit of the computer device forms a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0052] Those skilled in the art will understand that Figure 2 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. A specific terminal may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0053] In one embodiment, such as Figure 3 As shown, a perfusion imaging method is provided, which can be applied to... Figure 1 Taking a computer device as an example, the explanation includes the following steps:

[0054] S201, acquire the structural image and magnetic field distribution map corresponding to the region to be labeled on the blood vessel image; the region to be labeled includes at least two blood vessel structures.

[0055] Among them, the vascular image refers to the image of the blood vessels of the object to be tested. Optionally, the vascular image may include, but is not limited to, the TOF MIP (Time-of-Flight Maximum Intensity Projection) map of the blood vessels, the sagittal structural map, etc. The region to be labeled refers to the labeled area in the perfusion imaging process. The region to be labeled includes at least two vascular structures. The structural image refers to the cross-sectional view of the vascular signal in the region to be labeled. The magnetic field distribution map refers to the schematic diagram of the distribution of the B0 field in the region to be labeled.

[0056] In this embodiment, the user terminal can pre-determine the region to be labeled during the perfusion imaging process and transmit the location information of the region to the computer device. The computer device can then scan the arterial structure within the region to obtain an initial structural image based on the location information. Flow compensation is then applied to the initial structural image to obtain a flow-compensated structural image. The purpose of the flow compensation process is to mark the arterial vessels as bright signals for easy observation by the user. Furthermore, the computer device can also scan the magnetic field corresponding to the region to be labeled based on the location information to obtain a phase-unwound magnetic field distribution map. Of course, this embodiment does not limit the order in which the structural image and the magnetic field distribution map are acquired.

[0057] S202, Based on the structural image and magnetic field distribution map, determine the correction parameters; the correction parameters are used to correct the magnetic field of the area to be marked.

[0058] In this embodiment, optionally, the computer device can determine each vascular structure in the structural image corresponding to the region to be labeled, and calculate and determine the correction parameters based on each vascular structure and the magnetic field distribution map; alternatively, the computer device can also directly calculate and determine the correction parameters based on the structural image and the magnetic field distribution map. Of course, this embodiment does not limit the specific implementation method for determining the correction parameters. The correction parameters are used to correct the non-uniform magnetic field in the region to be labeled.

[0059] S203, perform perfusion imaging on the blood vessel image according to the correction parameters to obtain the perfusion imaging result.

[0060] In this embodiment, the computer device can mark the region to be marked in the vascular image according to correction parameters. Furthermore, the user terminal can pre-determine the region to be imaged during the perfusion imaging process and transmit the location information of the region to the computer device. Thus, after a preset time period following marking, i.e., after sufficient arterial blood has flowed into the region to be imaged, the computer device can image the region according to preset magnetic field parameters to obtain the perfusion imaging result. Here, the region to be imaged refers to the imaging area during the perfusion imaging process. Optionally, the preset magnetic field parameters can be the current magnetic field parameters of the region to be imaged during the imaging process, or the preset magnetic field parameters can be the pre-determined shimming parameters corresponding to the region to be imaged. Of course, this embodiment does not limit the preset magnetic field parameters or the preset time period.

[0061] In the above perfusion imaging method, a structural image and magnetic field distribution map corresponding to the region to be labeled on a vascular image are acquired; the region to be labeled includes at least two vascular structures; correction parameters are determined based on the structural image and magnetic field distribution map; the correction parameters are used to correct the magnetic field of the region to be labeled; perfusion imaging is performed on the vascular image based on the correction parameters to obtain the perfusion imaging result. Since the embodiments of this application can accurately determine the correction parameters based on the structural image and magnetic field distribution map corresponding to the region to be labeled, these correction parameters can be used to correct the non-uniform magnetic field of at least two vascular structures in the region to be labeled, thereby canceling the phase accumulation generated in the region to be labeled, thus improving the labeling effect, and further improving the imaging effect and the quality of the perfusion signal.

[0062] In one embodiment, the above-mentioned structural image includes a first vascular structure and a second vascular structure. Based on this, a method for determining correction parameters is provided, namely, the method in S202 above for "determining correction parameters based on the structural image and the magnetic field distribution map," as follows: Figure 4 As shown, it includes:

[0063] S301, Identify the first blood vessel structure and the second blood vessel structure in the structural image, and determine the first position of the first blood vessel structure and the second position of the second blood vessel structure.

[0064] The aforementioned structural image includes a first vascular structure and a second vascular structure. The first vascular structure may be an artery on one side, and the second vascular structure may be an artery on the other side. The first position refers to the position of the first vascular structure in the structural image, and the second position refers to the position of the second vascular structure in the structural image.

[0065] In this embodiment, optionally, the computer device can use a preset recognition model to identify the first and second blood vessel structures in the structural image, determining the first position of the first blood vessel structure and the second position of the second blood vessel structure. The preset recognition model can include, but is not limited to, any of a neural network model, a deep learning model, etc. Alternatively, the user terminal can annotate the first and second blood vessel structures in the structural image on the computer device's interactive interface. Thus, the computer device can also respond to the annotation operation of the user terminal to determine the first position of the first blood vessel structure and the second position of the second blood vessel structure. Of course, this embodiment does not limit the specific implementation method for determining the first and second positions.

[0066] S302, based on the first position of the first vascular structure, the second position of the second vascular structure, and the magnetic field distribution map, determine the offset information of the first vascular structure and the second vascular structure relative to the standard frequency; the offset information includes gradient and off-frequency.

[0067] In this embodiment, optionally, the computer device can directly determine the offset information of the first and second vascular structures relative to a standard frequency based on the first position of the first vascular structure, the second position of the second vascular structure, and the magnetic field distribution map; alternatively, the computer device can also determine the first frequency corresponding to the first vascular structure and the second frequency corresponding to the second vascular structure based on the first position of the first vascular structure, the second position of the second vascular structure, and the magnetic field distribution map, and then determine the offset information of the first and second vascular structures relative to the standard frequency based on the first frequency, the second frequency, the first position of the first vascular structure, and the second position of the second vascular structure. Of course, this embodiment does not limit the specific implementation method for determining the offset information.

[0068] The offset information refers to the offset information of the first and second vascular structures relative to the standard frequency corresponding to the shim. The offset information includes the gradient Gx (first-order term) and the offset frequency f (zero-order term) required to set the frequencies of the first and second vascular structures to zero.

[0069] S303, determine the correction parameters based on the offset information.

[0070] In this embodiment, the computer device can determine the zero-order, first-order, and higher-order shim current values ​​corresponding to the B0 shim based on the offset information of the first and second vascular structures relative to the standard frequency, and determine the aforementioned zero-order, first-order, and higher-order shim current values ​​as correction parameters. Furthermore, the computer device can also record the correction parameters on the computer device's interactive interface.

[0071] In this embodiment, the first and second blood vessel structures in the structural image can be identified, accurately determining the first position of the first blood vessel structure and the second position of the second blood vessel structure. Furthermore, based on the first position of the first blood vessel structure, the second position of the second blood vessel structure, and the magnetic field distribution map, the offset information of the first and second blood vessel structures relative to the standard frequency can be accurately determined. Therefore, based on the gradient and offset frequency required to set the frequencies of the first and second blood vessel structures to zero, the correction parameters used to correct the magnetic field of the region to be marked can be accurately determined.

[0072] In one embodiment, an implementation method for determining a first position and a second position is provided, namely, the method in S301 above for "identifying a first vascular structure and a second vascular structure in a structural image, and determining the first position of the first vascular structure and the second position of the second vascular structure", which includes:

[0073] Add a first bounding box corresponding to the first vascular structure and a second bounding box corresponding to the second vascular structure to the structural image.

[0074] Move the first marker box to the location of the first vascular structure, and move the second marker box to the location of the second vascular structure.

[0075] Based on the moved first and second marker frames, determine the first position of the first vascular structure and the second position of the second vascular structure.

[0076] In the embodiments of this application, such as Figure 5 As shown, Figure 5 This is a schematic diagram illustrating the determination of a first position, a second position, and offset information in an exemplary embodiment, wherein... Figure 5 In this context, 'a' represents the structural image. Figure 5 In the diagram, 'b' represents the magnetic field distribution map. The user terminal can select the post-processing application corresponding to the perfusion marker self-correction on the computer device's interactive interface. The computer device can then load and display the structural image and magnetic field distribution map on the interactive interface. Subsequently, the user terminal can determine the dimensions of the first and second bounding boxes in the image based on the vascular structure dimensions of the object under test, and add the first bounding box corresponding to the first vascular structure and the second bounding box corresponding to the second vascular structure to the structural image on the interactive interface. The interactive interface can include, but is not limited to, any software interface such as an MRI (Magnetic Resonance Imaging) software interface. It should be noted that since the structural image includes both the first and second vascular structures, each structural image includes two bounding boxes corresponding to the vascular structures.

[0077] Subsequently, the user terminal can move the first identifier box to the location of the first vascular structure and the second identifier box to the location of the second vascular structure. This can be understood as the user terminal being able to place the left arterial structure within the first identifier box and the right arterial structure within the second identifier box by moving the first and second identifier boxes. It should be noted that, in conjunction with... Figure 5 As shown, the bounding boxes in the structural image and the magnetic field distribution map are linked. That is, when the user terminal moves the bounding box in the structural image, the bounding box in the magnetic field distribution map will also move accordingly. Thus, the position of the vascular structure in the magnetic field distribution map can be determined based on the position of the vascular structure in the structural image. Therefore, the computer device can determine the first position of the first vascular structure and the second position of the second vascular structure based on the position of the first bounding box after the user terminal has moved and the position of the second bounding box after the user terminal has moved. For example, Figure 5 The 'c' in the equation includes the positions of the first and second marker boxes after they have been moved.

[0078] In this embodiment, a first identifier box corresponding to the first blood vessel structure and a second identifier box corresponding to the second blood vessel structure can be added to the structural image. The first identifier box can be moved to the location of the first blood vessel structure, and the second identifier box can be moved to the location of the second blood vessel structure. In this way, the first position of the first blood vessel structure and the second position of the second blood vessel structure can be accurately determined based on the positions of the first identifier box and the second identifier box after the user terminal has moved.

[0079] In one embodiment, a method for determining offset information is provided, namely, the method in S302 described above for "determining the offset information of the first and second vascular structures relative to a standard frequency based on the first position of the first vascular structure, the second position of the second vascular structure, and the magnetic field distribution map," such as... Figure 6 As shown, it includes:

[0080] S401, based on the first position of the first vascular structure and the second position of the second vascular structure, determine the vascular spacing and the vascular center deviation distance between the first vascular structure and the second vascular structure.

[0081] In this embodiment of the application, combined with Figure 5 As shown, the computer device can perform threshold segmentation on the first and second blood vessel structures in the structural image based on the first position of the first blood vessel structure and the second position of the second blood vessel structure, thereby generating a mask image corresponding to the structural image. Figure 5In this context, the computer device can determine the geometric center of the first and second vascular structures based on the mask image corresponding to the structural image. Furthermore, it can determine the vascular spacing Δx between the first and second vascular structures, and the deviation distance Δx0 between the centers of the first and second vascular structures from the isocenter of the perfusion imaging device. Here, the vascular spacing refers to the horizontal distance between the first and second vascular structures, and the deviation distance refers to the distance between the centers of the first and second vascular structures and the isocenter of the perfusion imaging device.

[0082] S402, based on the first mask image corresponding to the first blood vessel structure, the second mask image corresponding to the second blood vessel structure, and the magnetic field distribution map, determine the first frequency corresponding to the first blood vessel structure and the second frequency corresponding to the second blood vessel structure.

[0083] In this embodiment of the application, combined with Figure 5 As shown, the computer device can perform threshold segmentation on the first blood vessel structure in the structural image to generate a first mask image corresponding to the first blood vessel structure, i.e. Figure 5 The 'd' in the image, and the threshold segmentation of the second blood vessel structure in the structural image, can generate a second mask image corresponding to the second blood vessel structure, i.e. Figure 5 In the image 'e', ​​the first mask image, the second mask image, and the structure image have the same dimensions. Therefore, the computer device can apply the first mask image corresponding to the first blood vessel structure and the second mask image corresponding to the second blood vessel structure to the magnetic field distribution map to determine the first frequency corresponding to the first blood vessel structure and the second frequency corresponding to the second blood vessel structure.

[0084] In one embodiment, S402 includes:

[0085] The first mask image and the magnetic field distribution map are multiplied to generate the first magnetic field distribution map corresponding to the first blood vessel structure. The first magnetic field distribution map is then subjected to phase analysis to obtain the first frequency.

[0086] The second mask image and the magnetic field distribution map are multiplied to generate the second magnetic field distribution map corresponding to the second blood vessel structure. Phase analysis is then performed on the second magnetic field distribution map to obtain the second frequency.

[0087] In this embodiment of the application, combined with Figure 5As shown, the computer device can perform multiplication on the first mask image and the magnetic field distribution map to generate a first magnetic field distribution map corresponding to the first blood vessel structure. The first magnetic field distribution map includes the arterial blood vessel signal corresponding to the first blood vessel structure. Therefore, the computer device can calculate the average phase information in the first magnetic field distribution map and perform phase analysis and processing on the average phase information to calculate the first frequency f1. Similarly, the computer device can perform multiplication on the second mask image and the magnetic field distribution map to generate a second magnetic field distribution map corresponding to the second blood vessel structure. The second magnetic field distribution map includes the arterial blood vessel signal corresponding to the second blood vessel structure. Therefore, the computer device can calculate the average phase information in the second magnetic field distribution map and perform phase analysis and processing on the average phase information to calculate the second frequency f2. Of course, the embodiments of this application do not limit the order in which the first and second frequencies are determined.

[0088] S403, determine the offset information based on the intervascular spacing, the offset distance of the vascular center, the first frequency and the second frequency.

[0089] In this embodiment of the application, combined with Figure 5 As shown, the computer device can determine the gradient Gx based on the intervascular spacing Δx, the first frequency f1, and the second frequency f2. For example, the formula for determining the gradient Gx is shown in equation (1) below.

[0090]

[0091] The computer device can also determine the offset frequency f based on the intervascular spacing Δx, the deviation distance from the vascular center Δx0, the first frequency f1, and the second frequency f2. For example, the formula for determining the offset frequency f is shown in equation (2) below.

[0092]

[0093] Of course, the embodiments of this application do not limit the order in which the gradient Gx and the offset frequency f are determined.

[0094] In this embodiment, the distance between the first and second blood vessels can be determined based on the first position of the first blood vessel structure and the second position of the second blood vessel structure. Furthermore, the first frequency corresponding to the first blood vessel structure and the second frequency corresponding to the second blood vessel structure can be determined based on the first mask image corresponding to the first blood vessel structure, the second mask image corresponding to the second blood vessel structure, and the magnetic field distribution map. Therefore, the gradient Gx and offset frequency f of the first and second blood vessel structures relative to the standard frequency can be accurately determined based on the distance between the blood vessels, the offset distance of the blood vessel center, the first frequency, and the second frequency.

[0095] In one embodiment, a method for determining offset information is provided, namely, the method in S203 above for "performing perfusion imaging on a blood vessel image according to correction parameters to obtain perfusion imaging results", including:

[0096] The magnetic field in the region to be imaged on the blood vessel image is shimmed to obtain shimming parameters.

[0097] The magnetic field of the area to be marked is corrected according to the correction parameters.

[0098] After marking the region to be marked according to the corrected magnetic field, the region to be imaged is imaged according to the shimming parameters to obtain the perfusion imaging result.

[0099] In this embodiment, the user terminal can pre-determine the imaging area during the perfusion imaging process and transmit the location information of the imaging area to the computer device. The computer device can then perform system calibration on the imaging area in the vascular image and perform magnetic field homogenization processing on the magnetic field (such as the B0 field) in the imaging area to obtain homogenization parameters. System calibration may include, but is not limited to, calibrating the emission voltage and center frequency of the magnetic resonance system.

[0100] After the user terminal starts the perfusion sequence scanning process and enables the perfusion labeling self-correction option on the interactive interface, the computer device can correct the non-uniform magnetic field of the area to be labeled using correction parameters during the labeling period, thereby labeling the area to be labeled according to the corrected magnetic field. After the labeling is completed for a preset time period, that is, after the labeled arterial blood has fully flowed into the area to be imaged, the computer device can image the area to be imaged according to the shimming parameters to obtain the perfusion imaging result. It should be noted that the embodiments of this application can automatically execute the above process for each scanning process in the repeated scanning process, the process of averaging multiple scans, the process of scanning the control image, or the process of scanning the labeled image, so as to ensure that correction is achieved for each perfusion imaging process.

[0101] In this embodiment, the magnetic field in the region to be imaged on the vascular image can be shimmed to obtain shimming parameters. Furthermore, during the labeling period, the magnetic field of the region to be labeled can be corrected according to the correction parameters. Therefore, after labeling the region to be labeled based on the corrected magnetic field, imaging can be performed on the region to be imaged according to the shimming parameters to obtain perfusion imaging results. Thus, turning off the correction parameters after labeling improves the labeling efficiency of the perfusion sequence without affecting the imaging process, thereby achieving a high-quality perfusion measurement workflow.

[0102] In an optional embodiment, such as Figure 7 As shown, a perfusion imaging method is provided, applied to a computer device, comprising:

[0103] S501, homogenize the magnetic field in the region to be imaged on the blood vessel image to obtain homogenization parameters;

[0104] S502, acquire the structural image and magnetic field distribution map corresponding to the region to be labeled on the blood vessel image;

[0105] S503, add a first identification box corresponding to the first blood vessel structure and a second identification box corresponding to the second blood vessel structure to the structural image;

[0106] S504, move the first marker box to the location of the first blood vessel structure, and move the second marker box to the location of the second blood vessel structure;

[0107] S505, based on the moved first identifier box and the moved second identifier box, determine the first position of the first blood vessel structure and the second position of the second blood vessel structure;

[0108] S506, Based on the first position of the first vascular structure and the second position of the second vascular structure, determine the vascular spacing and the vascular center deviation distance between the first vascular structure and the second vascular structure;

[0109] S507, perform multiplication processing on the first mask image corresponding to the first blood vessel structure and the magnetic field distribution map to generate the first magnetic field distribution map corresponding to the first blood vessel structure, and perform phase analysis on the first magnetic field distribution map to obtain the first frequency;

[0110] S508, perform multiplication processing on the second mask image corresponding to the second blood vessel structure and the magnetic field distribution map to generate the second magnetic field distribution map corresponding to the second blood vessel structure, and perform phase analysis on the second magnetic field distribution map to obtain the second frequency;

[0111] S509, determine the offset information based on the intervascular spacing, the offset distance from the vascular center, the first frequency, and the second frequency; the offset information includes the gradient and the off-frequency.

[0112] S510, determine the correction parameters based on the offset information; the correction parameters are used to correct the magnetic field of the area to be marked;

[0113] S511, Correct the magnetic field of the area to be marked according to the correction parameters;

[0114] S512, after marking the area to be marked according to the corrected magnetic field, the area to be imaged is imaged according to the shimming parameters to obtain the perfusion imaging result.

[0115] In the above perfusion imaging method, a structural image and magnetic field distribution map corresponding to the region to be labeled on a vascular image are acquired; the region to be labeled includes at least two vascular structures; correction parameters are determined based on the structural image and magnetic field distribution map; the correction parameters are used to correct the magnetic field of the region to be labeled; perfusion imaging is performed on the vascular image based on the correction parameters to obtain the perfusion imaging result. Since the embodiments of this application can accurately determine the correction parameters based on the structural image and magnetic field distribution map corresponding to the region to be labeled, these correction parameters can be used to correct the non-uniform magnetic field of at least two vascular structures in the region to be labeled, thereby canceling the phase accumulation generated in the region to be labeled, thus improving the labeling effect, and further improving the imaging effect and the quality of the perfusion signal.

[0116] Based on the above embodiments, this application provides a self-correction method for addressing poor labeling results caused by partial resonant phase accumulation in perfusion applications. Taking a brain perfusion scenario as an example, after completing conventional shimming and system calibration of the area to be imaged, this application can acquire structural images and magnetic field distribution maps of the area to be labeled, and automatically segment at least two ROI (Region of Interest) regions of vascular structures from the structural images. Then, based on the ROI regions and magnetic field distribution maps of the left and right vascular structures, the frequency difference between the left and right carotid arteries is automatically calculated. Based on this frequency difference, the shimming gradient distribution and offset frequency required to correct the frequency difference can be further calculated. Thus, during the labeling period, zero-order, first-order, and higher-order shimming current values ​​corresponding to the shimming gradient distribution and offset frequency can be used to set the frequencies of the left and right vascular structures in the area to be labeled to zero, thereby eliminating partial resonant phase accumulation and improving the labeling effect. Furthermore, the correction parameters can be turned off after labeling, which can improve the labeling efficiency of the perfusion sequence without affecting the imaging process. In summary, a high-quality perfusion measurement process can be achieved.

[0117] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0118] Based on the same inventive concept, this application also provides a perfusion imaging apparatus for implementing the perfusion imaging method described above. The solution provided by this apparatus is similar to the implementation described in the above method; therefore, the specific limitations in one or more perfusion imaging apparatus embodiments provided below can be found in the limitations of the perfusion imaging method described above, and will not be repeated here.

[0119] In one exemplary embodiment, such as Figure 8 As shown, a perfusion imaging device is provided, comprising: an acquisition module 31, a determination module 32, and an imaging module 33, wherein:

[0120] The acquisition module 31 is used to acquire the structural image and magnetic field distribution map corresponding to the region to be labeled on the blood vessel image; the region to be labeled includes at least two blood vessel structures;

[0121] The determination module 32 is used to determine the correction parameters based on the structural image and the magnetic field distribution map; the correction parameters are used to correct the magnetic field of the area to be marked.

[0122] The imaging module 33 is used to perform perfusion imaging on the blood vessel image according to the correction parameters to obtain the perfusion imaging result.

[0123] In one embodiment, the determining module 32 includes:

[0124] The location determination unit is used to identify the first blood vessel structure and the second blood vessel structure in the structural image, and to determine the first location of the first blood vessel structure and the second location of the second blood vessel structure.

[0125] The offset information determination unit is used to determine the offset information of the first vascular structure and the second vascular structure relative to a standard frequency based on the first position of the first vascular structure, the second position of the second vascular structure, and the magnetic field distribution map; the offset information includes gradient and off-frequency.

[0126] The correction parameter determination unit is used to determine the correction parameters based on the offset information.

[0127] In one embodiment, the offset information determination unit includes:

[0128] The distance determination subunit is used to determine the intervascular spacing and the offset distance between the first vascular structure and the second vascular structure based on the first position of the first vascular structure and the second position of the second vascular structure.

[0129] The frequency determination subunit is used to determine the first frequency corresponding to the first blood vessel structure and the second frequency corresponding to the second blood vessel structure based on the first mask image corresponding to the first blood vessel structure, the second mask image corresponding to the second blood vessel structure, and the magnetic field distribution map.

[0130] The offset information determination subunit is used to determine offset information based on the intervascular spacing, the offset distance of the vascular center, the first frequency, and the second frequency.

[0131] In one embodiment, the frequency determination subunit is specifically used for:

[0132] The first mask image and the magnetic field distribution map are multiplied to generate the first magnetic field distribution map corresponding to the first blood vessel structure. The first magnetic field distribution map is then subjected to phase analysis to obtain the first frequency.

[0133] The second mask image and the magnetic field distribution map are multiplied to generate the second magnetic field distribution map corresponding to the second blood vessel structure. Phase analysis is then performed on the second magnetic field distribution map to obtain the second frequency.

[0134] In one embodiment, the position determination unit includes:

[0135] The identifier box adds a sub-unit, which is used to add a first identifier box corresponding to the first blood vessel structure and a second identifier box corresponding to the second blood vessel structure to the structural image;

[0136] The moving subunit is used to move the first identifier box to the location of the first blood vessel structure and to move the second identifier box to the location of the second blood vessel structure.

[0137] The position determination subunit is used to determine the first position of the first blood vessel structure and the second position of the second blood vessel structure based on the moved first and second identifier boxes.

[0138] In one embodiment, the imaging module 33 includes:

[0139] The shimming unit is used to shim the magnetic field in the imaging region of the blood vessel image to obtain shimming parameters.

[0140] The correction unit is used to correct the magnetic field of the area to be marked according to the correction parameters.

[0141] The imaging unit is used to mark the region to be marked according to the corrected magnetic field, and then to image the region to be imaged according to the shimming parameters to obtain the perfusion imaging result.

[0142] Each module in the aforementioned perfusion imaging device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0143] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 2 As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements an injection imaging method. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0144] Those skilled in the art will understand that Figure 2 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0145] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0146] Obtain the structural image and magnetic field distribution map corresponding to the region to be labeled on the vascular image; the region to be labeled includes at least two vascular structures;

[0147] Based on the structural image and magnetic field distribution map, the correction parameters are determined; these parameters are used to correct the magnetic field of the area to be marked.

[0148] Perfusion imaging is performed on the vascular images based on the correction parameters to obtain perfusion imaging results.

[0149] In one embodiment, the structural image includes a first vascular structure and a second vascular structure. Based on the structural image and the magnetic field distribution map, correction parameters are determined. When the processor executes the computer program, it further performs the following steps:

[0150] The first and second blood vessel structures in the structural image are identified to determine the first position of the first blood vessel structure and the second position of the second blood vessel structure.

[0151] Based on the first position of the first vascular structure, the second position of the second vascular structure, and the magnetic field distribution map, the offset information of the first and second vascular structures relative to the standard frequency is determined; the offset information includes gradient and off-frequency.

[0152] The correction parameters are determined based on the offset information.

[0153] In one embodiment, based on the first position of the first vascular structure, the second position of the second vascular structure, and the magnetic field distribution map, the offset information of the first and second vascular structures relative to a standard frequency is determined. When the processor executes the computer program, it further performs the following steps:

[0154] Based on the first position of the first vascular structure and the second position of the second vascular structure, determine the vascular spacing and the vascular center deviation distance between the first vascular structure and the second vascular structure;

[0155] Based on the first mask image corresponding to the first blood vessel structure, the second mask image corresponding to the second blood vessel structure, and the magnetic field distribution map, the first frequency corresponding to the first blood vessel structure and the second frequency corresponding to the second blood vessel structure are determined.

[0156] The offset information is determined based on the intervascular spacing, the deviation distance from the vascular center, the first frequency, and the second frequency.

[0157] In one embodiment, based on a first mask image corresponding to a first blood vessel structure, a second mask image corresponding to a second blood vessel structure, and a magnetic field distribution map, a first frequency corresponding to a first blood vessel structure and a second frequency corresponding to a second blood vessel structure are determined. When the processor executes the computer program, it further performs the following steps:

[0158] The first mask image and the magnetic field distribution map are multiplied to generate the first magnetic field distribution map corresponding to the first blood vessel structure. The first magnetic field distribution map is then subjected to phase analysis to obtain the first frequency.

[0159] The second mask image and the magnetic field distribution map are multiplied to generate the second magnetic field distribution map corresponding to the second blood vessel structure. Phase analysis is then performed on the second magnetic field distribution map to obtain the second frequency.

[0160] In one embodiment, a first blood vessel structure and a second blood vessel structure in a structural image are identified, a first position of the first blood vessel structure and a second position of the second blood vessel structure are determined, and the processor, when executing the computer program, further implements the following steps:

[0161] Add a first bounding box corresponding to the first vascular structure and a second bounding box corresponding to the second vascular structure to the structural image;

[0162] Move the first marker box to the location of the first blood vessel structure, and move the second marker box to the location of the second blood vessel structure;

[0163] Based on the moved first and second marker frames, determine the first position of the first vascular structure and the second position of the second vascular structure.

[0164] In one embodiment, perfusion imaging is performed on the vascular image according to the correction parameters to obtain the perfusion imaging result. When the processor executes the computer program, it also performs the following steps:

[0165] The magnetic field in the region to be imaged on the blood vessel image is shimmed to obtain shimming parameters.

[0166] The magnetic field of the area to be marked is corrected according to the correction parameters;

[0167] After marking the region to be marked according to the corrected magnetic field, the region to be imaged is imaged according to the shimming parameters to obtain the perfusion imaging result.

[0168] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0169] Obtain the structural image and magnetic field distribution map corresponding to the region to be labeled on the vascular image; the region to be labeled includes at least two vascular structures;

[0170] Based on the structural image and magnetic field distribution map, the correction parameters are determined; these parameters are used to correct the magnetic field of the area to be marked.

[0171] Perfusion imaging is performed on the vascular images based on the correction parameters to obtain perfusion imaging results.

[0172] In one embodiment, the structural image includes a first vascular structure and a second vascular structure. Based on the structural image and the magnetic field distribution map, correction parameters are determined. When the computer program is executed by the processor, the following steps are also performed:

[0173] The first and second blood vessel structures in the structural image are identified to determine the first position of the first blood vessel structure and the second position of the second blood vessel structure.

[0174] Based on the first position of the first vascular structure, the second position of the second vascular structure, and the magnetic field distribution map, the offset information of the first and second vascular structures relative to the standard frequency is determined; the offset information includes gradient and off-frequency.

[0175] The correction parameters are determined based on the offset information.

[0176] In one embodiment, based on the first position of the first vascular structure, the second position of the second vascular structure, and the magnetic field distribution map, the offset information of the first and second vascular structures relative to a standard frequency is determined. When the computer program is executed by the processor, it further performs the following steps:

[0177] Based on the first position of the first vascular structure and the second position of the second vascular structure, determine the vascular spacing and the vascular center deviation distance between the first vascular structure and the second vascular structure;

[0178] Based on the first mask image corresponding to the first blood vessel structure, the second mask image corresponding to the second blood vessel structure, and the magnetic field distribution map, the first frequency corresponding to the first blood vessel structure and the second frequency corresponding to the second blood vessel structure are determined.

[0179] The offset information is determined based on the intervascular spacing, the deviation distance from the vascular center, the first frequency, and the second frequency.

[0180] In one embodiment, based on a first mask image corresponding to a first blood vessel structure, a second mask image corresponding to a second blood vessel structure, and a magnetic field distribution map, a first frequency corresponding to a first blood vessel structure and a second frequency corresponding to a second blood vessel structure are determined. When the computer program is executed by the processor, the following steps are also performed:

[0181] The first mask image and the magnetic field distribution map are multiplied to generate the first magnetic field distribution map corresponding to the first blood vessel structure. The first magnetic field distribution map is then subjected to phase analysis to obtain the first frequency.

[0182] The second mask image and the magnetic field distribution map are multiplied to generate the second magnetic field distribution map corresponding to the second blood vessel structure. Phase analysis is then performed on the second magnetic field distribution map to obtain the second frequency.

[0183] In one embodiment, a first blood vessel structure and a second blood vessel structure in a structural image are identified, a first position of the first blood vessel structure and a second position of the second blood vessel structure are determined, and the computer program, when executed by a processor, further implements the following steps:

[0184] Add a first bounding box corresponding to the first vascular structure and a second bounding box corresponding to the second vascular structure to the structural image;

[0185] Move the first marker box to the location of the first blood vessel structure, and move the second marker box to the location of the second blood vessel structure;

[0186] Based on the moved first and second marker frames, determine the first position of the first vascular structure and the second position of the second vascular structure.

[0187] In one embodiment, perfusion imaging is performed on the vascular image according to the correction parameters to obtain the perfusion imaging result. When the computer program is executed by the processor, it also performs the following steps:

[0188] The magnetic field in the region to be imaged on the blood vessel image is shimmed to obtain shimming parameters.

[0189] The magnetic field of the area to be marked is corrected according to the correction parameters;

[0190] After marking the region to be marked according to the corrected magnetic field, the region to be imaged is imaged according to the shimming parameters to obtain the perfusion imaging result.

[0191] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0192] Obtain the structural image and magnetic field distribution map corresponding to the region to be labeled on the vascular image; the region to be labeled includes at least two vascular structures;

[0193] Based on the structural image and magnetic field distribution map, the correction parameters are determined; these parameters are used to correct the magnetic field of the area to be marked.

[0194] Perfusion imaging is performed on the vascular images based on the correction parameters to obtain perfusion imaging results.

[0195] In one embodiment, the structural image includes a first vascular structure and a second vascular structure. Based on the structural image and the magnetic field distribution map, correction parameters are determined. When the computer program is executed by the processor, the following steps are also performed:

[0196] The first and second blood vessel structures in the structural image are identified to determine the first position of the first blood vessel structure and the second position of the second blood vessel structure.

[0197] Based on the first position of the first vascular structure, the second position of the second vascular structure, and the magnetic field distribution map, the offset information of the first and second vascular structures relative to the standard frequency is determined; the offset information includes gradient and off-frequency.

[0198] The correction parameters are determined based on the offset information.

[0199] In one embodiment, based on the first position of the first vascular structure, the second position of the second vascular structure, and the magnetic field distribution map, the offset information of the first and second vascular structures relative to a standard frequency is determined. When the computer program is executed by the processor, it further performs the following steps:

[0200] Based on the first position of the first vascular structure and the second position of the second vascular structure, determine the vascular spacing and the vascular center deviation distance between the first vascular structure and the second vascular structure;

[0201] Based on the first mask image corresponding to the first blood vessel structure, the second mask image corresponding to the second blood vessel structure, and the magnetic field distribution map, the first frequency corresponding to the first blood vessel structure and the second frequency corresponding to the second blood vessel structure are determined.

[0202] The offset information is determined based on the intervascular spacing, the deviation distance from the vascular center, the first frequency, and the second frequency.

[0203] In one embodiment, based on a first mask image corresponding to a first blood vessel structure, a second mask image corresponding to a second blood vessel structure, and a magnetic field distribution map, a first frequency corresponding to a first blood vessel structure and a second frequency corresponding to a second blood vessel structure are determined. When the computer program is executed by the processor, the following steps are also performed:

[0204] The first mask image and the magnetic field distribution map are multiplied to generate the first magnetic field distribution map corresponding to the first blood vessel structure. The first magnetic field distribution map is then subjected to phase analysis to obtain the first frequency.

[0205] The second mask image and the magnetic field distribution map are multiplied to generate the second magnetic field distribution map corresponding to the second blood vessel structure. Phase analysis is then performed on the second magnetic field distribution map to obtain the second frequency.

[0206] In one embodiment, a first blood vessel structure and a second blood vessel structure in a structural image are identified, a first position of the first blood vessel structure and a second position of the second blood vessel structure are determined, and the computer program, when executed by a processor, further implements the following steps:

[0207] Add a first bounding box corresponding to the first vascular structure and a second bounding box corresponding to the second vascular structure to the structural image;

[0208] Move the first marker box to the location of the first blood vessel structure, and move the second marker box to the location of the second blood vessel structure;

[0209] Based on the moved first and second marker frames, determine the first position of the first vascular structure and the second position of the second vascular structure.

[0210] In one embodiment, perfusion imaging is performed on the vascular image according to the correction parameters to obtain the perfusion imaging result. When the computer program is executed by the processor, it also performs the following steps:

[0211] The magnetic field in the region to be imaged on the blood vessel image is shimmed to obtain shimming parameters.

[0212] The magnetic field of the area to be marked is corrected according to the correction parameters;

[0213] After marking the region to be marked according to the corrected magnetic field, the region to be imaged is imaged according to the shimming parameters to obtain the perfusion imaging result.

[0214] It should be noted that the user information (including but not limited to user terminal information, user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0215] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0216] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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 application.

[0217] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A perfusion imaging method, characterized in that, The method includes: Acquire the structural image and magnetic field distribution map corresponding to the region to be labeled on the vascular image; the region to be labeled includes at least two vascular structures; Based on the structural image and the magnetic field distribution map, correction parameters are determined; these correction parameters are used to correct the magnetic field of the region to be labeled. Perfusion imaging is performed on the vascular image according to the correction parameters to obtain perfusion imaging results.

2. The method according to claim 1, characterized in that, The structural image includes a first vascular structure and a second vascular structure. Determining the correction parameters based on the structural image and the magnetic field distribution map includes: The first and second blood vessel structures in the structural image are identified to determine the first position of the first blood vessel structure and the second position of the second blood vessel structure. Based on the first position of the first vascular structure, the second position of the second vascular structure, and the magnetic field distribution map, the offset information of the first vascular structure and the second vascular structure relative to the standard frequency is determined; the offset information includes gradient and off-frequency. The correction parameters are determined based on the offset information.

3. The method according to claim 2, characterized in that, The step of determining the offset information of the first and second vascular structures relative to a standard frequency based on the first position of the first vascular structure, the second position of the second vascular structure, and the magnetic field distribution map includes: Based on the first position of the first vascular structure and the second position of the second vascular structure, determine the vascular spacing and the vascular center deviation distance between the first vascular structure and the second vascular structure; Based on the first mask image corresponding to the first blood vessel structure, the second mask image corresponding to the second blood vessel structure, and the magnetic field distribution map, the first frequency corresponding to the first blood vessel structure and the second frequency corresponding to the second blood vessel structure are determined. The offset information is determined based on the blood vessel spacing, the blood vessel center deviation distance, the first frequency, and the second frequency.

4. The method according to claim 3, characterized in that, The step of determining the first frequency corresponding to the first blood vessel structure and the second frequency corresponding to the second blood vessel structure based on the first mask image corresponding to the first blood vessel structure, the second mask image corresponding to the second blood vessel structure, and the magnetic field distribution map includes: The first mask image and the magnetic field distribution map are multiplied to generate the first magnetic field distribution map corresponding to the first blood vessel structure, and the first magnetic field distribution map is phase analyzed to obtain the first frequency. The second mask image and the magnetic field distribution map are multiplied to generate a second magnetic field distribution map corresponding to the second blood vessel structure. Phase analysis is then performed on the second magnetic field distribution map to obtain the second frequency.

5. The method according to any one of claims 2-4, characterized in that, The step of identifying the first and second vascular structures in the structural image and determining the first position of the first vascular structure and the second position of the second vascular structure includes: Add a first identification box corresponding to the first blood vessel structure and a second identification box corresponding to the second blood vessel structure to the structural image; Move the first marker frame to the location of the first blood vessel structure, and move the second marker frame to the location of the second blood vessel structure; Based on the moved first and second marker frames, the first position of the first vascular structure and the second position of the second vascular structure are determined.

6. The method according to any one of claims 1-4, characterized in that, The step of performing perfusion imaging on the vascular image according to the correction parameters to obtain perfusion imaging results includes: The magnetic field in the region to be imaged on the blood vessel image is homogenized to obtain homogenization parameters; The magnetic field of the region to be marked is corrected according to the correction parameters. After marking the region to be marked according to the corrected magnetic field, the region to be imaged is imaged according to the shimming parameters to obtain the perfusion imaging result.

7. A perfusion imaging device, characterized in that, The device includes: The acquisition module is used to acquire the structural image and magnetic field distribution map corresponding to the region to be labeled on the vascular image; the region to be labeled includes at least two vascular structures; The determination module is used to determine correction parameters based on the structural image and the magnetic field distribution map; the correction parameters are used to correct the magnetic field of the region to be marked. An imaging module is used to perform perfusion imaging on the blood vessel image according to the correction parameters to obtain perfusion imaging results.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

Images