CN112649773B - Magnetic resonance scanning method, device, equipment and storage medium - Google Patents
Magnetic resonance scanning method, device, equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a magnetic resonance scanning method, a magnetic resonance scanning device, magnetic resonance scanning equipment and a storage medium. The method comprises the following steps: acquiring artifact identification data in the magnetic resonance scanning process; wherein the artifact identification data comprises a set of magnetic resonance images and/or motion data respectively corresponding to at least one magnetic resonance image in the set of magnetic resonance images; determining an artifact image in the magnetic resonance image set based on the artifact identification data and a trained target artifact identification model; determining rescanning parameters corresponding to the artifact image based on a magnetic resonance scanning mode, and performing rescanning operation on the measured object based on the rescanning parameters to obtain a corrected image; and updating the magnetic resonance image set based on the correction image to obtain a target magnetic resonance image set. The embodiment of the invention solves the problem of poor timeliness of artifact image compensation operation and improves the quality of magnetic resonance scanning.
Description
Technical Field
Embodiments of the present invention relate to the field of magnetic resonance imaging technologies, and in particular, to a magnetic resonance scanning method, apparatus, device, and storage medium.
Background
Magnetic resonance imaging is a tomographic imaging technique that uses the magnetic resonance phenomenon to acquire electromagnetic signals from a subject and reconstruct tissue information based on the electromagnetic signals. Because the time of the magnetic resonance scanning is long, the movement behavior of the measured object can be inevitably generated in the process of the magnetic resonance scanning, and the movement behavior can cause artifacts in the obtained magnetic resonance image, thereby influencing the subsequent diagnosis result.
According to a traditional motion artifact identification scheme, manual screening is needed depending on a scanning technician, the scanning technician judges whether motion artifacts exist in a magnetic resonance image according to personal experience, whether the motion artifacts affect clinical diagnosis or not, and judges whether rescanning is possible to acquire images with higher quality or not according to the condition of a patient. The traditional artifact identification scheme needs a scanning technician to have rich image judgment capability and clinical experience, increases the workload of the scanning technician and has large identification result errors. And the process of identifying the artifact image has certain time delay, so that the operation of the subsequent supplementary scanning can exceed the requirement of the magnetic resonance scanning on timeliness.
Disclosure of Invention
The embodiment of the invention provides a magnetic resonance scanning method, a device, equipment and a storage medium, which are used for improving the timeliness of the supplementary scanning operation in the magnetic resonance scanning process and the image quality obtained by magnetic resonance scanning.
In a first aspect, an embodiment of the present invention provides a magnetic resonance scanning method, including:
acquiring artifact identification data in the magnetic resonance scanning process; wherein the artifact identification data comprises a set of magnetic resonance images and/or motion data respectively corresponding to at least one magnetic resonance image in the set of magnetic resonance images;
determining an artifact image in the magnetic resonance image set based on the artifact identification data and a trained target artifact identification model;
determining rescanning parameters corresponding to the artifact image based on a magnetic resonance scanning mode, and performing rescanning operation on the measured object based on the rescanning parameters to obtain a corrected image;
and updating the magnetic resonance image set based on the correction image to obtain a target magnetic resonance image set.
In a second aspect, an embodiment of the present invention further provides a magnetic resonance scanning apparatus, including:
the artifact identification data acquisition module is used for acquiring artifact identification data in the magnetic resonance scanning process; wherein the artifact identification data comprises a set of magnetic resonance images and/or motion data respectively corresponding to at least one magnetic resonance image in the set of magnetic resonance images;
an artifact image recognition module for determining an artifact image in the set of magnetic resonance images based on the artifact recognition data and a trained target artifact recognition model;
the correction image determining module is used for determining rescanning parameters corresponding to the artifact image based on a magnetic resonance scanning mode, and performing rescanning operation on the tested object based on the rescanning parameters to obtain a correction image;
and the target magnetic resonance image set determining module is used for updating the magnetic resonance image set based on the correction image to obtain a target magnetic resonance image set.
In a third aspect, an embodiment of the present invention further provides an electronic device, including:
one or more processors;
a memory for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the magnetic resonance scanning method of any of the above-referenced figures.
In a fourth aspect, embodiments of the present invention also provide a storage medium containing computer executable instructions which, when executed by a computer processor, are used to perform a magnetic resonance scanning method as described in any of the above.
According to the embodiment of the invention, the artifact image in the magnetic resonance image set obtained by magnetic resonance scanning is identified, the rescanning parameter corresponding to the artifact image is determined based on the magnetic resonance scanning mode, the magnetic resonance image set is updated based on the rescanning correction image, the problem of poor timeliness of artifact image compensation operation is solved, and the image quality obtained by magnetic resonance scanning is improved.
Drawings
Fig. 1 is a flowchart of a magnetic resonance scanning method according to a first embodiment of the present invention;
fig. 2 is a flowchart of a magnetic resonance scanning method according to a second embodiment of the present invention;
fig. 3 is a flowchart of a magnetic resonance scanning method corresponding to a multi-breath-hold scanning mode according to a second embodiment of the present invention;
fig. 4 is a flowchart of a specific example of a magnetic resonance scanning method according to the second embodiment of the present invention;
fig. 5 is a schematic diagram of a magnetic resonance scanning apparatus according to a third embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting thereof. It should be further noted that, for convenience of description, only some, but not all of the structures related to the present invention are shown in the drawings.
Example 1
Fig. 1 is a flowchart of a magnetic resonance scanning method according to an embodiment of the present invention, where the method may be performed by a magnetic resonance scanning apparatus, the apparatus may be implemented in software and/or hardware, and the apparatus may be configured in a magnetic resonance device or a terminal device. The method specifically comprises the following steps:
s110, artifact identification data in the magnetic resonance scanning process are acquired.
Wherein, the artifact identification data is specifically used for determining whether the artifact identification data exists in the magnetic resonance scanning process. In this embodiment, the artifact identification data comprises a set of magnetic resonance images and/or motion data respectively corresponding to at least one magnetic resonance image of the set of magnetic resonance images. Wherein, specifically, the magnetic resonance image set comprises at least one magnetic resonance image.
Wherein the motion data includes, but is not limited to, at least one of respiration data, heartbeat data, and motion data of the target site, by way of example. Specifically, the breathing data includes data such as breathing signals, breathing frequency and breathing amplitude, the heartbeat data includes data such as heartbeat signals, heartbeat frequency and heartbeat amplitude, the target portion may be a hand, a head, a chest, a foot, a leg, and the like, and the motion data of the target portion may be pose motion data, where the pose motion data includes pose angle data and/or position data. The choice of motion data is not particularly limited herein.
S120, determining an artifact image in the magnetic resonance image set based on the artifact identification data and the trained target artifact identification model.
Exemplary target artifact recognition models include, but are not limited to, a K-nearest neighbor algorithm-based network model, a support vector machine, a bayesian network model, a decision tree, a convolutional neural network model, a cyclic neural network model, a deep learning network model, or the like, and the specific model type of the target artifact recognition model is not limited herein.
On the basis of the foregoing embodiment, optionally, the target artifact identification model includes a first target artifact identification model and/or a second target artifact identification model, and accordingly, determining an artifact image in the magnetic resonance image set based on the artifact identification data and the trained target artifact identification model includes: respectively inputting each magnetic resonance image into a first target artifact identification model to obtain an output first identification result, and/or respectively inputting each motion data into a second target artifact identification model to obtain an output second identification result; an artifact image in the set of magnetic resonance images is determined based on the first recognition result and/or the second recognition result.
The first target artifact identification model and the second target artifact identification model include, but are not limited to, a network model based on a K-nearest neighbor algorithm, a support vector machine, a bayesian network model, a decision tree, a convolutional neural network model, a cyclic neural network model, a deep learning network model, or the like, and specific model types of the first target artifact identification model and the second target artifact identification model are not limited herein. Specifically, the types of the first target artifact identification model and the second target artifact identification model may be the same or different. In an exemplary embodiment, the first recognition result is whether the magnetic resonance image is an artifact image, and the second recognition result is whether the magnetic resonance image corresponding to the motion data is an artifact image.
In one embodiment, optionally, the first recognition result includes a first artifact level corresponding to each magnetic resonance image, and the second recognition result includes a second artifact level corresponding to each motion data. The number of divisions of the artifact level is not limited herein, and the artifact level includes, for example, 3 levels, specifically, a no artifact level, a slight artifact level, and a serious artifact level, respectively. Specifically, the second artifact level corresponding to the motion data is used for describing the fluctuation condition of the motion data. Illustratively, the no-artifact level, the slight-artifact level, and the severe-artifact level correspond to no-fluctuation, slight-fluctuation, and severe-fluctuation, respectively, of the motion data.
On the basis of the embodiment, optionally, acquiring a sample magnetic resonance image and sample motion data, inputting the sample magnetic resonance image into a first initial artifact identification model, and performing iterative training on the first initial artifact identification model according to the output first prediction identification result and the first standard identification result until a first preset requirement is met, thereby obtaining a trained first target artifact identification model; and inputting the sample motion data into a second initial artifact identification model, and performing iterative training on the second initial artifact identification model according to the output second prediction identification result and the second standard identification result until a second preset requirement is met, so as to obtain a trained second target artifact identification model.
In one embodiment, optionally, determining an artifact image in the set of magnetic resonance images based on the first recognition result and/or the second recognition result comprises: determining, for each magnetic resonance image, a target artifact level based on the first artifact level and the second artifact level; and if at least one of the target artifact level, the first artifact level and the second artifact level reaches a preset level threshold, taking the magnetic resonance image as an artifact image.
Specifically, according to the weighting coefficients corresponding to the first artifact level and the second artifact level, the first artifact level and the second artifact level are weighted and calculated to obtain the target artifact level.
In one embodiment, optionally, the preset requirement is that the consistency ratio calculated based on the standard recognition result and the predicted recognition result is less than or equal to a preset ratio threshold, or the preset requirement is that the loss function value calculated based on the output predicted recognition result and the standard recognition result converges. Specifically, if the consistency ratio is greater than a preset ratio threshold, increasing the sample size of the sample magnetic resonance image, and continuing to iteratively train the initial artifact identification model.
S130, determining rescanning parameters corresponding to the artifact image based on the magnetic resonance scanning mode, and performing rescanning operation on the tested object based on the rescanning parameters to obtain a corrected image.
The magnetic resonance scan mode includes, but is not limited to, a multi-breath-hold scan mode, a single breath-hold scan mode, a non-breath-hold scan mode, etc., and the different magnetic resonance scan modes correspond to different ways of determining the rescanning parameters. The specific steps of this section are specifically illustrated in the following examples.
Exemplary rescan parameters include, but are not limited to, magnetic resonance receive coil parameters, magnetic field homogeneity compensation parameters, and excitation times, among others.
And S140, updating the magnetic resonance image set based on the correction image to obtain a target magnetic resonance image set.
In one embodiment, optionally, the correction image is replaced by an artifact image in the set of magnetic resonance images resulting in a set of target magnetic resonance images. Wherein the exemplary set of magnetic resonance images comprises image 1, image 2 and image 3, wherein image 2 is an artifact image and the corrected image corresponding to the artifact image is image 2', and the target set of magnetic resonance images comprises image 1, image 2' and image 3.
In another embodiment, optionally, the correction image is added to the set of magnetic resonance images resulting in a set of target magnetic resonance images. Therein, the correction images may be stored in correspondence with the artifact images in the target magnetic resonance image set, for example, image 1, image 2' and image 3. The correction images may also be stored separately from the artifact images in a set of target magnetic resonance images, for example image 1, image 2, image 3 and image 2', as in the example above. The manner in which the correction image is added to the set of magnetic resonance images is not limited here.
According to the technical scheme, the artifact images in the magnetic resonance image set obtained through magnetic resonance scanning are identified, rescanning parameters corresponding to the artifact images are determined based on the magnetic resonance scanning mode, the magnetic resonance image set is updated based on the correction images obtained through rescanning, the problem that the timeliness of artifact image compensation operation is poor is solved, and the image quality obtained through magnetic resonance scanning is improved.
Example two
Fig. 2 is a flowchart of a magnetic resonance scanning method according to a second embodiment of the present invention, and the technical solution of this embodiment is further elaboration based on the foregoing embodiment. Optionally, the determining, based on the magnetic resonance scan mode, a rescanning parameter corresponding to the artifact image includes: and if the magnetic resonance scanning mode is a single breath-hold scanning mode or a non-breath-hold scanning mode, determining rescanning parameters corresponding to the artifact image according to the image position of the artifact image.
The specific implementation steps of the embodiment include:
s210, artifact identification data in the magnetic resonance scanning process are acquired.
S220, determining an artifact image in the magnetic resonance image set based on the artifact identification data and the trained target artifact identification model.
S230, if the magnetic resonance scanning mode is a single breath-hold scanning mode or a non-breath-hold scanning mode, determining rescanning parameters corresponding to the artifact image according to the image position of the artifact image.
Specifically, the single breath-hold scanning mode or the non-breath-hold scanning mode belongs to a continuous scanning mode, and the continuous scanning mode can perform one-time continuous scanning on a tested object to obtain a magnetic resonance image set. In the magnetic resonance scanning process, a plurality of magnetic resonance images on different layers are obtained through scanning, the image positions can be used for describing the positions of the scanned slices, and the scanning parameters corresponding to different slices can be different.
In one embodiment, optionally, determining a rescanning parameter corresponding to the artifact image according to an image location of the artifact image includes: determining at least one slice group based on an image position of the at least one artifact image; for each slice group, a rescan parameter corresponding to the slice group is determined based on a slice position of the slice group and a number of artifact images in the slice group.
In this embodiment, each group of slices contains artifact images that are spatially contiguous, and illustratively, a group of slices may contain only one artifact image, or at least two artifact images that are spatially contiguous.
The magnetic resonance images in the magnetic resonance image set are, for example, image 1, image 2, image 3, image 4, image 5, image 6 and image 7 in this order according to the image position. Assuming that images 3, 4 and 6 in the magnetic resonance image set are artifact images, two slice groups, slice group 1 containing images 3 and 4 and slice group 2 containing image 6, respectively, can be determined.
The slice position of the slice group may be an image position of any artifact image in the slice group, for example. The rescanning parameter is correlated with the slice position of the slice group and the number of artifact images in the slice group so that the corrected image scanned based on the rescanning parameter is consistent with parameters such as signal-to-noise ratio and contrast of the artifact image corresponding to the corrected image.
On the basis of the above embodiment, optionally, determining a rescanning parameter corresponding to the artifact image based on the magnetic resonance scan mode includes: and if the magnetic resonance scanning mode is a multi-breath-hold scanning mode, taking a single breath-hold scanning parameter corresponding to the artifact image as a rescanning parameter.
Specifically, when the magnetic resonance scanning mode is a multi-breath-hold scanning mode, the tested object needs to keep a breath-hold state in each breath-hold period, and execute magnetic resonance scanning operation based on a single breath-hold scanning parameter in the breath-hold period, and after the scanning operation is completed, a magnetic resonance image set corresponding to the breath-hold period is obtained. Specifically, the single breath-hold scanning parameters corresponding to each breath-hold period may be the same or different.
In one embodiment, optionally, acquiring artifact identification data during a magnetic resonance scan includes: and when the magnetic resonance scanning mode is a plurality of breath-hold scanning modes, artifact identification data corresponding to a single breath-hold period is acquired. The beneficial effect of setting like this lies in that can in time carry out the artifact discernment to the magnetic resonance image collection that single breath-holding cycle gathered after every breath-holding cycle finishes to in time carry out subsequent benefit to this breath-holding cycle and sweep the step, reduce the benefit of mending and sweep the degree of difficulty, guarantee the timeliness of benefit and sweep the step.
Fig. 3 is a flowchart of a magnetic resonance scanning method corresponding to a multi-breath-hold scanning mode according to a second embodiment of the present invention. Specifically, the multiple breath-hold scanning mode comprises m breath-hold periods, after the nth (n is less than or equal to m) scanning is completed, magnetic resonance image reconstruction is carried out on scanning data obtained by scanning, a magnetic resonance image set is obtained, at least one magnetic resonance image in the magnetic resonance image set is respectively input into the target artifact identification model, and whether artifact images exist in the magnetic resonance image set is determined. If so, a supplementary scanning operation is performed, specifically, the nth scanning is re-performed based on the nth scanning parameter, and if not, n=n+1 and the nth scanning is continued to be performed in the case where n.ltoreq.m.
S240, rescanning operation is carried out on the tested object based on the rescanning parameters to obtain a corrected image, and the magnetic resonance image set is updated based on the corrected image to obtain a target magnetic resonance image set.
On the basis of the above embodiment, optionally, before determining the rescanning parameters corresponding to the artifact image based on the magnetic resonance scan mode, the method further comprises: displaying the artifact image and/or motion data corresponding to the artifact image on an interactive interface; and if a touch-up instruction input by the user based on the interactive interface is received, executing the operation of determining the rescanning parameters.
Wherein, for example, the artifact risk prompt corresponding to the artifact image can also be displayed on the interactive interface. Illustratively, the swipe instruction includes a target artifact image corresponding to a user selection operation. This has the advantage that magnetic resonance scanning errors are reduced, and thus unnecessary supplementary scanning steps are avoided, thereby improving the scanning efficiency of the magnetic resonance scan.
Fig. 4 is a flowchart of a specific example of a magnetic resonance scanning method according to the second embodiment of the present invention. Specifically, the multiple breath-hold scanning mode comprises m breath-hold periods, after the nth (n is less than or equal to m) scanning is completed, motion data are input into a second target artifact identification model to obtain a second identification result, specifically, whether the motion data fluctuate or not is determined according to the second identification result, if yes, artifact risks are indicated, if not, a magnetic resonance image obtained by reconstructing a magnetic resonance image based on scanning data obtained by scanning is input into a first target artifact identification model to obtain whether the magnetic resonance image has artifacts, if yes, artifact risks are indicated, if not, n=n+1 is indicated, and the nth scanning is continuously executed under the condition that n is less than or equal to m. After prompting that the artifact risk exists, determining whether a compensation instruction is received, if so, re-executing the nth scanning based on the nth scanning parameter, and if not, continuously executing the nth scanning under the condition that n=n+1 is less than or equal to m.
According to the technical scheme, the rescanning parameters corresponding to the artifact image are determined based on the magnetic resonance scanning mode, and the measured object is rescanned based on the rescanning parameters, so that the problem of determining the rescanning parameters in different magnetic resonance scanning modes is solved, the magnetic resonance scanning mode applicable to the supplementary scanning operation is widened, and the image quality obtained by the magnetic resonance scanning is further improved.
Example III
Fig. 5 is a schematic diagram of a magnetic resonance scanning apparatus according to a third embodiment of the present invention. The embodiment can be applied to the situation of carrying out artifact identification on the magnetic resonance image, the device can be realized in a software and/or hardware mode, and the device can be configured in magnetic resonance equipment or terminal equipment. The magnetic resonance scanning apparatus includes: an artifact identification data acquisition module 310, an artifact image identification module 320, a corrected image determination module 330, and a target magnetic resonance image set determination module 340.
The artifact identification data acquisition module 310 is configured to acquire artifact identification data in a magnetic resonance scanning process; wherein the artifact identification data comprises a set of magnetic resonance images and/or motion data respectively corresponding to at least one magnetic resonance image in the set of magnetic resonance images;
an artifact image identification module 320 configured to determine an artifact image in the magnetic resonance image set based on the artifact identification data and the trained target artifact identification model;
a corrected image determining module 330, configured to determine a rescanning parameter corresponding to the artifact image based on the magnetic resonance scan mode, and perform a rescanning operation on the measured object based on the rescanning parameter, to obtain a corrected image;
the target magnetic resonance image set determining module 340 is configured to update the magnetic resonance image set based on the correction image to obtain a target magnetic resonance image set.
According to the technical scheme, the artifact images in the magnetic resonance image set obtained through magnetic resonance scanning are identified, rescanning parameters corresponding to the artifact images are determined based on the magnetic resonance scanning mode, the magnetic resonance image set is updated based on the correction images obtained through rescanning, the problem that the timeliness of artifact image compensation operation is poor is solved, and the image quality obtained through magnetic resonance scanning is improved.
On the basis of the above technical solution, optionally, the correction image determining module 330 includes:
and the rescanning parameter determining unit is used for determining rescanning parameters corresponding to the artifact image according to the image position of the artifact image if the magnetic resonance scanning mode is a single breath-hold scanning mode or a non-breath-hold scanning mode.
On the basis of the above technical solution, optionally, the rescanning parameter determining unit is specifically configured to:
determining at least one slice group based on an image position of the at least one artifact image;
for each slice group, a rescan parameter corresponding to the slice group is determined based on a slice position of the slice group and a number of artifact images in the slice group.
On the basis of the above technical solution, optionally, the target artifact identification model includes a first target artifact identification model and/or a second target artifact identification model, and the corresponding artifact image identification module 320 includes:
the identification result determining unit is used for respectively inputting each magnetic resonance image into the first target artifact identification model to obtain an output first identification result, and/or respectively inputting each motion data into the second target artifact identification model to obtain an output second identification result;
an artifact image determining unit is used for determining an artifact image in the magnetic resonance image set based on the first identification result and/or the second identification result.
On the basis of the above technical solution, optionally, the apparatus further includes:
the system comprises a compensation instruction receiving module, a compensation instruction processing module and a display module, wherein the compensation instruction receiving module is used for displaying an artifact image and/or motion data corresponding to the artifact image on an interactive interface before determining rescanning parameters corresponding to the artifact image based on a magnetic resonance scanning mode; and if a touch-up instruction input by the user based on the interactive interface is received, executing the operation of determining the rescanning parameters.
On the basis of the above technical solution, optionally, the first recognition result includes a first artifact level corresponding to each magnetic resonance image, and the second recognition result includes a second artifact level corresponding to each motion data.
On the basis of the above technical solution, optionally, the artifact image determining unit is specifically configured to:
determining, for each magnetic resonance image, a target artifact level based on the first artifact level and the second artifact level;
and if at least one of the target artifact level, the first artifact level and the second artifact level reaches a preset level threshold, taking the magnetic resonance image as an artifact image.
The magnetic resonance scanning device provided by the embodiment of the invention can be used for executing the magnetic resonance scanning method provided by the embodiment of the invention, and has the corresponding functions and beneficial effects of the execution method.
It should be noted that, in the embodiment of the magnetic resonance scanning apparatus, each unit and module included are only divided according to the functional logic, but are not limited to the above-mentioned division, so long as the corresponding functions can be implemented; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present invention.
Example IV
Fig. 6 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention, which provides services for implementing the magnetic resonance scanning method according to the above embodiment of the present invention, and the magnetic resonance scanning apparatus according to the above embodiment may be configured. Fig. 6 shows a block diagram of an exemplary device 12 suitable for use in implementing embodiments of the present invention. The device 12 shown in fig. 6 is merely an example and should not be construed as limiting the functionality and scope of use of embodiments of the present invention.
As shown in fig. 6, device 12 is in the form of a general purpose computing device. Components of device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, a bus 18 that connects the various system components, including the system memory 28 and the processing units 16.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 30 and/or cache memory 32. Device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from or write to non-removable, nonvolatile magnetic media (not shown in FIG. 6, commonly referred to as a "hard disk drive"). Although not shown in fig. 6, a magnetic disk drive for reading from and writing to a removable non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In such cases, each drive may be coupled to bus 18 through one or more data medium interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored in, for example, memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules 42 generally perform the functions and/or methods of the embodiments described herein.
The processing unit 16 executes various functional applications and data processing, such as implementing the magnetic resonance scanning method provided by the embodiment of the present invention, by running a program stored in the system memory 28.
By the electronic equipment, the problem of large error of the artifact image recognition result is solved, and the magnetic resonance scanning efficiency and the recognition quality are improved.
Example five
A fifth embodiment of the present invention also provides a storage medium containing computer-executable instructions which, when executed by a computer processor, are for performing a magnetic resonance scanning method, the method comprising:
acquiring artifact identification data in the magnetic resonance scanning process; wherein the artifact identification data comprises a set of magnetic resonance images and/or motion data respectively corresponding to at least one magnetic resonance image in the set of magnetic resonance images;
determining an artifact image in the magnetic resonance image set based on the artifact identification data and the trained target artifact identification model;
determining rescanning parameters corresponding to the artifact image based on the magnetic resonance scanning mode, and performing rescanning operation on the measured object based on the rescanning parameters to obtain a corrected image;
and updating the magnetic resonance image set based on the correction image to obtain a target magnetic resonance image set.
The computer storage media of embodiments of the invention may take the form of any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations of the present invention may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
Of course, the storage medium containing the computer executable instructions provided in the embodiments of the present invention is not limited to the above method operations, and may also perform the related operations in the magnetic resonance scanning method provided in any embodiment of the present invention.
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.
Claims (10)
1. A magnetic resonance scanning method, comprising:
acquiring artifact identification data in the magnetic resonance scanning process; wherein the artifact identification data comprises a magnetic resonance image set and motion data respectively corresponding to at least one magnetic resonance image in the magnetic resonance image set;
determining an artifact image in the magnetic resonance image set based on the artifact identification data and a trained target artifact identification model;
determining rescanning parameters corresponding to the artifact image based on a magnetic resonance scanning mode, and performing rescanning operation on the measured object based on the rescanning parameters to obtain a corrected image;
and updating the magnetic resonance image set based on the correction image to obtain a target magnetic resonance image set.
2. The method of claim 1, wherein the determining rescan parameters corresponding to the artifact image based on a magnetic resonance scan mode comprises:
and if the magnetic resonance scanning mode is a single breath-hold scanning mode or a non-breath-hold scanning mode, determining rescanning parameters corresponding to the artifact image according to the image position of the artifact image.
3. The method of claim 2, wherein determining rescan parameters corresponding to the artifact image based on an image location of the artifact image comprises:
determining at least one slice group based on an image position of the at least one artifact image;
for each slice group, a rescan parameter corresponding to the slice group is determined based on a slice position of the slice group and a number of artifact images in the slice group.
4. The method of claim 1, wherein the target artifact identification model comprises a first target artifact identification model and a second target artifact identification model, and wherein the determining an artifact image in the set of magnetic resonance images based on the artifact identification data and the trained target artifact identification model, respectively, comprises:
respectively inputting each magnetic resonance image into a first target artifact identification model to obtain an output first identification result, and respectively inputting each motion data into a second target artifact identification model to obtain an output second identification result;
an artifact image in the set of magnetic resonance images is determined based on the first and second recognition results.
5. The method of claim 4, wherein prior to determining rescan parameters corresponding to the artifact image based on a magnetic resonance scan mode, the method further comprises:
displaying the artifact image and motion data corresponding to the artifact image on an interactive interface;
and if a compensation instruction input by a user based on the interactive interface is received, executing the operation of determining the rescanning parameters.
6. The method of claim 4, wherein the first recognition result includes a first artifact level respectively corresponding to each of the magnetic resonance images, and the second recognition result includes a second artifact level respectively corresponding to each of the motion data.
7. The method of claim 4, wherein the determining an artifact image in the set of magnetic resonance images based on the first and second recognition results comprises:
determining, for each magnetic resonance image, a target artifact level based on the first artifact level and the second artifact level;
and if at least one of the target artifact level, the first artifact level and the second artifact level reaches a preset level threshold, taking the magnetic resonance image as an artifact image.
8. A magnetic resonance scanning apparatus, comprising:
the artifact identification data acquisition module is used for acquiring artifact identification data in the magnetic resonance scanning process; wherein the artifact identification data comprises a magnetic resonance image set and motion data respectively corresponding to at least one magnetic resonance image in the magnetic resonance image set;
an artifact image recognition module for determining an artifact image in the set of magnetic resonance images based on the artifact recognition data and a trained target artifact recognition model;
the correction image determining module is used for determining rescanning parameters corresponding to the artifact image based on a magnetic resonance scanning mode, and performing rescanning operation on the tested object based on the rescanning parameters to obtain a correction image;
and the target magnetic resonance image set determining module is used for updating the magnetic resonance image set based on the correction image to obtain a target magnetic resonance image set.
9. An electronic device, the electronic device comprising:
one or more processors;
a memory for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the magnetic resonance scanning method of any one of claims 1-7.
10. A storage medium containing computer executable instructions which, when executed by a computer processor, are for performing the magnetic resonance scanning method as claimed in any one of claims 1 to 7.
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