Magnetic resonance imaging data acquisition method, magnetic resonance imaging data acquisition device, magnetic resonance imaging equipment, imaging method and imaging system

Abstract

The invention relates to a magnetic resonance imaging data acquisition method and device, equipment and an imaging method and system. The method comprises the following steps: acquiring original scanning data acquired by magnetic resonance equipment; abnormal point detection is carried out on the original scanning data, and abnormal positions in the original scanning data are determined; and determining target scanning data from the original scanning data according to the abnormal position. Complete magnetic resonance imaging data can be obtained by adopting the method.

Description

Technical Field

[0001] This application relates to the field of image processing technology, and in particular to a magnetic resonance imaging data acquisition method, apparatus, device, imaging method, and system. Background Technology

[0002] Magnetic resonance imaging (MRI) technology has been increasingly used in preclinical examinations and diagnosis of various systems due to its excellent soft tissue resolution and radiation-free characteristics.

[0003] Taking scientific research scenarios as an example, if an abnormality occurs during long-term scanning or advanced sequence scanning of the magnetic resonance equipment (e.g., abnormal power failure or manual stop), it may result in incomplete scanning data, affecting the subsequent image reconstruction process. Summary of the Invention

[0004] Therefore, it is necessary to provide a magnetic resonance imaging data acquisition method, apparatus, device, imaging method, and system that can acquire relatively complete magnetic resonance imaging data in response to the above-mentioned technical problems.

[0005] In a first aspect, this application provides a method for acquiring magnetic resonance imaging data, including:

[0006] Acquire raw scan data from the magnetic resonance imaging (MRI) device;

[0007] Anomaly detection is performed on the raw scan data to determine the locations of anomalies in the raw scan data;

[0008] Target scan data is determined from the original scan data based on the location of the anomaly.

[0009] In one embodiment, anomaly detection is performed on the original scan data to determine the locations of anomalies in the original scan data, including:

[0010] Retrieve the data attributes of multiple scan data points from the raw scan data;

[0011] Based on the data attributes of each scan data, anomaly detection is performed on the original scan data to determine the abnormal locations in the original scan data.

[0012] In one embodiment, anomaly detection is performed on the original scan data based on the data attributes of each scan data point to determine the abnormal locations in the original scan data, including:

[0013] Retrieve scan data where the data attribute is empty from each scan data set;

[0014] The location of scanned data with null data attributes is identified as an abnormal location in the original scanned data.

[0015] In one embodiment, determining the target scan data from the original scan data based on the abnormal location includes:

[0016] Identify the abnormal data in the original scan data based on the location of the abnormality;

[0017] Remove abnormal data from the original scan data to obtain the target scan data.

[0018] In one embodiment, determining abnormal data in the original scan data based on the abnormal location includes:

[0019] Obtain the scan data to be verified at any scan dimension for the abnormal location, and determine whether the scan data to be verified is complete;

[0020] If not, the scan data to be verified and all scan data following it will be identified as abnormal data.

[0021] In one embodiment, any scanning dimension includes one of the following: layer number dimension, phase encoding dimension, frequency encoding dimension, layer selection dimension, or cardiac phase encoding dimension.

[0022] In one embodiment, the method further includes:

[0023] Predict the total storage space of the target scan data based on the data dimensions of the target scan data;

[0024] The target scan data is split according to the total storage space and splitting rules;

[0025] The split target scan data is stored in the scan database.

[0026] Secondly, this application also provides a magnetic resonance imaging method, which includes any one of the magnetic resonance imaging data acquisition methods in the first aspect above, the magnetic resonance imaging method including:

[0027] Magnetic resonance imaging data is acquired based on the target scan data.

[0028] Thirdly, this application also provides a magnetic resonance imaging data acquisition device, comprising:

[0029] The acquisition module is used to acquire the raw scan data collected by the magnetic resonance imaging equipment;

[0030] The detection module is used to detect anomalies in the raw scan data and determine the locations of anomalies in the raw scan data.

[0031] The determination module is used to determine the target scan data from the raw scan data based on the abnormal location.

[0032] Fourthly, this application also provides a magnetic resonance imaging device, which includes:

[0033] The imaging module is used to reconstruct images based on target scanning data.

[0034] Fifthly, 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 content of any embodiment of the magnetic resonance imaging data acquisition method in the first aspect described above.

[0035] Sixthly, this application also provides a magnetic resonance imaging system, which includes a magnetic resonance device and a computer device, wherein the magnetic resonance device is connected to the computer device;

[0036] Magnetic resonance imaging (MRI) equipment is used to acquire raw scan data and send it to a computer.

[0037] Computer equipment is used to detect anomalies in raw scan data, determine the locations of anomalies in the raw scan data, and determine the target scan data from the raw scan data based on the locations of anomalies.

[0038] In a seventh aspect, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the content of any embodiment of the magnetic resonance imaging data acquisition method in the first aspect described above.

[0039] Eighthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the content of any embodiment of the magnetic resonance imaging data acquisition method in the first aspect described above.

[0040] The aforementioned magnetic resonance imaging (MRI) data acquisition method, apparatus, device, imaging method, and system acquire raw scan data from an MRI scanner; perform anomaly detection on the raw scan data to determine anomaly locations; and determine target scan data from the raw scan data based on the anomaly locations. This method, through anomaly detection, can determine whether the raw scan data was completely scanned during the scanning process. In the case of incomplete scanning, target scan data of the complete scan layer can be selected from the raw scan data based on the anomaly locations. Thus, using target scan data of the complete scan layer avoids affecting the subsequent image reconstruction process. Attached Figure Description

[0041] 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.

[0042] Figure 1 This is an application environment diagram of a magnetic resonance imaging data acquisition method in one embodiment;

[0043] Figure 2 This is a flowchart illustrating a magnetic resonance imaging data acquisition method in one embodiment;

[0044] Figure 3 This is a flowchart illustrating a magnetic resonance imaging data acquisition method in one embodiment;

[0045] Figure 4 This is a flowchart illustrating a magnetic resonance imaging data acquisition method in one embodiment;

[0046] Figure 5 This is a flowchart illustrating a magnetic resonance imaging data acquisition method in one embodiment;

[0047] Figure 6 This is a flowchart illustrating a magnetic resonance imaging data acquisition method in one embodiment;

[0048] Figure 7 This is a flowchart illustrating a magnetic resonance imaging data acquisition method in one embodiment;

[0049] Figure 8 This is a schematic diagram of a reconstructed image in one embodiment;

[0050] Figure 9 This is a schematic flowchart of a magnetic resonance imaging method in one embodiment;

[0051] Figure 10 This is a schematic flowchart of a magnetic resonance imaging method in one embodiment;

[0052] Figure 11 This is a structural block diagram of a magnetic resonance imaging data acquisition device in one embodiment. Detailed Implementation

[0053] 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.

[0054] The magnetic resonance imaging data acquisition method provided in this application embodiment can be applied to, for example... Figure 1 The application environment shown is a computer device that can be a server, personal computer, laptop, smartphone, tablet, or mobile phone. This computer device may include a processor, memory, and network interface connected via a system bus or wirelessly. The processor provides computing and control capabilities. The memory may include non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores data acquired during the magnetic resonance imaging (MRI) data acquisition process. The network interface of the computer device communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements a magnetic resonance imaging (MRI) data acquisition method.

[0055] In one exemplary embodiment, such as Figure 2 As shown, a method for acquiring magnetic resonance imaging data is provided, which can be applied to... Figure 1 The following steps, 201 to 203, are used as an example of computer equipment.

[0056] S201, acquire the raw scan data collected by the magnetic resonance imaging equipment.

[0057] In this embodiment, all raw scan data acquired by the MRI device are stored in a scan database. The computer device can search the scan database for scan data matching the identification information of the MRI device and use this matching scan data as the raw scan data acquired by the MRI device. Alternatively, the computer device can send a data acquisition command to the MRI device. Upon receiving the command, the MRI device begins acquiring raw scan data and sends the acquired raw scan data to the computer device. This embodiment does not limit the method of acquiring the raw scan data from the MRI device.

[0058] S202, perform anomaly detection on the original scan data to determine the abnormal locations in the original scan data.

[0059] An anomaly refers to a location where an anomaly occurs during an MRI scan. For example, an anomaly could be caused by a power outage or accidental manual stopping by the operator. Specifically, if a power outage or accidental manual stopping occurs during an MRI scan, the scan data following the anomaly point cannot be acquired.

[0060] In this embodiment, no data was collected after the anomaly point; that is, all data after the anomaly point was represented as zero. The computer device can analyze the original scan data, determine the starting point where the scan data is zero, and use this starting point as the anomaly position in the original scan data.

[0061] Alternatively, the computer device can input the raw scan data into a preset anomaly detection model, analyze the anomaly points in the raw scan data using the anomaly detection model, and output the locations of anomalies in the raw scan data. This application embodiment does not limit the method of anomaly detection.

[0062] It should be emphasized that if there are no abnormal locations in the original scan data, it means that the scanning process of the original scan data is complete, and the image reconstruction process can be performed directly.

[0063] S203, Determine the target scan data from the original scan data based on the abnormal location.

[0064] Target scan data refers to the scan data used for image reconstruction.

[0065] In this embodiment, since image reconstruction can only reconstruct complete layer scan data, anomalies may occur at the beginning, middle, or end of a layer's scan data. Regardless of the location of the anomaly within a layer, the scan data of the corresponding layer cannot be used for image reconstruction. Therefore, the computer device can determine the scan data of the anomalous layer based on the anomaly location. The scan data of the anomalous layer, as well as all subsequent scan data, are then cleared. This leaves only complete multi-layer scan data, which can then be used as the target scan data.

[0066] Optionally, after acquiring the abnormal location in the original scan data, the computer device can determine the abnormal location and the predicted scan data after the abnormal location based on the scan data before the abnormal location. Since the data after the abnormal scan layer is incomplete, the computer device can discard the data after the abnormal scan layer and use the data before the scanned layer as the target scan data.

[0067] The aforementioned magnetic resonance imaging (MRI) data acquisition method involves acquiring raw scan data from an MRI scanner; detecting anomalies in the raw scan data to determine abnormal locations; and identifying target scan data from the raw scan data based on these anomaly locations. This method, through anomaly detection, can determine whether the raw scan data was completely scanned during the scanning process. In the case of incomplete scanning, target scan data representing complete scan layers can be selected from the raw scan data based on the anomaly locations. Thus, using target scan data representing complete scan layers avoids impacting subsequent image reconstruction processes.

[0068] The following example illustrates the specific process of determining anomaly locations in raw scan data through anomaly detection. This example focuses on the layer-level dimension, but the process remains applicable to other data dimensions. In one embodiment, such as... Figure 3 As shown, the specific process includes the following steps:

[0069] S301, retrieve the data attributes of multiple scan data in the original scan data.

[0070] The raw scan data comprises multiple layers, with each layer containing multiple data points. During the scanning process using an MRI scanner, once any data point is acquired, its data attributes are generated. The data attributes of each data point in the raw scan data are stored together with the corresponding data. For example, the data attributes of any data point may include its length, index, and the scan layer it belongs to, etc.

[0071] In this embodiment, after obtaining the original scan data, the computer device can layer the original scan data to obtain multi-layer scan data, and then obtain the data attributes of each scan data in the multi-layer scan data.

[0072] S302, based on the data attributes of each scan data, perform anomaly detection on the original scan data to determine the abnormal locations in the original scan data.

[0073] If there is an abnormal power outage or the operator accidentally stops the scan, the MRI machine will stop scanning, and that scan data will not be detected. In this case, the scan attributes of the scan data will be filled with abnormal values. The computer can filter out the abnormal values ​​(empty values) from the data attributes of multiple scan data and use the positions corresponding to the abnormal values ​​as the abnormal positions in the original scan data.

[0074] Optionally, the computer device can also input each scan data and its corresponding data attributes into a preset anomaly detection model, and analyze the data attributes of each scan data through the anomaly detection model to determine the location of anomalies in the original scan data.

[0075] The aforementioned magnetic resonance imaging (MRI) data acquisition method involves acquiring the data attributes of multiple scan data points from the original scan data. Based on the data attributes of each scan data point, anomaly detection is performed on the original scan data to determine the locations of anomalies. This method, by acquiring the data attributes of each scan data point and based on these attributes, can accurately determine whether the scan data corresponding to that data attribute is abnormal, thereby accurately identifying the locations of anomalies in the original scan data.

[0076] If there is an abnormal power outage or the operator accidentally stops the scan manually, the MRI machine will stop scanning, and the scan data will not be detected. In this case, the scan data's attributes will be missing and will be empty. Therefore, in one embodiment, such as... Figure 4 As shown, the specific process of detecting outliers in the original scan data based on the data attributes of each scan data includes:

[0077] S401, retrieve scan data whose data attributes are empty from each scan data.

[0078] In this embodiment, the computer device can simultaneously analyze the data attributes of multiple scan data in multiple scan layers to determine whether there is scan data with null values ​​in each scan layer. Alternatively, the computer device can iterate through the data attributes of all scan data to determine scan data with null values. Furthermore, in the event of an abnormal power outage or accidental manual stopping by the operator, the data attributes of that scan data may show an error message, and the computer device can determine the scan data with null values ​​based on the location of the error message.

[0079] S402, the location of scanned data with null data attributes is determined as the abnormal location of the original scanned data.

[0080] In this embodiment of the application, since the location of scanned data with null data attributes is the location of an anomaly, the computer device can take the location of scanned data with null data attributes as the location of an anomaly in the original scanned data.

[0081] In the aforementioned magnetic resonance imaging data acquisition method, scan data with null values ​​are acquired from each scan data set; the locations of these null value scan data are identified as abnormal locations in the original scan data. This method, based on whether the data attributes are null, can accurately identify each scan data set, thereby accurately determining the abnormal locations in the original scan data.

[0082] The above embodiments illustrate how to determine abnormal locations in raw scan data. After obtaining the abnormal locations, it is also necessary to determine the target scan data for image reconstruction based on these locations. In one embodiment, such as... Figure 5 As shown, the specific process of determining target scan data based on abnormal locations may include:

[0083] S501, Based on the abnormal location, identify the abnormal data in the original scan data.

[0084] In this embodiment, since no data was acquired after the abnormal location, only the original scan data before the abnormal location is retained as the target reconstruction data. The image can then be obtained through subsequent magnetic resonance imaging (MRI) data acquisition. The computer device can determine the scanning layer corresponding to the abnormal location based on the abnormal location, and treat all data from that scanning layer and all data from subsequent scanning layers as abnormal data in the original scan data.

[0085] S502, delete abnormal data in the original scan data to obtain the target scan data.

[0086] In this embodiment of the application, after obtaining abnormal data in the original scan data, the computer device can delete the abnormal data. The deleted original scan data is the scan data of the complete scan layer required for image reconstruction, and the deleted original scan data is used as the target scan data.

[0087] In the aforementioned magnetic resonance imaging (MRI) data acquisition method, abnormal data in the original scan data is identified based on the location of the abnormality; the abnormal data is then deleted to obtain the target scan data. This method can accurately identify and delete abnormal data from the original scan data by identifying the abnormal location, thus improving the accuracy of the obtained target scan data.

[0088] Image reconstruction can only reconstruct data from a single complete scan layer. Therefore, in one embodiment, such as... Figure 6 As shown, the abnormal data in the original scan data determined based on the abnormal location includes the following:

[0089] S601, obtain the scan data to be verified at the abnormal location in any scan dimension, and determine whether the scan data to be verified is complete.

[0090] Any one of the scanning dimensions can be a layer dimension, a phase encoding dimension, a frequency encoding dimension, a layer selection dimension, or a cardiac phase encoding dimension.

[0091] In this embodiment, taking a layer-based scanning dimension as an example, the computer device can calculate the scanning layer where the abnormal location is located based on the abnormal location and the protocol parameters before the magnetic resonance imaging (MRI) device scans. The protocol parameters may include readout codes, first phase codes, second phase codes, number of coil channels, average number of scans, and number of repetitions. For example, the protocol parameters could be [176, 108, 110, 3, 4, 35]. The actual scanning parameters could be [176, 184, 144, 3, 4, 27]. If the abnormal location is the 2,748,623rd scan data point, and the calculated result is 26.1157, then the scanning layer where the abnormal location is located is layer 27.

[0092] Furthermore, computer equipment can also use the average number of times, the number of repetitions, or the number of layers as splitting dimensions to determine the location of abnormal data under different dimensions. Then, it can determine the scanned data to be verified under that dimension and whether the scanned data is complete. For example, based on the above calculation results, it can be seen that only a portion of the data was scanned during the scanning process for layer 27; therefore, the scanned data corresponding to this layer is incomplete.

[0093] S602, if not, identify the scan data to be verified and all scan data after the scan data to be verified as abnormal data.

[0094] In this embodiment, taking layer-level scanning as an example, if the scan data of the scan layer where the abnormal location is determined to be incomplete, then all scan data of that scan layer and all data of the scan layers after that scan layer cannot be used for image reconstruction. Therefore, the scan data corresponding to the scan layer and all data of the scan layers after that scan layer can be directly identified as abnormal data.

[0095] In the aforementioned magnetic resonance imaging (MRI) data acquisition method, the scan data to be verified at the abnormal location in any scanning dimension is acquired, and it is determined whether the scan data to be verified is complete. If not, the scan data to be verified and all subsequent scan data are identified as abnormal data. This method determines whether the scan data to be verified at the abnormal location in any scanning dimension is complete, and based on the determination result, abnormal data can be accurately identified from the original scan data.

[0096] It should be noted that the aforementioned magnetic resonance imaging (MRI) equipment can be animal MRI equipment, primarily used for MRI scans of animals. Alternatively, the MRI equipment can also be a high-magnetic-field MRI equipment, for example, the magnetic field strength of which can be 7 Tesla (T), 9.4T, 11T, etc. Furthermore, the MRI equipment can also be a preclinical research MRI equipment.

[0097] In scientific research settings, magnetic resonance imaging (MRI) devices generate enormous amounts of scan data during long-duration or advanced sequence scans, typically reaching tens or even hundreds of gigabytes (GB). The large volume of scan data is easily limited by computer hardware resources during reading and parsing. To address this issue, embodiments of this application can split and store the scan data, thus facilitating the reading and parsing of the scan data during subsequent image reconstruction.

[0098] In one embodiment, such as Figure 7 As shown, the process of splitting storage includes the following:

[0099] S701, predicts the total storage space of the target scan data based on the data dimension of the target scan data.

[0100] In this embodiment of the application, the computer device can obtain the variable types of the target scan data and estimate the total storage space required for the target scan data based on the data dimensions and variable types of the target scan data.

[0101] S702 splits the target scan data according to the total storage space and splitting rules.

[0102] The dimensions for splitting the target scan data can be the average number of times, the number of repetitions, the number of layers, or other data dimensions.

[0103] In this embodiment, the computer device can split the target scan data according to the average split dimension to determine the storage space under the average split dimension. Additionally, the computer device can also split the target scan data according to the number of layers split dimension to determine the storage space under the number of layers split dimension. The storage space under the average split dimension is compared with the storage space under the number of layers split dimension, and the split result of the split dimension with the smaller storage space is taken as the split result of the target scan data.

[0104] S703 stores the split target scan data into the scan database.

[0105] In this embodiment of the application, if the total storage space is less than the storage space of the computer device, the computer device can store the split target scan data into the scan database corresponding to the computer device.

[0106] In the aforementioned magnetic resonance imaging data acquisition method, the total storage space of the target scan data is predicted based on the data dimensions of the target scan data; the target scan data is then split according to the total storage space and splitting rules; and the split target scan data is stored in the scan database. This method splits the target scan data through data splitting to facilitate the storage of large amounts of target scan data.

[0107] Once the target scan data is stored, subsequent magnetic resonance imaging (MRI) procedures can be performed. In one embodiment, the MRI method includes:

[0108] Image reconstruction is performed based on the target scan data.

[0109] In this embodiment of the application, after the target scanning data is split and saved in the scanning database, when magnetic resonance imaging data needs to be acquired, the computer device can obtain the target scanning data from the scanning database and perform preprocessing on the target scanning data (e.g., noise reduction, filtering, etc.) to reduce signal noise caused by system and other factors.

[0110] Specifically, after acquiring the preprocessed target scan data, the computer equipment can use magnetic resonance imaging (MRI) data acquisition algorithms to reconstruct the preprocessed target scan data, obtaining a reconstructed MRI image corresponding to the preprocessed target scan data. It should be noted that the reconstructed MRI image can be a partial image of the scanning area of ​​the MRI equipment, or it can be an image of the entire scanning area.

[0111] Furthermore, computer devices can also write reconstructed images into Digital Imaging and Communications in Medicine (DICOM) images.

[0112] Figure 8 This diagram illustrates the reconstructed image, showing that the reconstructed image is only a portion of the scanned area of ​​the magnetic resonance imaging (MRI) device. For example, MRI data acquisition algorithms can include Fast Fourier Transform (FFT) algorithms, back projection algorithms, and so on.

[0113] In the aforementioned magnetic resonance imaging method, image reconstruction is performed based on the target scan data. Since the scan data in the scan database is stored in segments, the process of reading and parsing this scan data is more convenient, facilitating the image reconstruction process.

[0114] As a specific embodiment of this application, processes such as anomaly detection, data splitting, and image reconstruction all belong to the magnetic resonance imaging process. The magnetic resonance imaging process will be described in detail below. In one embodiment, such as... Figure 9 As shown, magnetic resonance imaging methods include:

[0115] S801, acquire the raw scan data collected by the magnetic resonance imaging equipment;

[0116] S802, retrieve the data attributes of multiple scan data in the raw scan data;

[0117] S803, retrieve scan data whose data attributes are empty in each scan data;

[0118] S804, the location of scanned data with null data attributes is determined as the abnormal location of the original scanned data;

[0119] S805: Obtain the scan data to be verified at any scan dimension where the abnormal location is located, and determine whether the scan data to be verified is complete.

[0120] S806, If not, the scan data to be verified and all scan data after the scan data to be verified are identified as abnormal data;

[0121] S807, delete abnormal data in the original scan data to obtain the target scan data;

[0122] S808 predicts the total storage space of the target scan data based on the data dimensions of the target scan data;

[0123] S809 splits the target scan data according to the total storage space and splitting rules;

[0124] S810 stores the split target scan data into the scan database;

[0125] S811 retrieves target scan data from the scan database and performs image reconstruction based on the target scan data.

[0126] Figure 10 This is a flowchart of a magnetic resonance imaging (MRI) method, which includes: S901: acquiring abnormally large raw scan data; S902: detecting abnormal points in the raw scan data and determining the abnormal locations; S903: deleting abnormal data from the raw scan data based on the abnormal locations; S904: splitting and storing the deleted raw scan data according to the splitting dimensions; S905: performing preprocessing such as denoising and filtering on the deleted raw scan data; S906: reconstructing the image from the preprocessed scan data to obtain a reconstructed image; S907: writing the reconstructed image into a medical digital imaging and communication image.

[0127] 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.

[0128] Based on the same inventive concept, this application also provides a magnetic resonance imaging data acquisition device for implementing the magnetic resonance imaging data acquisition method described above. The solution provided by this device is similar to the implementation described in the above method; therefore, the specific limitations in one or more embodiments of the magnetic resonance imaging data acquisition device provided below can be found in the limitations of the magnetic resonance imaging data acquisition method described above, and will not be repeated here.

[0129] In one exemplary embodiment, such as Figure 11 As shown, a magnetic resonance imaging data acquisition device is provided, comprising: an acquisition module 11, a detection module 12, and a determination module 13, wherein:

[0130] The acquisition module 11 is used to acquire the raw scan data collected by the magnetic resonance imaging device;

[0131] Detection module 12 is used to detect abnormal points in the original scan data and determine the abnormal locations in the original scan data;

[0132] The determination module 13 is used to determine the target scan data from the original scan data based on the abnormal location.

[0133] In one embodiment, the detection module 12 includes: an attribute acquisition unit and a detection unit, wherein:

[0134] The attribute acquisition unit is used to acquire the data attributes of multiple scan data in the original scan data;

[0135] The detection unit is used to detect anomalies in the original scan data based on the data attributes of each scan data, and to determine the abnormal locations in the original scan data.

[0136] In one embodiment, the detection unit is further configured to acquire scan data in each scan data where the data attribute is null; and to determine the location of the scan data with null data attribute as the abnormal location of the original scan data.

[0137] In one embodiment, the determining module includes: a data determining unit and a deletion unit, wherein:

[0138] The data determination unit is used to determine abnormal data in the original scan data based on the abnormal location;

[0139] The deletion unit is used to delete abnormal data in the original scan data to obtain the target scan data.

[0140] In one embodiment, the data determination unit is further configured to acquire the scan data to be verified at the abnormal location in any scanning dimension, and determine whether the scan data to be verified is complete; if not, the scan data to be verified and all scan data after the scan data to be verified are determined as abnormal data.

[0141] Any one of the scanning dimensions includes one of the following: layer number dimension, phase encoding dimension, frequency encoding dimension, layer selection dimension, or cardiac phase encoding dimension.

[0142] In one embodiment, the magnetic resonance imaging data acquisition device further includes: a prediction module, a splitting module, and a storage module, wherein:

[0143] The prediction module is used to predict the total storage space of the target scan data based on the data dimensions of the target scan data.

[0144] The splitting module is used to split the target scan data according to the total storage space and splitting rules;

[0145] The storage module is used to store the split target scan data into the scan database.

[0146] In one exemplary embodiment, a magnetic resonance imaging apparatus is provided, including a reconstruction module, wherein:

[0147] The reconstruction module is used to reconstruct images based on target scan data.

[0148] The aforementioned magnetic resonance imaging data acquisition device and magnetic resonance imaging device, and their respective modules, 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 in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0149] 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 implement the content of any of the embodiments of the magnetic resonance imaging data acquisition methods described above.

[0150] In one exemplary embodiment, a magnetic resonance imaging system is provided, which includes a magnetic resonance device and a computer device, wherein the magnetic resonance device is connected to the computer device.

[0151] Magnetic resonance imaging (MRI) equipment is used to acquire raw scan data and send it to a computer.

[0152] Computer equipment is used to detect anomalies in raw scan data, determine the locations of anomalies in the raw scan data, and determine the target scan data from the raw scan data based on the locations of anomalies.

[0153] The aforementioned magnetic resonance imaging (MRI) system includes an MRI scanner and a computer, with the MRI scanner connected to the computer. The MRI scanner acquires raw scan data and transmits it to the computer. The computer detects anomalies in the raw scan data to determine their locations. Based on these anomalies, it identifies target scan data from the raw scan data. By detecting anomalies in the raw scan data acquired by the MRI scanner, the computer in this system can determine whether the raw scan data was completely scanned during the scanning process. In cases of incomplete scans, target scan data representing complete scan layers can be selected from the raw scan data based on the anomaly locations. This avoids impacting subsequent image reconstruction processes by using target scan data representing complete scan layers.

[0154] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the content of any embodiment of the magnetic resonance imaging data acquisition method described above.

[0155] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the content of any one of the embodiments of the magnetic resonance imaging data acquisition method described above.

[0156] It should be noted that the user information (including but not limited to 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.

[0157] 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, database, 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.

[0158] 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.

[0159] 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 method of magnetic resonance imaging data acquisition, characterized by, The method comprises: acquiring original scanning data collected by a magnetic resonance device; performing outlier detection on the original scanning data to determine an abnormal position in the original scanning data; determining target scanning data from the original scanning data according to the abnormal position.

2. The method of claim 1, wherein, The performing of the outlier detection on the original scanning data to determine the abnormal position in the original scanning data comprises: acquiring data attributes of a plurality of pieces of scanning data in the original scanning data; performing outlier detection on the original scanning data according to the data attributes of the scanning data to determine the abnormal position in the original scanning data.

3. The method of claim 2, wherein, The performing of the outlier detection on the original scanning data according to the data attributes of the scanning data to determine the abnormal position in the original scanning data comprises: acquiring scanning data with a null data attribute in each piece of scanning data; determining the position of the scanning data with the null data attribute as the abnormal position of the original scanning data.

4. The method according to any one of claims 1 to 3, characterized in that, The determining of the target scanning data from the original scanning data according to the abnormal position comprises: determining abnormal data in the original scanning data according to the abnormal position; deleting the abnormal data in the original scanning data to obtain the target scanning data.

5. The method of claim 4, wherein, The determining of the abnormal data in the original scanning data according to the abnormal position comprises: acquiring to-be-verified scanning data of the abnormal position in any one scanning dimension and determining whether the to-be-verified scanning data is complete; if not, determining the to-be-verified scanning data and all scanning data after the to-be-verified scanning data as the abnormal data.

6. The method of claim 5, wherein, The any one scanning dimension comprises one of a layer dimension, a phase encoding dimension, a frequency encoding dimension, a layer selection dimension, or a cardiac phase encoding dimension.

7. The method according to any one of claims 1 to 3, characterized in that, The method further comprises: predicting a total storage space of the target scanning data according to a data dimension of the target scanning data; splitting the target scanning data according to the total storage space and a splitting rule; storing the split target scanning data into a scanning database.

8. A magnetic resonance imaging method characterized by, The magnetic resonance imaging data acquisition method according to any one of claims 1-6 further comprises: performing image reconstruction according to the target scanning data. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-8 when the computer program is executed by the processor. The processor implements the steps of the method of any one of claims 1-7 when executing the computer program.

10. A magnetic resonance imaging system, characterized by The magnetic resonance device and the computer device are connected; The magnetic resonance device is configured to collect original scanning data and send the original scanning data to the computer device; The computer device is configured to perform outlier detection on the original scanning data to determine an abnormal position in the original scanning data, and determine target scanning data from the original scanning data according to the abnormal position.

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