50 results about "Magnetic resonance sequence" patented technology

The invention relates to a computer-implemented method for operating a magnetic resonance device (20) during a recording process according to a recording protocol, which comprises a plurality of sequence sections (1) of a magnetic resonance sequence in at least one repetition, wherein each sequence section (1) comprises a preparation module (8) and a readout module (10), and each readout module (10) comprises a plurality of readout submodules (2), in each of which radio-frequency pulses (12, 13) precede readout periods (6) for recording magnetic resonance data, wherein - in each readout module (10) at least one navigator submodule (11) is used to record navigator data of the sequence section (1), - for each sequence section (1), correlation information is determined by comparing the navigator data record of the sequence section (1) with at least one navigator data record of a further sequence section (1), and - the correlation information is evaluated to select sequence sections (1) whose magnetic resonance data are discarded and / or to assign a weighting to the magnetic resonance data of at least some of the sequence sections (1) before reconstructing a magnetic resonance image.

The invention relates to the field of medical image processing, and discloses a multi-mode magnetic resonance aneurysm occlusion assessment method and system. The method comprises the following steps: acquiring scanning configuration and a multi-modal magnetic resonance sequence, and generating fused image data through cross-modal registration, artifact suppression and denoising processing; image segmentation, three-dimensional structure reconstruction and topology correction are carried out, and a three-dimensional anatomy and blood flow model is obtained; then, through gridding, index normalization and time sequence alignment processing, individual feature vectors are extracted; and finally, obtaining a blocking mechanism score and probability based on multi-model fusion reasoning, completing three-dimensional visual rendering, and backfilling key parameters to a configuration structure to form closed-loop optimization. According to the method, multi-modal data are effectively integrated, the evaluation accuracy is improved, and self-adaptive optimization and result traceability of the system are realized through parameter backfilling.

The invention provides a training method for a thermal ablation related image generation model, and the method comprises the steps: collecting a rapid magnetic resonance sequence image and a thermal ablation related image in the same thermal ablation process through a reproducible thermal ablation simulation test; forming a training sample by taking the fast magnetic resonance sequence image as a sample and taking a corresponding thermal ablation related image as annotation data; and generating a training sample set by referring to the previous steps, and training a deep learning model to obtain a thermal ablation related image generation model. According to the method, the rapid magnetic resonance sequence image and the corresponding thermal ablation related image data are acquired through the reproducible thermal ablation simulation test, and the defects that real thermal ablation data are insufficient and training data of the model are difficult to acquire are effectively overcome. Moreover, the user can acquire the image through the rapid magnetic resonance sequence in the clinical thermal ablation process and generate the thermal ablation related image by using the trained thermal ablation related image generation model, and the real-time performance and accuracy of ablation monitoring are both considered.

The invention relates to a computer-implemented method for acquiring magnetic resonance data with a magnetic resonance device (18), wherein a magnetic resonance sequence is used in which, during an equilibrium state in a sequence segment maintained by regular excitation modules (9, 9a - 9e) with at least one excitation pulse, both a first readout time window (11, 11a - 11e) immediately following an excitation module (9, 9a - 9e) for measuring magnetic resonance data of a free induction decay and second readout time windows (12, 12a - 12e), which are spaced at least the first readout duration of the first readout time window (11, 11a - 11e) from a last excitation module (9, 9a - 9e), which acts as a refocusing module for the penultimate excitation module (9, 9a - 9e), are used for measuring magnetic resonance data of a spin echo. become,wherein, between at least one pair consisting of a starting excitation module (9c) and a final excitation module (9d) that follow one another, a fat saturation module (15) with at least one high-frequency fat saturation pulse (16) is output in the magnetic resonance sequence during a preparation period (14).

The present application relates to the field of biotechnology, in particular to biomarkers for predicting the risk of central nervous system paralymphoid dysfunction and application thereof. The biomarkers for predicting the risk of central nervous system paralymphoid dysfunction are astrocyte-derived migratory bodies isolated from peripheral blood. An increase in the number of peripheral blood astrocyte-derived migratory bodies can be used as a marker for predicting the risk of paralymphoid dysfunction. The peripheral blood astrocyte migratory bodies provided by the present application can be used as an index for predicting the risk of central nervous system paralymphoid dysfunction, which can help to prompt central nervous system paralymphoid dysfunction when a patient cannot complete a head magnetic resonance DTI-ALPS sequence scan. The peripheral blood astrocyte migratory bodies can help doctors to formulate appropriate prevention or treatment plans for patients in combination with clinical symptoms, medical history or other examination information in a timely manner, and have extremely important clinical application potential and value.

A computer-implemented method for operating a magnetic resonance device during the acquisition of magnetic resonance data from an examination region of an examination object may use a magnetic resonance sequence. The MR sequence may include a saturation section in which, by means of a saturation radiofrequency pulse which is generated when a saturation gradient pulse is applied, a saturation with respect to a spin species that is to be imaged is performed in at least one first saturation region. The saturation radiofrequency pulse may be designed as a multiband pulse by means of which, in addition, in at least one second saturation region, the magnetization with respect to a second spin species that is not to be captured is saturated.

The invention is suitable for the technical field of magnetic resonance imaging, and provides a magnetic resonance sequence generation method and device, equipment, a storage medium and a product, and the method comprises the steps: pre-designing a plurality of candidate sequence modules, packaging the corresponding parameter calculation logic and working mode setting logic, and carrying out the content configuration of a selected target sequence module, according to the method, the hardware equipment is controlled to operate according to the configured working mode and the parameter calculation mode, so that the target magnetic resonance sequence is generated, the generation process of the magnetic resonance sequence is simplified, each parameter in the magnetic resonance sequence is prevented from being manually and independently debugged, the generation efficiency of the magnetic resonance sequence is improved, and the development period of the magnetic resonance sequence is shortened.

The invention relates to a method for classifying and identifying lesions in magnetic resonance images based on a causal line network model, and the method comprises the steps: collecting magnetic resonance multi-parameter sequence data, screening out sample data from the data, carrying out the preprocessing, and constructing a data set; building a causal line network model, and training the causal line network model by using the data set to obtain a focus recognition model; a current to-be-recognized magnetic resonance sequence image is preprocessed, then the image is input into the focus recognition model, and a corresponding focus type and a sign signal are output and obtained. Compared with the prior art, the accuracy and interpretability of focus type identification can be improved, and more comprehensive focus characteristic prediction, better clinical interpretability, causal interpretability of a model structure and higher prediction output consistency are realized.

The invention relates to the technical field of magnetic resonance imaging, in particular to a configuration method and device of a magnetic resonance sequence, equipment, a storage medium and a product. The method comprises the following steps: the terminal equipment displays configuration information corresponding to a plurality of candidate sequence modules respectively, wherein the configuration information comprises a plurality of configuration parameters corresponding to the candidate sequence modules; in response to a parameter input operation on the target sequence module, configuration result information corresponding to the target sequence module is generated, and the configuration result information comprises parameter values after the configuration parameters are configured respectively; and generating a sequence result corresponding to the target sequence module based on the configuration result information. By providing the standardized configuration file for the designer to perform parameter configuration on the preset candidate sequence module, the sequence result meeting the requirement can be directly generated, so that the difficulty of sequence development and the debugging complexity are effectively reduced, and the design and generation efficiency of the magnetic resonance sequence is remarkably improved.

The disclosure relates to a computer-implemented method for processing a magnetic resonance data set of an acquisition area, which is based on an acquisition in an examination procedure in a magnetic resonance facility with a magnetic resonance sequence in which multiple echoes are acquired in an echo train, in particular after a common radio-frequency excitation pulse. For the magnetic resonance data set, a path data set describing the signal path of the measured magnetic resonance signal over an acquisition period, in particular the echo train, in the magnetic resonance sequence is determined in the k-space. A trained image processing function for determining a result data set is transferred together with the magnetic resonance data set as input data.

The invention discloses a method, system, electronic device and computer storage medium for detecting rapeseed clubroot disease, and relates to the technical field of clubroot disease detection. The method comprises: obtaining a target magnetic resonance sequence image; the rapeseed root system to be detected is the rapeseed root system in the soil; segmenting, aligning and multiplying the target magnetic resonance sequence image in sequence, and three-dimensionally reconstructing the target root system three-dimensional model; based on the three-dimensional interactive measurement technology, obtaining the root system parameters of the rapeseed root system to be detected from the target root system three-dimensional model; the root system parameters include: total root system length, main root length, maximum root system depth, maximum root system width, maximum root system diameter, root system volume and number of root branches; the root system parameters are input into the rapeseed clubroot disease detection model to obtain the detection result of the rapeseed root system to be detected. The invention directly detects the rapeseed root system still in the soil through the rapeseed clubroot disease detection model, and realizes the in-situ non-destructive detection of rapeseed clubroot disease.

The invention relates to a computer-implemented method for processing a magnetic resonance data set (23) of a recording region based on recording in an examination process in a magnetic resonance apparatus by means of a magnetic resonance sequence in which a plurality of echoes (16) in an echo train are recorded, in particular after a common radio frequency excitation pulse (16), wherein a change process data set (24) in k-space is ascertained with respect to a magnetic resonance data set (23), said change process data set (24) describing a signal change process (17) of a magnetic resonance signal measured in the magnetic resonance sequence in a recording period, in particular in the range of the echo train, and transmitting the change process dataset together with the magnetic resonance dataset (23) as input data to a trained image processing function in order to ascertain a result dataset.

The invention relates to a computer-implemented method for processing a magnetic resonance data set, the magnetic resonance data of which are recorded in k-space at various k-space positions, which are sampled along a k-space trajectory using a magnetic resonance sequence, with a magnetic resonance device in a recording operation, wherein the spatial resolution of the magnetic resonance data set in the image space is increased. - a resolution enhancement function, especially one that has been trained, is applied to a low-resolution base image reconstructed from the magnetic resonance data in order to obtain a higher-resolution intermediate image, - an intermediate data set in k-space is determined from the intermediate image by means of a Fourier transform, - to obtain a target dataset, the portions of k-space covered by the magnetic resonance data of the magnetic resonance dataset in k-space are replaced by the magnetic resonance data in the intermediate dataset, and - a higher resolution target image is reconstructed and provided from the target dataset, whereby - in a correction process at least one edge height (7) is reduced at at least one boundary between the sampled k-space (2) and an extension component (3) of the k-space that extends the originally sampled k-space (2) due to the increase in resolution, which edge height (7) occurs due to intensity weights in the magnetic resonance data set because of the time of sampling of a respective k-space position after a high-frequency excitation pulse during the magnetic resonance sequence, wherein the intensity weights are not present in the extension component (3).

This invention discloses a magnetic resonance imaging (MRI) sequence translation communication control system and method. The system includes: a parameter customization module for receiving and verifying user-configured MRI parameters; a sequence generation module for generating MRI sequence files conforming to the Pulseq standard based on the verified parameters; a sequence translation module for translating the MRI sequence files into a TLV format hardware instruction stream according to the target spectrometer hardware configuration file; a hardware control module for writing the TLV instruction stream into the spectrometer hardware registers via an open hardware instruction bus, controlling the spectrometer to transmit radio frequency pulses, apply gradient fields, and acquire MRI signals; and a verification and feedback module for real-time monitoring of hardware execution status and data consistency verification. This invention solves the problems of complex hardware interfaces and poor sequence portability in existing MRI systems by constructing a closed-loop architecture of "parameter configuration - sequence generation - TLV translation - hardware execution," thereby improving the system's versatility, scalability, and control accuracy.

The present invention discloses a VTK-based magnetic resonance scanning coordinate system conversion method and device, comprising: placing a preset phantom in a scanning coil in a preset manner and moving it to the scanning center, scanning the preset phantom based on a preset magnetic resonance sequence to obtain raw data; determining an MR coordinate system based on the raw data and a first preset gradient excitation matrix; determining a gradient excitation matrix based on the MR coordinate system, the VTK coordinate system, and the position matrix of the current FOV in the VTK coordinate system; determining the excitation mode of the preset magnetic resonance sequence, and determining a layer selection offset value based on the excitation mode; and determining the position information of the image data matrix based on the gradient excitation matrix and the layer selection offset value. The above-mentioned coordinate system conversion process no longer needs to consider the scanning posture, and the conversion from the VTK coordinate system to the MR coordinate system can be achieved based on the determination of the gradient excitation matrix and the layer selection offset value.

The invention discloses a central axis type spinal arthritis sacroiliac joint MRI synthesis CT image processing system and method based on a deep learning algorithm, and the system comprises a data obtaining unit which is used for obtaining magnetic resonance sequence data obtained through the magnetic resonance imaging of a sacroiliac joint of a target user; the deep learning model unit is used for inputting the magnetic resonance sequence data into a deep learning algorithm model trained by federal learning to obtain bone cortex features and soft tissue features of sacroiliac joints; the image synthesis unit is used for synthesizing a synthesized CT image corresponding to the sacroiliac joint of the target user based on the bone cortex features and the soft tissue features, non-radiation high-precision CT image acquisition is achieved, the diagnosis requirement for the axial spine joint in the sacroiliac joint can be met, and the influence of radiation on the target user can be reduced.

A method for generating am intensity-corrected magnetic resonance representation. In this method, reference measurement data is provided, wherein at least part of the reference measurement data is generated from magnetic resonance signals acquired by at least one receive antenna of at least one local coil by a magnetic resonance apparatus in accordance with a reference magnetic resonance sequence. In addition, image measurement data is provided, which is generated from magnetic resonance signals acquired by the at least one receive antenna of the least one local coil by the magnetic resonance apparatus in accordance with an image magnetic resonance sequence. A function trained by a machine learning algorithm is applied to the reference measurement data and the image measurement data as input data of the trained function. Correction data is provided from output data of the trained function, wherein the correction data describes an instrumentation-induced intensity inhomogeneity of the image measurement data. An intensity-corrected magnetic resonance representation is generated on the basis of the image measurement data and the correction data.

This invention discloses a method for generating missing modalities in brain MRI based on hypergraphs and attention mechanisms. This method addresses the issue of missing modalities in multimodal brain MRI sequences such as T1, T1ce, T2, and FLAIR in clinical scenarios by constructing a unified multi-input multi-output translation framework. The method introduces hypergraph convolution and region-level self-attention into the generative network, aggregating group-level features from different tumors and healthy tissues and modeling structural relationships between sub-regions, preserving the spatial tissue structure of the tumor. Combined with bidirectional Mamba sequence modeling, it enables the 2D network to efficiently capture long-range dependencies between layers of 3D volumetric data, ensuring voxel-level spatial continuity. Through a teacher-student knowledge distillation mechanism, the student network learns structurally perceptual features without a tumor mask, achieving high-fidelity generation. This method can improve the overall quality of generated images and the detail fidelity of tumor lesions, thereby enhancing the performance of downstream tumor segmentation tasks and showing promising application prospects.

This application provides a method, device, terminal, and medium for simultaneous quantitative magnetic resonance imaging (MRI) of cardiac fat fraction and multiple relaxation parameters during free breathing. The method includes: scanning the cardiac tissue of a subject under free breathing conditions using an established MRI sequence corresponding to the simultaneous quantification of cardiac fat fraction and multiple relaxation parameters, obtaining dual-echo images and ECG trigger signals for each cardiac cycle at each imaging level; simulating the evolution of the magnetization vector based on the Bloch equation and the ECG trigger signal, and establishing a dictionary; performing a water-fat separation operation based on mixed multi-echo imaging on the processed dual-echo images to obtain water signal images and fat fraction maps; and obtaining a set of relaxation parameter maps of the subject by matching the water signal images with the dictionary. This application acquires data during free breathing, reducing the burden on the subject while ensuring the accuracy of fat fraction quantification and water-fat separation.

The present invention relates to the field of penetration testing security, and relates to a method for modal conversion of quantitative magnetic resonance imaging based on artificial intelligence, including data acquisition and fitting; data generation; data preprocessing; establishing a deep neural model. The present invention uses deep learning technology to achieve quantitative MRI modal conversion of conventional magnetic resonance scanning sequence modal data with arbitrary different contrasts as input. By introducing magnetic resonance sequence parameter encoding through a deep learning network, the present invention can achieve efficient conversion of conventional MRI images with arbitrary contrasts to quantitative MRI parameter maps, significantly reducing the time required for multiple scans and complex fitting calculations in traditional methods. Compared with the prior art, the acquisition efficiency of quantitative MRI data is greatly improved.

The invention relates to a computer-implemented method for angiography with a magnetic resonance device (11) in a body region (1) of a subject (2), wherein in at least one acquisition section of each section acquisition area (3, 4, 5) of the body region (1) useful magnetic resonance data are acquired by means of a magnetic resonance sequence after administration of a contrast agent, wherein at least one detection of the arrival of the contrast agent bolus in at least one detection area (7) of the subject (1) during the acquisition of useful magnetic resonance data takes place, wherein the detected arrival is used to select useful magnetic resonance data and / or to determine a time of the beginning and / or the end of at least one acquisition section.

The invention relates to a computer-implemented method for operating a magnetic resonance device (10) when recording magnetic resonance data from an area of ​​investigation of an object under investigation, wherein a magnetic resonance sequence with a saturation section (1) is used, in which saturation with respect to a spin type to be recorded is carried out in at least one first saturation region by means of a saturation radio frequency pulse (4), which is given when a saturation gradient pulse (5) is applied, characterized in that the saturation radio frequency pulse (4) is designed as a multiband pulse, with which the magnetization with respect to a second, not to be recorded, spin type is additionally saturated in at least one second saturation region.

The application relates to the field of medical image processing and discloses a multi-modal magnetic resonance aneurysm occlusion evaluation method and system. The method comprises the following steps: acquiring a scanning configuration and multi-modal magnetic resonance sequences, generating fusion image data through cross-modal registration, artifact suppression and denoising processing; then performing image segmentation, three-dimensional structure reconstruction and topology correction to obtain a three-dimensional anatomy and blood flow model; then extracting an individual feature vector through gridding, index normalization and time sequence alignment processing; finally, obtaining an occlusion mechanism score and probability based on multi-model fusion reasoning, completing three-dimensional visualization rendering, backfilling key parameters to a configuration structure, and forming a closed-loop optimization. The application effectively integrates multi-modal data, improves evaluation accuracy, and realizes adaptive optimization and result traceability of the system through parameter backfilling.

The invention relates to a computer-implemented method for operating a magnetic resonance device (20) during an acquisition process according to an acquisition protocol, which uses at least one magnetic resonance sequence in an acquisition period and comprises radio-frequency pulses (2, 4) preceding acquisition periods (3), wherein - for at least some of the high-frequency pulses (2, 4), at least one measured value is recorded in a measuring period (5) describing the reverse power reflected back by a coil element used to output the high-frequency pulses (2, 4), so that a time series (6, 7, 8, 9) of measured values is created over the recording period, - the time series (6, 7, 8, 9) of measured values for detecting an occurring movement of the recorded examination object, which is described by movement information, is evaluated in an evaluation step (S3), and - the movement information is used to control the recording process and / or in a reconstruction of an image data set from recorded magnetic resonance data, characterized in that before the evaluation step (S3), in a preprocessing step (S2), the time series (6, 7, 8, 9) is used to at least partially remove the property from the time series (6, 7, 8, 9) using at least one piece of background information which describes a non-movement-related, expected property of the time series (6, 7, 8, 9).

Method for motion compensation during magnetic resonance imaging of an object under investigation using a magnetic resonance device, wherein a magnetic resonance sequence is used for the magnetic resonance imaging, comprising the following method steps: - Performing a reference measurement at a first time point during magnetic resonance imaging, where a navigator reference volume is acquired using a simultaneous multi-slice measurement technique with a first acceleration factor and a first number of first slice groups, - Performing a navigator measurement at a second time point during magnetic resonance imaging, wherein a navigator volume is acquired using a simultaneous multi-slice measurement technique with a second acceleration factor and a second number of second slice groups, wherein the second acceleration factor is equal to the first acceleration factor, and wherein the navigator measurement is inserted into the magnetic resonance sequence used for magnetic resonance imaging. - Determining motion information from the navigator reference volume and the navigator volume, where the motion information describes a movement of the object under investigation between the first time point and the second time point, and - Setting recording parameters, which are set after the second time point for magnetic resonance imaging, depending on the motion information.

Systems and methods for creating a magnetic resonance sequence for a magnetic resonance device. The magnetic resonance sequence is described by at least one sequence parameter and provided parameter values of the sequence parameters are used for the determination of a temporal sequence pattern over time by simulation of a subsection of the magnetic resonance sequence by a simulation unit. A permissible parameter value range for at least one selected one of the sequence parameters is determined by an evaluation unit on the basis of the temporal sequence pattern and provided limitations. A new parameter value of the at least one selected parameter within the permissible parameter value range is defined by a definition unit. At least one duration limitation relating to the entire duration of the magnetic resonance sequence, or a specified time constant is provided. The temporal sequence pattern is expanded beyond the subsection by the simulation unit by repetition of the subsection, until the entire duration or the specified time constant is reached or an abort criterion relating to the duration limitation is satisfied.

A technique is provided for determining a position of a coil element of a radiofrequency coil (RF) for placement into a patient placement region of a magnetic resonance (MR) apparatus. A magnetic resonance sequence is output via a radiofrequency (RF) antenna, which is arranged inside a scanner unit of the MR apparatus, first MR data is captured via the RF antenna, and second MR data is captured via the coil element. First MR images are ascertained from the first MR data, and second MR images are ascertained from the first MR data and the second MR data. Moreover, a similarity measure is determined from the first MR images and the second MR images, and an effective range of the coil element is determined from the first MR images and the second MR images. The effective range comprises a position of the coil element of the RF coil.

A computer-implemented method for operating a magnetic resonance device, the method including: acquiring, as part of an examination process, magnetic resonance data describing diffusion and / or perfusion in a target area of a subject under examination in which an exogenous paramagnetic contrast agent is present, using a magnetic resonance sequence; and prior to at least one acquisition period in which magnetic resonance data of a dynamic data set is acquired using the magnetic resonance sequence, outputting an additional magnetic gradient field to generate a magnetic movement force that acts on the contrast agent to introduce kinetic energy into the target area, wherein the additional magnetic gradient field is output separately from pulses of the magnetic resonance sequence.

The application discloses a kind of based on magnetic resonance auxiliary ablation treatment method and device, method includes: detecting the current operation process of tumor ablation operation;When detecting preoperative simulation, scan image is obtained based on three-dimensional magnetic resonance scanning, and organ region and tumor region are segmented, to assist in generating optimal probe strategy;When detecting intraoperative navigation, real-time magnetic resonance scanning is carried out in the process of probe insertion, current magnetic resonance image is obtained, and probe tip, probe angle and tumor coordinates are identified, to assist probe to reach tumor;When detecting intraoperative thermometry, magnetic resonance sequence scanning is carried out in the process of probe ablation, multiple echo magnetic resonance image is obtained, and current temperature distribution and thermal ablation range are displayed in real time until tumor is completely inactivated.