59 results about "K-space" patented technology

The invention discloses an electromagnetic interference suppression method and system for ultra-low field magnetic resonance imaging, and belongs to the technical field of nuclear magnetic resonance, and the system comprises an electromagnetic interference signal collection module which is composed of a plurality of EMI coils and corresponding signal collectors and actively detects EMI signals from the environment; the electromagnetic interference suppression module is used for performing model training by using the data, performing electromagnetic interference suppression through a model, predicting and eliminating an EMI component based on the electromagnetic interference suppression model, and outputting k space data without EMI; and the image reconstruction module is used for receiving the EMI-free k-space data and carrying out averaging and image reconstruction on the data so as to generate a high-quality MRI image. According to the invention, EMI noise is effectively suppressed, image quality is improved, and mobile and portable development of MRI equipment is promoted.

The invention discloses a non-Cartesian magnetic resonance rapid intelligent imaging method for k-space direct learning, and relates to the technical field of medical image processing and magnetic resonance imaging, and the method comprises the steps: firstly obtaining non-Cartesian full-sampling k-space data from a magnetic resonance instrument, obtaining non-Cartesian under-sampling k-space data through combining an under-sampling operator and a zero filling operator, and carrying out the calculation of the non-Cartesian full-sampling k-space data; forming a training set; then designing a magnetic resonance fast reconstruction network based on k space direct learning non-Cartesian sampling of a graph neural network, network reasoning and loss function constraint; solving an optimal parameter set of the magnetic resonance fast reconstruction network; and finally, inputting non-Cartesian under-sampling k space data to be reconstructed into the trained magnetic resonance rapid reconstruction network to reconstruct a magnetic resonance image. According to the non-Cartesian magnetic resonance imaging method, k-space data similar feature fusion is carried out through the graph neural network, and under-sampling k-space missing point direct filling learning is carried out through the convolutional network, so that rapid and low-error non-Cartesian magnetic resonance intelligent image reconstruction is realized.

The invention relates to a magnetic resonance imaging method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring under-sampling K space data of an imaging object; determining an initial reconstruction image based on the under-sampled K space data; the initial reconstruction image is input into a trained correction model, an intermediate reconstruction image is obtained based on the output of the correction model, and the output of the correction model is the deviation between the initial reconstruction image and a full-sampling reconstruction image; and performing distortion correction on the intermediate reconstructed image based on the under-sampled K space data to obtain a target reconstructed image. According to the invention, the quality of the target reconstructed image is effectively improved while the image reconstruction speed is improved.

The invention discloses a multi-contrast magnetic resonance image reconstruction method and device based on detail contour feature perception. The method comprises the following steps: acquiring a target modal initial image and an auxiliary modal initial image; constructing an iterative network formed by alternately cascading image domain reconstruction units and data consistency layers, wherein each image domain reconstruction unit comprises an encoder and a decoder; in the first iteration, target modal initial images and auxiliary modal initial images are spliced and then input, an encoder extracts shared features firstly, then global contour features and high-frequency detail features are separated in parallel, and potential features are obtained through collaborative fusion; the decoder takes the potential features as input and outputs an image domain preliminary reconstruction result; the data consistency layer transforms the preliminary result into a k space, performs consistency correction on the preliminary result and a target modal sampling point, and then inversely transforms the preliminary result back to an image domain to complete one iteration; and splicing the current output and the auxiliary modal initial image again, inputting the spliced image into a next round of iteration, and repeating the process until a preset number of times to obtain a final target modal magnetic resonance image.

The invention provides a medical magnetic resonance image reconstruction method and system, and belongs to the technical field of image reconstruction, and the method comprises the steps: obtaining sampling coding and under-sampling k space data; processing the under-sampled k space data through inverse Fourier transform, and converting the k space data into an image domain to obtain under-sampled image data with blurring or artifacts; carrying out preliminary restoration on the undersampled image data based on sampling coding, further applying data consistency operation on the image to obtain a rough image, and taking the rough image as an image condition vector after underspace coding; acquiring a text serving as a cue word, inputting the text into a text encoder, and encoding the text into a high-dimensional semantic embedding vector by the text encoder; and inputting the high-dimensional semantic embedding vector and the image condition vector into a reconstruction model based on the correction flow to predict a full-sampling MRI image, and generating a final reconstructed MRI image.

A line-field optical coherence tomography (OCT) system and method provide enhanced imaging accuracy through k-linearization of interference data. The system includes a swept laser source, a line-field sensor, and a single board computer (SBC) with processing capabilities. The system uses a frequency reference to produce a periodic reference pattern, which is detected by a subset of pixels in the line-field sensor. The SBC determines a resampling curve based on the reference pattern to correct non-linearities in the wavelength tuning of the laser. The resampling curve is applied to k-linearize the interference data, enabling the generation of high resolution transform-limited depth profiles through inverse Fourier transform. Methods are disclosed for recalculating the resampling curve periodically, continuously, or adaptively based on a linearity threshold. The system can further update the laser's tuning function dynamically to ensure consistent performance. These advancements enable precise and efficient OCT imaging for applications such as ophthalmology, angiography, and other diagnostic uses.

The invention provides a magnetic resonance free respiration data extraction method based on a respiratory wave extraction algorithm, and relates to the technical field of respiration acquisition, and the method comprises the following steps: obtaining a rapid imaging sequence, and extracting a complex number sampling value of a center k space line of the rapid imaging sequence in a z direction as an initial input signal; performing z-direction IFFT interpolation processing on the initial input signal to output a high-resolution z-t signal matrix; performing time dimension signal smoothing processing on the high-resolution z-t signal matrix; performing normalization processing on the z-axis signal at each time point based on a smoothing processing result; the z-axis signals of all the channels are spliced along the longitudinal axis according to the normalization processing result to form a unified matrix; the unified matrix is subjected to standard PCA decomposition, and principal components of the unified matrix are extracted to obtain respiratory wave data; according to the method, the breathing signal waveform can be stably extracted from the MRI original k space in the free breathing state without depending on the breath holding condition, and the structure consistency and time synchronism of breathing waves are improved.

The invention relates to a magnetic resonance image reconstruction method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a K space data set of a plurality of phases of at least one layer of a detection object, wherein the K space data set of the at least one layer is under-sampled; performing weighted combination on the K space data sets of the plurality of phase phases to generate a synthesized K space data set, and generating a coil sensitivity distribution diagram according to the synthesized K space data set; performing initialization reconstruction on the K space data sets of the plurality of phases to obtain initial dynamic magnetic resonance images; performing machine learning-based iterative reconstruction on the initial dynamic magnetic resonance image to obtain a dynamic magnetic resonance image of the detected object; an iterative reconstruction of machine learning includes a coincidence term generated based on a K-space dataset of multiple phase phases and a coil sensitivity profile. By adopting the method, the reconstruction quality of the magnetic resonance image can be improved.

The invention discloses an adaptive total variation weight magnetic resonance image reconstruction method based on a local structure and global information measurement, and the method comprises the steps: 1, obtaining under-sampling k space data K (x, y); step 2, establishing a CS-MRI reconstruction model; step 3, initializing adaptive TV regularization weight optimization; 4, calculating local structure information measurement; 5, calculating global information measurement; step 6, calculating a self-adaptive TV regularization weight; 7, optimizing the reconstruction model; 8, reconstructing a final image; and step 9, evaluating and optimizing. Through the above steps, the method significantly improves the quality of the image reconstructed by CS-MRI through the self-adaptive adjustment of the TV regularization weight in combination with the local structure and global information measurement, and provides higher fidelity and robustness for clinical application.

The invention discloses a parallel MRI (Magnetic Resonance Imaging) reconstruction method based on a scanning specific triple attention improved residual network, and belongs to the field of MRI imaging. And acquiring full-sampling multi-coil k-space data, and performing multiple operations on the full-sampling multi-coil k-space data to obtain under-sampling multi-coil k-space data. Designing a specific triple attention improved residual parallel MRI reconstruction network (SS-TARNet) based on scanning, wherein the SS-TARNet is a reconstruction network model with adaptive and multi-scale feature extraction; constructing a mixed loss function of the reconstructed network model; solving the optimal parameters of the reconstructed network model by using the training set, the verification set and the mixed loss function; and for the test set, performing MRI image reconstruction by using the optimal parameters of the reconstruction network model to obtain a reconstructed image. The final reconstruction result is amplitude fusion of the sum. According to the method, the reconstruction results obtained by the two different networks are uniquely utilized to perform amplitude fusion output, and a better reconstruction effect is obtained, so that the reconstruction performance in the under-sampling MRI scene is greatly improved.

The invention discloses a magnetic resonance fingerprint reconstruction method based on a double-domain geometric structure and spatial prior depth expansion, and relates to the technical field of magnetic resonance fingerprint imaging. The method comprises the following steps: (1) acquiring magnetic resonance fingerprint undersampling k space data; (2) establishing a magnetic resonance fingerprint reconstruction model based on fingerprint domain manifold structure prior and tissue characteristic domain sparse prior; (3) iteratively solving the reconstruction model by using a dominant minimization and near-end gradient algorithm; (4) adopting an effective strategy to obtain a closed-form solution of a near-end mapping sub-problem, and expanding all iteration steps to the deep neural network; (5) training the network by using the existing data to obtain a network model; and (6) reconstructing magnetic resonance fingerprints and various tissue parameter diagrams by using the trained network. According to the method, the structured geometric information of the fingerprint data and the spatial characteristics of the organization parameter diagram are fully utilized by expanding the network, and an excellent reconstruction effect can be presented under the condition of high-power undersampling of the data.

The invention discloses a full-space switchable nanoimprint and holographic display method based on a metasurface, and belongs to the field of micro-nano optics and holographic display. According to the metasurface-based full-space switchable nanoimprint and holographic display method, the metasurface used for achieving full-space switchable nanoimprint and holographic display is composed of nano antennas of different geometric dimensions, and the geometric dimensions and the arrangement mode of the metasurface are determined through an amplitude constrained phase holographic optimization algorithm; the amplitude distribution of the light field passing through the metasurface is restrained into binary image distribution in a real space, and holographic reconstruction is carried out in a wave vector k space. According to the sensitivity of the metasurface to the wavelength of incident light, three different optical modulation modes are realized under three wavelengths; the wavelength sensitivity of the metasurface is utilized to modulate a reflected light beam and a transmitted light beam under different incident light wavelengths, so that full-space switchable nanoimprint and holographic display are realized, and the metasurface can be applied to the fields of optical nanoimprint, counterfeiting prevention, optical switches, optical communication, display and the like.

The application discloses a kind of low field intensity magnetic susceptibility weighted imaging optimization method and system, it is related to magnetic susceptibility weighted imaging field, comprising: obtaining the K space original data obtained by scanning target object;According to K space original data reconstruction image field data, extract the amplitude data and phase data of image field data;Phase data is preliminary unwrapping processing, and unwrapping phase data is obtained;Unwrapping phase data is separated from background field, and local phase diagram is obtained;Local phase diagram and amplitude data are operated based on complex domain phase separation high-pass filter, and high-frequency phase data is obtained;According to high-frequency phase data and amplitude data, the reconstruction of magnetic susceptibility weighted image is carried out, and the magnetic susceptibility weighted image of target object is obtained.The application can significantly reduce the phase artifact of SWI image, and improve the definition of image detail.

The invention provides a respiratory-gating-free free-breathing liver glycogen quantitative magnetic resonance imaging method and system, and the method comprises the steps: applying a chemical exchange saturation transfer imaging sequence to a liver region of a subject, and the imaging sequence comprises saturation pulses of a plurality of saturation frequency deviation points; a radial blade type k-space acquisition strategy is adopted to acquire magnetic resonance signal data, the radial blade type k-space acquisition strategy comprises a plurality of blades, each blade is composed of a group of parallel k-space lines, and different blades are rotationally distributed by taking the k-space center as a rotating shaft; performing image reconstruction on the acquired k space data to obtain magnetic resonance images under different saturation frequency deviations; and performing fitting analysis on the magnetic resonance image by adopting a multi-pool Lorentz model to obtain quantitative information of the liver glycogen. According to the method, the interference of respiratory movement on the CESTMRI data acquisition process can be eliminated, so that the accurate quantification of the liver glycogen in the free respiration state is realized.

The invention relates to a magnetic resonance image processing method and device, and an EPI-based image processing method. The method comprises the steps of obtaining a first sampling image of a target object according to sensitivity information of a receiving coil corresponding to the target object and K space data; correcting artifacts in the first sampling image to obtain a second sampling image of the target object; and iterating data of a preset first magnetic resonance image by taking the second sampling image as a constraint condition and taking the K space data as a fidelity term in an iterative reconstruction process to obtain a magnetic resonance image of the target object. By adopting the method, the problem of aliasing artifacts existing in magnetic resonance imaging images can be solved.

The invention provides an ultra-low field multi-core synchronous magnetic resonance imaging method. The method comprises the following steps: improving a longitudinal magnetization vector of each pre-imaging nuclide in an ultra-low field; performing space coding and signal acquisition on each pre-imaging nuclide to obtain a K space signal set corresponding to an imaging nuclide plane; obtaining total K space data corresponding to the K space signal set, and performing zero filling on the total K space data; based on the total K space data after zero filling, obtaining total frequency distribution corresponding to an imaging nuclide plane; splitting the total frequency distribution to obtain sub-frequency distribution corresponding to each type of pre-imaging nuclide; obtaining sub-K space data corresponding to various pre-imaging nuclides based on the sub-frequency distribution; and based on the sub-K space data, image reconstruction is carried out on the various pre-imaging nuclides, and reconstructed images corresponding to the various pre-imaging nuclides are obtained. According to the method provided by the invention, multi-nuclide synchronous magnetic resonance imaging in an extremely low field can be realized, and the image quality of multi-nuclear magnetic resonance imaging is improved.

The invention discloses a method, a device, equipment and a product for reconstructing a spatially selective core measurement image, which comprises the following steps of: acquiring k-space data of a core to be measured by using a k-space radial sampling mode, and then, acquiring the k-space data of the core to be measured by using the k-space data; constructing an image model based on the image of the rock core to be measured, the k-space data and the contour data of each spoke in the k-space data; then, image reconstruction can be carried out based on the image model, so that in the image reconstruction process, the adverse effect of the contour data of each spoke in the k space data on rock core imaging is eliminated, and the optimal image of the rock core to be measured is obtained; and finally, based on this, obtaining a corresponding spatial selective core measurement image. Therefore, the image reconstruction is realized by utilizing an algorithm, and compared with the traditional technology, the method does not need to change hardware, is high in feasibility, and can greatly reduce the influence of profi on the image quality, so that the image reconstruction quality can be remarkably improved.

The invention is suitable for the technical field of magnetic resonance chemical exchange saturation transfer imaging, and provides a magnetic resonance chemical exchange saturation transfer imaging method, device, equipment, product and storage medium. A gradient echo sequence is adopted to collect saturated water molecule signals, and the collected water molecule signals are stored in a K space; and wave control coding is introduced in the acquisition process, and a CEST image is reconstructed based on a water molecule signal of a K space. The introduction of wave control coding can reduce the scanning time. Due to the fact that the wave control coding sampling efficiency is high, a larger matrix size can be supported within the same time, high-resolution imaging is achieved, the partial volume effect can be relieved, and CEST quantitative accuracy is improved.

The present disclosure provides a system and method for magnetic resonance imaging. The method may include obtaining a first set of imaging data, the first set of imaging data being sampled in multiple shots, each shot of the multiple shots corresponding to a plurality of echo times, the first set of imaging data including partially sampled data in a first k space; obtaining a second set of imaging data, the second set of imaging data including fully sampled data in a central region of a second k space; determining fitting data in the first k space based on the first set of imaging data and the second set of imaging data; and / or generating a target image based on the fitting data in the first k space and the first set of imaging data in the first k space.

The invention relates to a system and a method for K-space neutron space parallel imaging. A computer-implemented method includes obtaining, via a processing system including one or more processors, multichannel k-space data of a subject acquired with a magnetic resonance imaging scanner. The computer-implemented method further includes combining, via the processing system, information from locally adjacent k-space locations and across a plurality of channels using a subspace convolution kernel on the multi-channel k-space data to generate subspace compressed k-space data, the subspace compressed k-space data has fewer channels than the number of channels used to collect the multi-channel k-space data.

The application provides a small animal sciatic nerve magnetic resonance coil and an imaging method, and the method comprises the following steps: filling a high-concentration sugar syrup solution at the bottom of the magnetic resonance coil and performing constant temperature control; placing a small animal in a prone position in the high-concentration sugar syrup solution and discharging air in the gap between the lower limbs and below the abdomen of the small animal; after performing magnetic resonance positioning scanning to determine the main sequence scanning range, starting the main sequence scanning, suppressing the flow tissue signal through a pre-pulse combination, exciting the tissue by using a radio frequency pulse with preset parameters, acquiring echo signals by combining a fast spin echo technology and filling K space, and obtaining scanning original data; performing preprocessing on the scanning original data and accurate segmentation of the sciatic nerve and spinal nerve to obtain a segmentation result; and completing three-dimensional model reconstruction, optimization and multi-modal fusion visualization based on the segmentation result to obtain an image scanning result. The application is suitable for small animals, is accurate in imaging, can effectively suppress various kinds of artifacts, and can be widely applied to sciatic nerve imaging scenarios of small animals.

The embodiment of the invention discloses an under-sampling point recovery method and device in magnetic resonance imaging and a magnetic resonance imaging system. The method comprises the following steps: in the process of performing magnetic resonance scanning on an imaging target by adopting a multi-echo data imaging merging sequence, acquiring magnetic resonance signals of echoes of channels in an undersampling mode, and putting the acquired magnetic resonance signals of the echoes of the channels into K spaces of the echoes of the channels respectively, each channel has a plurality of echoes, and each echo of each channel corresponds to a K space; and for an under-sampling point in the K space of a specified echo of a specified channel of the imaging target, recovering the under-sampling point by adopting the magnetic resonance signals in the K spaces of the echoes of all channels and the magnetic resonance signals in the K spaces of other echoes of the specified channel. According to the embodiment of the invention, the under-sampling point recovery accuracy during MR imaging by adopting the MEDIC sequence is improved.

Embodiments of the present application disclose a multi-echo data magnetic resonance imaging scanning method, device and magnetic resonance imaging system. The method comprises: in the process of multi-echo data magnetic resonance imaging scanning on an imaging target, if automatic calibration data needs to be collected in the current repetition time, and the position of the automatic calibration data in K space is inconsistent with the position of any imaging data in K space which needs to be collected in the current repetition time, then: when the plateau signal of the first readout gradient in the readout direction is applied, start to apply an offset gradient in the phase encoding direction, wherein the first readout gradient is any readout gradient in the readout direction except the last readout gradient; and during the application of the plateau signal of the dephasing gradient of the first readout gradient in the readout direction, the automatic calibration data is collected. Embodiments of the present application avoid TR oscillation in multi-echo data MR imaging scanning, and realize the continuity of the collected automatic calibration data and imaging data.

The invention relates to a plane echo imaging method and system, computer equipment and a storage medium, and the method comprises the steps: obtaining a K-space data set obtained after the radio frequency excitation of a to-be-imaged region, the K-space data set comprising an echo time dimension, the K space data set is under-sampled along at least one phase coding direction and echo time dimension; recovering the K space data set along at least one phase coding direction and echo time dimension to obtain an updated K space data set; and reconstructing according to the updated K space data set to obtain a plurality of plane echo images. According to the method and the device, the problem that plane echo imaging cannot give consideration to improvement of the signal-to-noise ratio, the robustness and the calculation speed of the image in related technologies is solved, and the signal-to-noise ratio, the robustness and the calculation speed of the plane echo imaging are comprehensively improved.

The invention discloses a self-supervised parallel MRI (Magnetic Resonance Imaging) reconstruction method based on a deep double-domain fusion network. The method comprises the following steps: constructing an up-down parallel comparison network based on the deep double-domain fusion network; in the training stage, simulation enhancement and re-undersampling are carried out based on an original sampling mask, a re-undersampling mask pair is generated, and comparison and re-undersampling k space data are obtained; respectively inputting the two paths of data into a parallel comparison network for comparison self-supervision training; a mixed loss function of the network comprises image domain calibration loss, symmetry constraint loss and projection prediction comparison loss, and network parameters are optimized under the condition of no full sampling reference image to obtain a trained model. According to the method, the reconstruction quality can be improved and the artifact noise can be suppressed without full sampling labeling, the generalization of cross-mask and cross-acceleration factors is enhanced, and the data acquisition, training and deployment maintenance cost is reduced.

The invention discloses a reconfigurable magnetic resonance image reconstruction system and a dynamic control method thereof. The system comprises an input adapter, a module manager, a pipeline manager, an execution engine, a plurality of processing modules and an output adapter. According to the system, registration and instantiation of the processing modules are achieved through the module manager, declarative configuration files are analyzed through the assembly line manager to construct an execution topology, a unified data container is dynamically scheduled through an execution engine according to the topology to flow through all the processing modules, and the reconstruction process from k space data to diagnostic images is completed. According to the system and the dynamic control method thereof, flexible recombination of the reconstruction process and dynamic control during operation are achieved, the problems that in the prior art, the process is rigid, expansion is difficult, and cross-language compatibility is insufficient are solved, and adaptability, expandability and reconstruction efficiency of the system are remarkably improved.

The application discloses a kind of quantitative magnetic susceptibility imaging method and device based on radial sampling, comprising: by magnetic resonance scanner executes three-dimensional gradient echo multi-echo sequence, and the three-dimensional k space multi-echo data of tissue is collected in radial sampling mode;The three-dimensional k space multi-echo data collected is corrected and density is compensated to obtain the three-dimensional k space multi-echo data and corrected track RT after track correction and density compensation;The three-dimensional k space multi-echo data and corrected track RT after track correction and density compensation are input into non-uniform fast Fourier transform reconstruction complex image, to obtain corresponding amplitude diagram and phase diagram;Phase diagram is unwound and background field is removed, to obtain corresponding local field;By improved sparse linear equation and least square method ILSQR algorithm inversion local field, corresponding magnetic susceptibility distribution diagram is generated.The method and device of the application reduce the influence of motion artifact, improve imaging quality and diagnostic accuracy.

The present application relates to a kind of wideband omni-directional completely transparent system and its application of torsion structure implementation, the system includes several first structure and second structure connected alternately, the first structure rotates set angle in Z axis direction towards clockwise direction, the second structure rotates set angle in Z axis direction towards counterclockwise direction;The first structure and the second structure all include several first structure layer and second structure layer, which are arranged in up-down overlap along X axis direction;The omni-directional completely transparent system meets the following zero shift condition.The system of the present application realizes the rotation of IFCs (Iso-frequency curves, equal frequency curve) in k space by twisting by multiple layers of alternatingly arranged dielectric materials, and realizes wideband OPT under zero reflection condition.

The invention discloses a method and a device for identifying and eliminating low-frequency strong interference noise of a magnetic resonance system, which are characterized in that after being processed by a conventional self-adaptive noise reduction method, signals in a k space which is not influenced by low-frequency strong EMI (Electro-Magnetic Interference) along frequency and phase encoding directions are smooth, and the low-frequency strong EMI is discontinuous in the phase encoding direction, so that the low-frequency strong interference noise can be identified and eliminated. According to the characteristic that the signal is in a peak shape in time sequence, low-frequency strong EMI post-processing identification and elimination are carried out on the signal after self-adaptive noise reduction; therefore, the low-frequency strong interference noise in the nuclear magnetic resonance signal can be removed, so that the quality of nuclear magnetic resonance imaging is improved; therefore, the method is very suitable for large-scale application and popularization in the field of ultra-low field nuclear magnetic resonance.

The application relates to a parallel emission local excitation pulse generation method, device and storage medium, the method comprising: generating a radio frequency pulse according to a three-dimensional mapping of a test object and a three-dimensional excitation K space; calculating excitation uniformity according to the three-dimensional mapping, the three-dimensional excitation K space and the radio frequency pulse; when the excitation uniformity is less than a preset value, updating the three-dimensional mapping and the three-dimensional excitation K space used for generating the radio frequency pulse and for calculating the excitation uniformity; when the excitation uniformity is greater than or equal to the preset value, generating the parallel emission local excitation pulse according to the three-dimensional excitation K space and the radio frequency pulse currently used for calculating the excitation uniformity. Through the application, the problem that the radio frequency pulse duration is long in the prior art is solved, the local excitation position uniformity in the expected magnetic resonance emission field is achieved, and the radio frequency pulse length is shortened.