126 results about "Coil sensitivity" patented technology

A magnetic resonance (MR) imaging apparatus and technique exploits spatial information inherent in a surface coil array to increase MR image acquisition speed, resolution and / or field of view. Magnetic resonance response signals are acquired simultaneously in the component coils of the array and, using an autocalibration procedure, are formed into two or more signals to fill a corresponding number of lines in the signal measurement data matrix. In a Fourier embodiment, lines of the k-space matrix required for image production are formed using a set of separate, preferably linear combinations of the component coil signals to substitute for spatial modulations normally produced by phase encoding gradients. One or a few additional gradients are applied to acquire autocalibration (ACS) signals extending elsewhere in the data space, and the measured signals are fitted to the ACS signals to develop weights or coefficients for filling additional lines of the matrix from each measurement set. The ACS lines may be taken offset from or in a different orientation than the measured signals, for example, between or across the measured lines. Furthermore, they may be acquired at different positions in k-space, may be performed at times before, during or after the principal imaging sequence, and may be selectively acquired to optimized the fitting for a particular tissue region or feature size. The in vivo fitting procedure is readily automated or implemented in hardware, and produces an enhancement of image speed and / or quality even in highly heterogeneous tissue. A dedicated coil assembly automatically performs the calibration procedure and applies it to measured lines to produce multiple correctly spaced output signals. One application of the internal calibration technique to a subencoding imaging process applies the ACS in the central region of a sparse set of measured signals to quickly form a full FOV low resolution image. The full FOV image is then used to determine coil sensitivity related information and dealias folded images produced from the sparse set.

A method of correcting for motion in magnetic resonance images of an object detected by a plurality of signal receiver coils comprising the steps of acquiring a plurality of image signals with the plurality of receiver coils, determining motion between sequential image signals relative to a reference, applying rotation and translation to image signals to align image signals with the reference, determining altered coil sensitivities due to object movement during image signal acquisition, and employing parallel imaging reconstruction of the rotated and translated image signals using the altered coil sensitivities in order to compensate for undersampling in k-space.

Methods and systems in a parallel magnetic resonance imaging (MRI) system utilize sensitivity-encoded MRI data acquired from multiple receiver coils together with spatially dependent receiver coil sensitivities to generate MRI images. The acquired MRI data forms a reduced MRI data set that is undersampled in at least a phase-encoding direction in a frequency domain. The acquired MRI data and auto-calibration signal data are used to determine reconstruction coefficients for each receiver coil using a weighted or a robust least squares method. The reconstruction coefficients vary spatially with respect to at least the spatial coordinate that is orthogonal to the undersampled, phase-encoding direction(s) (e.g., a frequency encoding direction). Values for unacquired MRI data are determined by linearly combining the reconstruction coefficients with the acquired MRI data within neighborhoods in the frequency domain that depend on imaging geometry, coil sensitivity characteristics, and the undersampling factor of the acquired MRI data. An MRI image is determined from the reconstructed unacquired data and the acquired MRI data.

A system and method for mapping the sensitivity of MR coils includes a neural network or other computer intelligence trained from sample MR data to determine coil sensitivity profiles or sensitivity normalizations. Once the network is trained, subsequent coil mapping determinations may include fewer mapping acquisitions per coil. The resulting sensitivity map can be used in compensating for B1 inhomogeneities, parallel imaging reconstruction, generating tailored excitation currents for each individual coil, RF shimming, or other processes.

A phase labeling using sensitivity encoding system and method for correcting geometric distortion caused by magnetic field inhomogeneity in echo planar imaging (EPI) uses local phase shifts derived directly from the EPI measurement itself, without the need for extra field map scans or coil sensitivity maps. The system and method employs parallel imaging and k-space trajectory modification to produce multiple images from a single acquisition. The EPI measurement is also used to derive sensitivity maps for parallel imaging reconstruction. The derived phase shifts are retrospectively applied to the EPI measurement for correction of geometric distortion in the measurement itself.

In a method for magnetic resonance imaging on the basis of a partially-parallel acquisition (PPA) reconstruction method and a magnetic resonance tomography apparatus, data for at least two two-dimensional slices of a patient are acquired (which two-dimensional slices are displaced in the direction of a slice-selection gradient (z-gradients) defining the slice-normal direction) with at least one data acquisition in k-space (which acquisition forms a partial data set) per slice with a number of component coils, with the sum of all partial data sets forming a complete data set in k-space. The coil sensitivities of each component coil are determined on the basis of the complete data set. At least one partial data set of each slice is completed with a PPA reconstruction method on the basis of the determined coil sensitivities. The completed slices in k-space are transformed into whole images in the spatial domain.

A method for accelerating data acquisition in MRI with N-dimensional spatial encoding has a first method step in which a transverse magnetization within an imaged object volume is prepared having a non-linear phase distribution. Primary spatial encoding is thereby effected through application of switched magnetic fields. Two or more RF receivers are used to simultaneously record MR signals originating from the imaged object volume, wherein, for each RF receiver, an N-dimensional data matrix is recorded which is undersampled by a factor Ri per selected k-space direction. Data points belonging to a k-space matrix which were not recoded by a selected acquisition schema are reconstructed using a parallel imaging method, wherein reference information concerning receiver coil sensitivities is extracted from a phase-scrambled reconstruction of the undersampled data matrix. The method generates a high-resolution image free of artifacts in a time-efficient manner by improving data sampling efficiency and thereby reducing overall data acquisition time.

A computer program product (1344, 1346, 1348) comprising machine executable instructions for performing a method of acquiring a magnetic resonance image (1342), the method comprising the steps of: acquiring (100, 200, 300) a set of coil array data (1334) of an imaging volume (1304) using a coil array (1314), wherein the set of coil array data comprises coil element data acquired for each antenna element (1316) of the coil array; acquiring (102, 202, 302) body coil data (1336) of the imaging volume with a body coil (1318), wherein the body coil data and / or the array coil data is sub-sampled; reconstructing (104, 204, 206, 304, 306, 308) a set of coil sensitivity maps (1338) using the set of coil array data and the body coil data, wherein there is a coil sensitivity map for each antenna element of the coil array; acquiring (106, 208, 310) magnetic resonance imaging data (1340) of the imaging volume using a parallel imaging method (1332); and reconstructing (108, 210, 312) the magnetic resonance image using the magnetic resonance imaging data and the set of coil sensitivity maps.

SENSitivity Encoding (SENSE) has demonstrated potential for significant scan time reduction using multiple receiver channels. SENSE reconstruction algorithms for non-uniformly sampled data proposed to date require relatively high computational demands. A Projection Onto Convex Sets (POCS)-based SENSE reconstruction method (POCSENSE) has been recently proposed as an efficient reconstruction technique in rectilinear sampling schemes. POCSENSE is an iterative algorithm with a few constraints imposed on the acquired data sets at each iteration. Although POCSENSE can be readily performed on rectilinearly acquired k-space data, it is difficult to apply to non-uniformly acquired k-space data. Iterative Next Neighbor re-Gridding (INNG) algorithm is a recently proposed new reconstruction method for non-uniformly sampled k-space data. The POCSENSE algorithm can be extended to non-rectilinear sampling schemes by using the INNG algorithm. The resulting algorithm (POCSENSINNG) is an efficient SENSE reconstruction algorithm for non-uniformly sampled k-space data, taking into account coil sensitivities.

Various methods and systems are provided for reconstructing magnetic resonance images from accelerated magnetic resonance imaging (MM) data. In one embodiment, a method for reconstructing a magnetic resonance (MR) image includes: estimating multiple sets of coil sensitivity maps from undersampled k-space data, the undersampled k-space data acquired by a multi-coil radio frequency (RF) receiver array; reconstructing multiple initial images using the undersampled k-space data and the estimated multiple sets of coil sensitivity maps; iteratively reconstructing, with a trained deep neural network, multiple images by using the initial images and the multiple sets of coil sensitivity maps to generate multiple final images, each of the multiple images corresponding to a different set of the multiple sets of sensitivity maps; and combining the multiple final images output from the trained deep neural network to generate the MR image.

In a method and apparatus for magnetic resonance imaging based on a partially parallel acquisition (PPA) reconstruction technique, a number of partial k-space data sets are acquired with a number of component coils, the totality of the partial data sets forming a complete k-space data set, the respective coil sensitivity of each component coil is determined based on at least one part of the complete k-space data set, any partial k-space data set is transformed via a PPA reconstruction technique dependent on the determined coil sensitivities, and the transformed partial data sets are superimposed to obtain a low-artifact image data set.

The embodiment of the invention provides a nuclear magnetic resonance imaging method and device. The method comprises a step of collecting data of multiple groups of different contrast images at a same scanning position, a step of carrying out undersampling on the data of each group of contrast images at a phase direction periphery and carrying out full sampling at a self calibration signal line in a k space, and obtaining sampling data, a step of taking coil sensitivity information as sharing information of each group of images in multiple groups of different contrast images, and forming a reconstruction data matrix by the coil sensitivity information and the to-be-reconstructed information of the multiple groups of different contrast images, a step of taking the sampling data and coil sensitivity smoothing information as input data, taking the reconstruction data matrix as an output, and forming a target function for solving the coil sensitivity information and the to-be-reconstructed information of the multiple groups of different contrast images, and a step of using a nonlinear iterative method to solve the target function, reconstructing the multiple groups of different contrast images, and calculating the coil sensitivity information.