41 results about "Sensitivity encoding" patented technology

The present invention includes a method for parallel magnetic resonance imaging termed Superresolution Sensitivity Encoding (SURE-SENSE) and its application to functional and spectroscopic magnetic resonance imaging. SURE-SENSE acceleration is performed by acquiring only the central region of k-space instead of increasing the sampling distance over the complete k-space matrix and reconstruction is explicitly based on intra-voxel coil sensitivity variation. SURE-SENSE image reconstruction is formulated as a superresolution imaging problem where a collection of low resolution images acquired with multiple receiver coils are combined into a single image with higher spatial resolution using coil sensitivity maps acquired with high spatial resolution. The effective acceleration of conventional gradient encoding is given by the gain in spatial resolution Since SURE-SENSE is an ill-posed inverse problem, Tikhonov regularization is employed to control noise amplification. Unlike standard SENSE, SURE-SENSE allows acceleration along all encoding directions.

An ultra-low magnetic field NMR system can non-invasively examine containers. Database matching techniques can then identify hazardous materials within the containers. Ultra-low field NMR systems are ideal for this purpose because they do not require large powerful magnets and because they can examine materials enclosed in conductive shells such as lead shells. The NMR examination technique can be combined with ultra-low field NMR imaging, where an NMR image is obtained and analyzed to identify target volumes. Spatial sensitivity encoding can also be used to identify target volumes. After the target volumes are identified the NMR measurement technique can be used to identify their contents.

For the purpose of changing the geometry of and spacing between loop coils incorporated into an RF coil without moving the RF coil, a first plurality of loops having a geometry optimized for a square sum method employing a phased array, and a second plurality of small loops having a geometry optimized for a sensitivity encoding method are switched by switching elements for an open/close operation using a diode, and at the same time, a first decoupling means and a second decoupling means are switched. Thus, an operator is not required to replace the RF coil positioned on a cradle, and the first plurality of loops for the square sum method employing a phased array and the second plurality of small loops for the sensitivity encoding method can be switched by electronic switching and can be used as RF coils.

A parallel magnetic resonance imaging (MRI) apparatus configurable to image a physical entity comprises: a main magnetic flux source for providing a uniform fixed magnetic field, Balpha; an RF array system comprising a plurality of RF coils and receivers, said RF system configured for: generating rotating RF excitation magnetic fields B1; and receiving RF signals due to precessing nuclear magnetization on multiple spatially distinct radio frequency coils and associated receiver channels, said RF system being configured to operate in accordance with a B1 sensitivity encoding technique; a control processor for controlling imaging functionality, collecting image data and effecting data processing of the captured image data the control processor being configured with post processing capability for the B1 sensitivity encoding technique; an image display means for displaying processed image data as resultant images; and an auxiliary magnetic field means capable of producing at least one auxiliary uniform Bo step magnetic field imaging region within the main B0 magnetic field; wherein: the auxiliary magnetic field, means is configured to operate in combination with the RF coil system and the B1 sensitivity encoding technique, the imaging apparatus thereby providing faster image acquisition than that attributed to the speed up factor provided solely by the B1 sensitivity encoding technique. The invention also includes a method of imaging using this apparatus. Furthermore, the invention also includes a method and apparatus for three-dimensional MR imaging using a 1D Multiple Acquisition Micro Bo array coupled with a 2D Multiple Acquisition Micro Bo array.

In a K-space SENSitivity Encoding (KSENSE) magnetic resonance parallel imaging method the sensitivity distribution of MR reception coils; is calculated and based on the sensitivity of the coils, signals from the respective coil merging channels are merged. The merged data are used to perform k-space data fitting and optimal fitting parameters are found. The fitting parameters are used to remove artifacts in the reconstructed image. The KSENSE method, compared to SENSE, mSENSE and GRAPPA, has the advantages of the image reconstructed by KSENSE having an optimized signal-to-noise ratio (SNR) that is superior to that of an image reconstructed by GRAPPA under the same conditions and approximates that when mSENSE is used, and an image reconstructed by KSENSE has relatively low residual artifacts and an artifact intensity, as a whole, that is superior to that of an image reconstructed by SENSE or the like under the same conditions and equivalent to that when GRAPPA is used, and, compared to GRAPPA that also performs operations in k-space, KSENSE has a higher reconstruction speed.

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.

The present invention provides a system and method for using a hardware-based compression of signals acquired with an magnetic resonance imaging (MRI) system. This allows a first multi-channel MR signal to be compressed to a second multi-channel MR signal having fewer channels than the first MR signal. This system and method reduces the number of RF receivers needed to achieve the sensitivity encoding benefits associated with highly parallel detection in MRI. Furthermore, the system and method reduces bottlenecks connection an MRI system's RF receiver and reconstruction computer and reduces the computational burden of image reconstruction.

The pursuit for ever higher field strengths and faster data acquisitions has led to the construction of coil arrays with high numbers of elements. With the SENSE technique it has been shown, how the sensitivity of those elements can be used for spatial image encoding. A method in accordance with the present invention, largely abstains from using encoding gradients. The resulting sensitivity encoded free induction decay (FID) data is then not used for imaging, but for determining field inhomogeneity distribution. The method has therefore been termed SSH for Sense SHimming.

Diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI) using a new technique, termed multiplexed sensitivity encoding with inherent phase correction, is proposed and implemented to effectively and reliably provide high-resolution segmented DWI and DTI, where shot-to-shot phase variations are inherently corrected, with high quality and SNR yet without relying on reference and navigator echoes. The performance and consistency of the new technique in enabling high-quality DWI and DTI are confirmed experimentally in healthy adult volunteers on 3 Tesla MRI systems. This newly developed technique should be broadly applicable in neuroscience investigations of brain structure and function.

For a purpose of improving homogeneity of an image obtained in a self-calibration by a parallel imaging method generally referred to as SENSE (SENSitivity Encoding), sensitivity factors S_n(p) are calculated using an additive image A_b=Σ|C_n| of complex images C_n obtained by conducting a calibration scan of an entire FOV for phased array coils Coil_n (n=1–N, N≧2) (Steps V2, V3). Moreover, sensitivity maps S_n are generated by conducting curve fitting by the method of least squares weighted by the square of a pixel value A_b(p) of the absolute value additive image A_b (Step V4).

The invention relates to a magnetic resonance imaging method and a magnetic resonance imaging device. The magnetic resonance imaging method comprises the following steps: generating a plurality of K space diagrams on the basis of magnetic resonance sensation signals which are arranged in a parallel manner; according to the plurality of K space diagrams, reconstructing a first sub-image corresponding to a reading gradient pulse in a first direction, and a second sub-image corresponding to a reading gradient pulse in a second direction; calculating the phase difference between the first sub-image and the second sub-image; updating a sensitivity distribution diagram according to the phase difference; according to a sensitivity distribution diagram before updating and a sensitivity distribution diagram after updating, performing sensitivity encoding reconstruction on the plurality of K space diagrams, thereby obtaining magnetic resonance images.

A system for parameterized FPGA (Field Programable Gate Array) implementation of real-time SENSE (SENSitivity Encoding) reconstruction including: a sensitivity maps memory configured to store sensitivity map data; an aliased image memory configured to store aliased image data acquired from a scanner; a reconstructed image memory configured to store reconstructed image data; a parameterized complex matrix multiplier; a pseudo-inverse calculator; a magnitude image block; and a controller; wherein sensitivity map data from the sensitivity maps memory is transferred to the pseudo-inverse calculator; wherein data from the pseudo-inverse calculator and the aliased image data from the aliased image memory is transferred to the complex matrix multiplier; wherein data from the complex matrix multiplier is transferred to the magnitude image block; wherein the controller is configured to generate an address of the sensitivity map memory and an address of the aliased image memory to access the encoding matrix and corresponding aliased image data and also configured to generate an address of the reconstructed image memory to store the reconstructed image data.

A method for magnetic resonance imaging includes unwrapping a calibration image based on coil sensitivity data obtained according to an array spatial sensitivity encoding technique and acquiring raw scan data of a plurality of MRI scan shots. The method further includes reconstructing an aliased image for each of the MRI scan shots, reconstructing an unaliased image for each of the MRI scan shots, according to the calibration image, recovering a plurality of pseudo-sensitivity maps from the plurality of unaliased images and from the calibration image, and unwrapping at least one final unaliased image from the plurality of aliased images, according to the plurality of pseudo-sensitivity maps.