The United States of America, As Represented by the Secretary, Department of Health and Human Services

Siemens Healthcare Gmbh

Siemens Aktiengesellschaft

Siemens Medical Solutions Usa, Inc.

The United States of America

Peter Kellman

Hui Xue

Andreas Greiser

Elliot R McVeigh

Bruce S Spottiswoode

Xiaoguang Lu

Sven Zuehlsdorff

Xiaoming Bi

Christopher Glielmi

Peter Weale

Kelvin Chow

Saurabh Shah

Renate Jerecic

Systems and methods to determine a first map of a first parameter based on first signals acquired by a magnetic resonance imaging system, the first map associating each of a plurality of voxels with a respective value of the first parameter, the first parameter quantifying a first physical characteristic of an object represented by the plurality of voxels, determine a second map of a second parameter based on the first signals, the second map associating each of the plurality of voxels with a respective value of the second parameter, the second parameter quantifying a second physical characteristic of the object, and determine a dark-blood phase-sensitive inversion recovery late gadolinium enhancement image based on the first map of the first parameter and on the second map of the second parameter.

Synthetic bright-blood and dark-blood PSIR LGE images

A method for performing free breathing pixel-wise myocardial T1 parameter mapping includes performing a free-breathing scan of a cardiac region at a plurality of varying saturation recovery times to acquire a k-space dataset; generating an image dataset based on the k-space dataset; and performing a respiratory motion correction process on the image dataset. The respiratory motion correction process comprises selecting a target image from the image dataset, co-registering each image in the image dataset to the target image to determine a spatial alignment measurement for each image, and identifying a subset of the image dataset comprising images with the spatial alignment measurement above a predetermined value. Following the respiratory motion correction process, a pixel-wise fitting is performed on the image dataset to estimate T1 relaxation time values for the cardiac region. Then, a pixel-map of the cardiac region is produced depicting the T1 relaxation time values.

Free breathing motion corrected pixel-wise MRI myocardial T1 parameter mapping

The present invention relates to a system and apparatus for managing and processing raw medical imaging data.

System and apparatus for real-time processing of medical imaging raw data using cloud computing

A computer-implemented method for determining magnetic field inversion time of a tissue species includes generating a T1-mapping image of a tissue of interest, the T1-mapping image comprising a plurality of T1 values within an expected range of T1 values for the tissue of interest. An image mask is created based on predetermined identification information about the tissue of interest. Next, an updated image mask is created based on a largest connected region in the image mask. The updated image mask is applied to the T1-mapping image to yield a masked image. Then, a mean relaxation time value is determined for the largest connected region. The mean relaxation time value is then used to determine a time point for nulling longitudinal magnetization.

Methods and systems for automatically determining magnetic field inversion time of a tissue species

Phase sensitive T1 mapping is provided in magnetic resonance (MR). The phase from samples of a modified Look-Locker inversion recovery sequence may be used to normalize contrast, allowing for accurate motion registration without extra information acquisition. The sign may be estimated, allowing T1 mapping with a single application of a non-linear fit.

Phase sensitive T1 mapping in magnetic resonance imaging

An MR magnetic field inhomogeneity compensation system acquires multiple MR data sets representing luminance intensity values of individual image elements comprising corresponding multiple different image versions of at least a portion of a first imaging slice of patient anatomy including fat and water components. The compensation system employs the multiple MR data sets in solving corresponding multiple simultaneous nonlinear equations to calculate local frequency offset associated with magnetic field inhomogeneity at the individual image element location, for an individual image element of the image elements. The local frequency offset comprises a difference between proton spin frequency at the location and a nominal proton spin frequency. The compensation system derives data representing an electrical signal to be applied to magnetic field generation coils to substantially compensate for determined offset frequencies at the plurality of individual locations. A magnetic field generation coil generates a magnetic field in response to applying the electrical signal to substantially compensate for the magnetic field inhomogeneity at the individual image element location.

System for adjusting a magnetic field for MR and other use

An MRI imaging system includes at least one processor and a plurality of coils to acquire a plurality of k-space samples of a target to image. The system includes a machine-readable media comprising instructions which, when executed by the processor, result in determining a plurality of different regularization matrices for a plurality of different regions of an image of the target. The regularization matrices are applied in the determination of a plurality of unmixing matrices for the regions. The unmixing matrices are applied to produce the image without ghost artifacts, from a plurality of MRI images produced from the plurality of k-space samples and each comprising ghost artifacts.

Method and apparatus to improve an MRI image using regularization

A ghost artifact cancellation technique is disclosed. Phased array combining is used to cancel ghosts caused by a variety of distortion mechanisms, including space-variant distortions, such as local flow or off-resonance. The technique uses a constrained optimization that optimizes signal-to-noise ratio (SNR) subject to the constraint of nulling ghost artifacts at known locations. In one aspect multi-coil, k-space data is passed through a converter to convert the k-space data to image domain. After the conversion, the images contain ghost artifacts. The images are then passed through one or more phased array combiners. Each phased array combiner separates the superimposed ghosts to produce an image without ghosts. These images may then be aligned by means of shifting and combined by a variety of means to improve the final image quality. In another aspect, the phase encode order is varied in time to produce ghosts with time varying phase. The series of images are then used to adaptively compute the phased array combiner and output combiner coefficients. The developed technique may be used with phase encode orders which reduce image distortion.

Ghost artifact cancellation using phased array processing

An apparatus and method for accelerating magnetic resonance imaging by decreasing the number of sequential phase encodes (undersampling). Image reconstruction of undersampled k-space data can cause ghost artifacts to be produced in the resulting sequence of images. A combination of temporal and spatial filters are used to substantially suppress the ghost artifacts. Additionally, the spatial filter receives spatial filter coefficients used in the filtering process. The spatial filter coefficients are adaptively or dynamically generated so that the coefficients are provided to the spatial filter while generating the sequence of images.

Growing community of inventors

Bethesda, MD, United States of America

Peter Kellman