Siemens Aktiengesellschaft

Siemens Healthcare Gmbh

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

Siemens Medical Solutions Usa, Inc.

The Ohio State University

Siemens Corporation

Other

The United States of America

Hui Xue

Marie-Pierre Jolly

Christoph Guetter

Jens Gühring

Andreas Greiser

Xiaoguang Lu

Sven Zuehlsdorff

Arne Littmann

Peter Kellman

Yu Ding

Jens Guehring

Mariappan S Nadar

Christophe Chefd'hotel

Orlando P Simonetti

Michaela Schmidt

Saurabh Shah

Bogdan Georgescu

Peter Speier

Marcel Dominik Nickel

Frank Sauer

Peter Schmitt

Michael Zenge

Edgar Mueller

Ti-chiun Chang

Qiu Wang

Xiaoming Bi

Jun Liu

Hasan Ertan Cetingul

Carmel Hayes

Rizwan Ahmad

Edgar Müller

Christopher Glielmi

Alban Lefebvre

Peter Weale

Bruce S Spottiswoode

Kelvin Chow

Nirmal Janardhanan

Manuela Rick

Zhili Yang

Samuel Tze Luong Ting

Jeremy Collins

Yixun Liu

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 estimating a coil sensitivity map for a magnetic resonance (MR) image includes providing a matrix A of sliding blocks of a 3D image of coil calibration data, calculating a left singular matrix Vfrom a singular value decomposition of A corresponding to &#x3c4; leading singular values, calculating P=VV, calculating a matrix that is an inverse Fourier transform of a zero-padded matrix P, and solving Mc=(S)cfor c, where cis a vector of coil sensitivity maps for all coils at spatial location r, and 

Eigen-vector approach for coil sensitivity maps estimation

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

A method of magnetic resonance (MR) imaging of a volume undergoing repetitive motion includes obtaining source slice data indicative of a plurality of source slices during the repetitive motion, and obtaining anchor slice data indicative of an anchor slice during the repetitive motion. The anchor slice intersects the plurality of source slices. The source slice data and the anchor slice data are reconstructed. A three-dimensional image assembly procedure is implemented to generate, for each phase of the repetitive motion, volume data based on a respective subset of the reconstructed source slice data. For each phase of the repetitive motion, the respective subset of slices is selected based on a correlation of the source slice data and the anchor slice data along an intersection between each source slice and the anchor slice. The source slice data of the selected subset is corrected for misalignment with the anchor slice data.

MRI 3D cine imaging based on intersecting source and anchor slice data

In a method for a rapid determination of spatially resolved magnetic resonance relaxation parameters in an area of examination, a preparation pulse is radiated into the area of examination. During the relaxation of the longitudinal magnetization, spatially encoded magnetic resonance signals are acquired at a minimum of two different points in time using a fast magnetic resonance sequence. At each inversion time, an image data record is reconstructed from the magnetic resonance signals, which are elastically registered to each other. From the recorded image data records, values of magnetic resonance relaxation parameters are spatially accurately determined.

Method for a rapid determination of spatially resolved magnetic resonance relaxation parameters in an area of examination

Magnetic resonance reconstruction includes motion compensation. Inverse-consistent non-rigid registration is used to determine motion between shots. The motion is incorporated into reconstruction. The incorporation compensates for the motion resulting from the period over which the MR data is acquired.

Motion compensated magnetic resonance reconstruction in real-time imaging

Parallel magnetic resonance imaging (pMRI) reconstruction techniques are commonly used to reduce scan time by undersampling the k-space data. In GRAPPA, a k-space based pMRI technique, the missing k-space data are estimated by solving a set of linear equations; however, this set of equations does not take advantage of the correlations within the missing k-space data. All k-space data in a neighborhood acquired from a phased-array coil are correlated. The correlation can be estimated easily as a self-constraint condition, and formulated as an extra set of linear equations to improve the performance of GRAPPA. We propose a modified k-space based pMRI technique call self-constraint GRAPPA (SC-GRAPPA) which combines the linear equations of GRAPPA with these extra equations to solve for the missing k-space data. Since SC-GRAPPA utilizes a least-squares solution of the linear equations, it has a closed-form solution that does not require an iterative solver.

Self-constraint non-iterative GRAPPA reconstruction with closed-form solution

Parallel imaging magnetic resonance reconstruction is performed with temporal sensitivity. Rather than estimate the coil sensitivity once for each coil of an array, the coil sensitivity at different times is estimated. The movement of the patient may result in different sensitivities at different times. By using the time varying sensitivity in iterative, self-consistent, non-linear parallel imaging, real-time imaging may be provided with stable artifacts in view of increasing SNR even with higher reduction factors (e.g., 4-6).

Self consistent parallel imaging with temporal sensitivity estimation in real-time magnetic resonance imaging

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

A method for correcting the background phase in magnetic resonance phase contrast flow images includes providing a time series of velocity encoded magnetic resonance images of a patient, where the time series of velocity encoded images comprises for each time point a phase contrast image where a pixel intensity is proportional to a flow velocity, measuring a change of intensity for each pixel over the time series of phase contrast images, identifying pixels with a low measure of temporal change as stationary pixels, and calculating a correction field for the stationary pixels, where the correction field represents a background phase to be subtracted from the phase contrast image.

System and method for background phase correction for phase contrast flow images

A method for performing motion compensation in a series of magnetic resonance (MR) images includes acquiring a set of MR image frames spanning different points along an MR recovery curve. A motion-free synthetic image is generated for each of the acquired MR image frames using prior knowledge pertaining to an MR recovery curve. Each of the acquired MR images is registered to its corresponding generated synthetic images. Motion within each of the acquired MR image is corrected based on its corresponding generated synthetic image that has been registered thereto.

Automatic registration of image series with varying contrast based on synthetic images derived from intensity behavior model

A method including receiving an image sequence, wherein the image sequence includes a plurality of two-dimensional (2D) image frames of an organ arranged in a time sequence; constructing a three-dimensional (3D) volume by stacking a plurality of the 2D image frames in time order; detecting a best bounding box for a target of interest in the 3D volume, wherein the best bounding box is specified by a plurality of parameters including spatial and temporal information contained in the 3D volume; and determining the target of interest from the best bounding box.

Detection of landmarks and key-frames in cardiac perfusion MRI using a joint spatial-temporal context model

A method for identifying a region of interest within a time sequence of images includes acquiring a time sequence of images comprising a plurality of image frames. Image segmentation is performed to segment a region of interest (ROI) from within each of the plurality of image frames of the time sequence of images. Manual edits are received for the ROI within one or more of the plurality of image frames. The manual edits are propagated to other image frames of the plurality of images. An extent to which each of the manual edits are propagated to other image frames is dependent upon a transformation function or deformation field used to propagate the manual edits and a weighing factor that is influenced by a distance in time between the other image frames and the frames that have been manually edited.

Interaction method for regions of-interest in time series images

A method for clinical parameter derivation and adaptive flow acquisition within a sequence of magnetic resonance images includes commencing an acquisition of a sequence of images. One or more landmarks are automatically detected from within one or more images of the sequence of images. The detected one or more landmarks are propagated across subsequent images of the sequence of images. A plane is fitted to the propagation of landmarks. The positions of landmarks or alternatively the position of the fitted plane within the sequence of images is used for derivation of clinical parameters such as tissue velocities and/or performing adaptive flow acquisitions to measure blood flow properties.

Motion tracking for clinical parameter derivation and adaptive flow acquisition in magnetic resonance imaging

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Franklin Park, NJ, United States of America

Hui Xue