Siemens Aktiengesellschaft

Siemens Healthcare Gmbh

Siemens Corporation

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

Siemens Medical Solutions Usa, Inc.

Yale University

Siemens Canada Limited

Edgar Mueller

Michael Zenge

Mariappan S Nadar

Qiu Wang

Dorin Comaniciu

Peter Speier

Andreas Greiser

Michaela Schmidt

Jun Liu

Bogdan Georgescu

Markus Vester

David Grodzki

Peter Schmitt

Stefan Thesen

Xiaoguang Lu

Ti-chiun Chang

Lars Lauer

Jens Guehring

Christoph Forman

Arne Littmann

Randall Kroeker

Alban Lefebvre

Nirmal Janardhanan

Zhili Yang

Oliver Heid

Stefan Popescu

Yefeng Zheng

Marcel Dominik Nickel

Berthold Kiefer

Stephan Kannengiesser

Marie-Pierre Jolly

Gareth Funka-Lea

Jens Gühring

Razvan Ioan Ionasec

Heiko Meyer

Hui Xue

Xiaoming Bi

Carmel Hayes

Jens Wetzl

Karsten Wicklow

Alexey Tsymbal

Robert Todd Constable

Donald Hardie

Dime Vitanovski

Kai Tobias Block

Katharina Hesels

Elmar Rummert

Gigi Galiana

Richard Hausmann

Aurelien Stalder

Rainer Kirsch

Manuela Rick

Axel Loewe

Gerhard Laub

Ralf Loeffler

Christian Muehlhaeusser

In a method for controlling a magnetic resonance imaging system as part of functional magnetic resonance imaging, a main magnetic field B0 is provided having a field strength of at most 1.4 tesla at a main field magnet system () of the magnetic resonance imaging system (); and a measurement is performed as part of functional magnetic resonance imaging, wherein a measurement sequence (MS) is applied that has a longer echo time TE (e.g. longer than 100 ms).

Method and device for controlling a magnetic resonance imaging system as part of functional magnetic resonance imaging

A magnet assembly for magnetic resonance imaging is used to generate the basic magnetic field with a strength needed to produce the steady state or equilibrium position of nuclei or nuclear spins in magnetic resonance imaging. This magnet, or a part thereof, is vibrated or tilted or otherwise periodically moved so as to change its position and thereby generate a time-varying gradient field, which is used to enter the acquired magnetic resonance signals as raw data into k-space.

Magnetic resonance imaging with spatial encoding by fast moving or vibrating magnetic field generator components

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

In a method for displaying quantitative magnetic resonance image data, and a processor, and a magnetic resonance (MR) apparatus that implement such a method, first quantitative MR image data of an examination object are provided to the processor, the first quantitative MR image having been obtained using an MR scanner with a first basic magnetic field strength. The first quantitative magnetic resonance image data are converted in the processor from the first basic magnetic field strength to a second basic magnetic field strength, thereby generating second quantitative MR image data, which are then displayed.

Method, processor and magnetic resonance apparatus for displaying quantitative magnetic resonance image data

In a method and apparatus for determining measurement protocol parameters of a magnetic resonance (MR) image, a first MR image exhibiting first contrast properties, is read into a computer and at least one first contrast ratio is determined in the computer from the first contrast properties. The computer then determines the measurement protocol parameters dependent on the at least one first contrast ratio, in order to generate a second MR image exhibiting second contrast properties such that the second contrast properties approximate, as closely as possible, to the first contrast properties. The measurement protocol parameters are presented as an output from the computer.

Automatic detection and setting of magnetic resonance protocols based on read-in image data

In a method and magnetic resonance apparatus for recording diagnostic measurement data of a heart of an examination object, the magnetic resonance apparatus is operated by a control sequence wherein an RF pulse excites nuclear spins with a flip angle of at least 60&#xb0;, the diagnostic measurement data are recorded in a coordinate system independent of the heart, and the basic magnetic field produced by the magnetic resonance apparatus is smaller than 1.0 tesla.

Method and magnetic resonance apparatus for acquiring diagnostic measurement data of a heart

The invention concerns a method for reconstructing medical image data which has access to free capacities of at least two computers and manages the use thereof for the purposes of the reconstruction. The method is a particularly reliable alternative to the reconstruction of medical image data based on algorithms that would require a working memory of above-average size.

Method and system of managed image reconstruction in medical imaging

A computer-implemented method of selecting a Magnetic Resonance Imaging (MRI) sampling strategy includes selecting a base variable-density sampling pattern and determining a scan time associated with the base variable-density sampling pattern. A modified variable-density sampling pattern is created by modifying one or more parameters of the base variable-density sampling pattern to maximize a sampled k-space area without increasing the scan time. Next, a scan is performed on an object of interest using the modified variable-density sampling pattern to obtain a sparse MRI dataset. Then a sparse reconstruction process is applied to the sparse MRI dataset to yield an image of the object of interest.

Sampling strategies for sparse magnetic resonance image reconstruction

In MR imaging of a predetermined volume segment of a living examination subject, the examination subject is stimulated with a defined stimulation pattern, MR data of the predetermined volume segment, are acquired, and MR images based on the MR data are generated that depend on the stimulation pattern. The predetermined volume segment is an internal organ or muscle tissue of the examination subject.

Method and magnetic resonance system for MR imaging of a predetermined volume segment of a living examination subject by stimulation of the examination subject

A computer-implemented method for learning a tight frame includes acquiring undersampled k-space data over a time period using an interleaved process. An average of the undersampled k-space data is determined and a reference image is generated based on the average of the undersampled k-space data. Next, a tight frame operator is determined based on the reference image. Then, a reconstructed image data is generated from the undersampled k-space data via a sparse reconstruction which utilizes the tight frame operator.

Dynamic image reconstruction with tight frame learning

A method of image reconstruction for a magnetic resonance imaging (MRI) system having a plurality of coils includes obtaining k-space scan data captured by the MRI system, the k-space scan data being representative of an undersampled region over time, determining a respective coil sensitivity profile for the region for each coil of the plurality of coils, and iteratively reconstructing dynamic images for the region from the k-space scan data via an optimization of a minimization problem. The minimization problem is based on the determined coil sensitivity profiles and redundant Haar wavelet transforms of the dynamic images.

MRI reconstruction with incoherent sampling and redundant haar wavelets

A system and method for regression-based segmentation of the mitral valve in 2D+t cardiac magnetic resonance (CMR) slices is disclosed. The 2D+t CMR slices are acquired according to a mitral valve-specific acquisition protocol introduced herein. A set of mitral valve landmarks is detected in each 2D CMR slice and mitral valve contours are estimated in each 2D CMR slice based on the detected landmarks. A full mitral valve model is reconstructed from the mitral valve contours estimated in the 2D CMR slices using a trained regression model. Each 2D CMR slice may be a cine image acquired over a full cardiac cycle. In this case, the segmentation method reconstructs a patient-specific 4D dynamic mitral valve model from the 2D+t CMR image data.

Method and system for regression-based 4D mitral valve segmentation from 2D+t magnetic resonance imaging slices

A computer-implemented method for reconstruction of a magnetic resonance image includes acquiring a first incomplete k-space data set comprising a plurality of first k-space lines spaced according to an acceleration factor and one or more calibration lines. A parallel imaging reconstruction technique is applied to the first incomplete k-space data to determine a plurality of second k-space lines not included in the first incomplete k-space data set, thereby yielding a second incomplete k-space data set. Then, the parallel imaging reconstruction technique is applied to the second incomplete k-space data to determine a plurality of third k-space lines not included in the second incomplete k-space data, thereby yielding a complete k-space data set.

Multi-stage magnetic resonance reconstruction for parallel imaging applications

A method and system for automated view planning for cardiac magnetic resonance imaging (MRI) acquisition is disclosed. The method and system automatically generate a full scan prescription using a single 3D MRI volume. The left ventricle (LV) is segmented in the 3D MRI volume. Cardiac landmarks are detected in the automatically prescribed slices. A full scan prescription, including a short axis stack and 2-chamber, 3-chamber, and 4-chamber views, is automatically generated based on cardiac anchors provided by the segmented left ventricle and the detected cardiac landmarks in the 3D MRI volume.

Method and system for automatic view planning for cardiac magnetic resonance imaging acquisition

A reconstructed image is rendered of a patient by a processor from a set of undersampled MRI data by first subtracting two repetitions of the acquired data in k-space to create a third dataset. The processor reconstructs the image by minimizing an objective function under a constraint related to the third dataset, wherein the objective function includes applying a Karhunen-Loeve Transform (KLT) to a temporal dimension of data. The objective function under the constraint is expressed as arg min{&#x2225;&#x3c6;(f)&#x2225;subject to &#x2225;Af&#x2212;y&#x2225;&#x2266;&#x3b5;}. The reconstructed image is an angiogram which may be a 4D angiogram. The angiogram is used to diagnose a vascular disease.

Non-contrast-enhanced 4D MRA using compressed sensing reconstruction

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Heroldsbach, Germany

Edgar Mueller