The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Aug. 28, 2018
Filed:
Dec. 17, 2014
Siemens Healthcare Gmbh, Erlangen, DE;
Boris Mailhe, Plainsboro, NJ (US);
Qiu Wang, Princeton, NJ (US);
Johannes Flake, Princeton, NJ (US);
Mariappan S. Nadar, Plainsboro, NJ (US);
Laszlo Lazar, Gheorgheni, RO;
Yuanhsi Chen, Mt. Laurel, NJ (US);
Siemens Healthcare GmbH, Erlangen, DE;
Abstract
A computer-implemented method for reconstructing magnetic resonance images using a parallel computing platform comprising a host unit and a graphical processing device includes receiving a plurality of coil data sets from a magnetic resonance imaging system, each respective coil data set comprising scanner data and a coil sensitivity map associated with a distinct coil included in the magnetic resonance imaging system. An iterative compressed-sensing reconstruction process is applied to reconstruct an image based on the plurality of coil data sets. Each iteration of the iterative compressed-sensing reconstruction process comprises: individually transferring the plurality of coil data sets from the host unit to the graphical processing device using a plurality of asynchronous data streams, overlapping with transfer of the plurality of coil data sets, optimizing a plurality of data fidelity values on the graphical processing device, each respective data fidelity value corresponding to a distinct coil data set, and computing an estimated image on the graphical processing device based on the plurality of data fidelity values.