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:
Sep. 20, 2022
Filed:
Dec. 31, 2018
Applicant:
Siemens Healthcare Gmbh, Erlangen, DE;
Inventors:
Assignee:
Siemens Healthcare GmbH, Erlangen, DE;
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G01R 33/56 (2006.01); G01R 33/44 (2006.01); G06N 3/04 (2006.01); G06N 3/08 (2006.01); G16H 30/40 (2018.01); G06T 11/00 (2006.01); G06T 7/00 (2017.01); G01R 33/24 (2006.01);
U.S. Cl.
CPC ...
G01R 33/5608 (2013.01); G01R 33/24 (2013.01); G01R 33/443 (2013.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06T 7/0012 (2013.01); G06T 11/006 (2013.01); G16H 30/40 (2018.01); G06T 2207/10088 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30016 (2013.01);
Abstract
Techniques are disclosed to leverage the use of convolutional neural networks or similar machine learning algorithms to predict an underlying susceptibility distribution from MRI phase data, thereby solving the ill-posed inverse problem. These techniques include the use of Deep Quantitative Susceptibility 'DeepQSM' mapping, which uses a large amount of simulated susceptibility distributions and computes phase distribution using a unique forward solution. These examples are then used to train a deep convolutional neuronal network to invert the ill-posed problem.