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.

Date of Patent:
Jul. 19, 2022

Filed:

May. 06, 2021
Applicant:

Canon Medical Systems Corporation, Otawara, JP;

Inventors:

Andrew James Wheaton, Vernon Hills, IL (US);

Antonios Matakos, Vernon Hills, IL (US);

Samir Dev Sharma, Vernon Hills, IL (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 5/00 (2006.01); A61B 5/055 (2006.01); G01R 33/48 (2006.01); G06T 11/00 (2006.01); G16H 30/40 (2018.01); G01R 33/561 (2006.01); G01R 33/565 (2006.01); G06T 7/20 (2017.01);
U.S. Cl.
CPC ...
A61B 5/055 (2013.01); A61B 5/7203 (2013.01); G01R 33/4818 (2013.01); G06T 11/005 (2013.01); G01R 33/5611 (2013.01); G01R 33/56509 (2013.01); G06T 7/20 (2013.01); G16H 30/40 (2018.01);
Abstract

An apparatus and method are provided to simultaneously provide good image quality and fast image reconstruction from magnetic resonance imaging (MRI) data by selecting an appropriate value for the regularization parameter used in compressed sensing (CS) image reconstruction. In CS reconstruction a high-resolution image can be reconstructed from randomized undersampled data by imposing sparsity in multi-scale transformation (e.g., wavelet) domain. Further, in the transformation domain, a threshold can be determined between signal and noise levels of the transform coefficients. A regularization parameter based on this threshold scales the regularization term, which imposes sparsity, relative to the data fidelity term in an objective function, thereby balancing the tradeoff between noise and smoothing.


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