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:
Jan. 12, 2021

Filed:

Jan. 09, 2019
Applicant:

The Board of Trustees of the University of Illinois, Urbana, IL (US);

Inventors:

Bradley P. Sutton, Savoy, IL (US);

Xi Peng, Urbana, IL (US);

Matthew Bramlet, Peoria, IL (US);

Kevin Urbain, Peoria, IL (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06T 15/08 (2011.01); G06T 7/11 (2017.01); A61B 5/055 (2006.01); A61B 5/00 (2006.01); G06T 19/00 (2011.01);
U.S. Cl.
CPC ...
G06T 15/08 (2013.01); A61B 5/055 (2013.01); A61B 5/7267 (2013.01); G06T 7/11 (2017.01); G06T 19/00 (2013.01); A61B 2576/023 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20132 (2013.01); G06T 2210/41 (2013.01); G06T 2219/004 (2013.01);
Abstract

Aspects of the subject disclosure may include, for example, a method comprising: receiving, by a processing system including a processor, an input three-dimensional dataset comprising a first plurality of two-dimensional images of all or a portion of a subject; applying, by the processing system, bias field correction to the input three-dimensional dataset to generate a corrected three-dimensional dataset comprising a second plurality of two-dimensional images; and generating, by the processing system, a labeled three-dimensional dataset comprising a third plurality of two-dimensional images, wherein the labeled three-dimensional dataset further comprises one or more labels indicating an anatomical structure, and wherein the labeled three-dimensional dataset is generated via a convolutional neural network based upon the corrected three-dimensional dataset and based upon a previously trained three-dimensional dataset. Additional embodiments are disclosed.


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