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:
Aug. 20, 2024

Filed:

Sep. 10, 2021
Applicants:

GE Precision Healthcare Llc, Milwaukee, WI (US);

The Board of Trustees of the Leland Stanford Junior University, Stanford, CA (US);

Inventors:

Adam S. Wang, Palo Alto, CA (US);

Debashish Pal, Sunnyvale, CA (US);

Abdullah-Al-Zubaer Imran, Sunnyvale, CA (US);

Sen Wang, Menlo Park, CA (US);

Evan Zucker, Palo Alto, CA (US);

Bhavik Natvar Patel, Paradise Valley, AZ (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); A61B 6/00 (2006.01); A61B 6/03 (2006.01); G06N 3/08 (2023.01); G06N 20/00 (2019.01); G06V 10/25 (2022.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); A61B 6/032 (2013.01); A61B 6/542 (2013.01); A61B 6/545 (2013.01); G06N 3/08 (2013.01); G06N 20/00 (2019.01); G06V 10/25 (2022.01); G06T 2207/10081 (2013.01); G06T 2207/10144 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30168 (2013.01);
Abstract

Techniques are described for tailoring automatic exposure control (AEC) settings to specific patient anatomies and clinical tasks. According to an embodiment, computer-implemented method comprises receiving one or more scout images captured of an anatomical region of a patient in association with performance of a computed tomography (CT) scan. The method further comprises employing a first machine learning model to estimate, based on the one or more scout images, expected organ doses representative of expected radiation doses exposed to organs in the anatomical region under different AEC patterns for the CT scan. The method can further comprises employing a second machine learning model to estimate, based on the one or more scout images, expected measures of image quality in target and background regions of scan images captured under the different AEC patterns, and determining an optimal AEC pattern based on the expected organ doses and the expected measures of image quality.


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