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:
Feb. 20, 2024

Filed:

Oct. 22, 2020
Applicants:

Canon Medical Systems Corporation, Otawara, JP;

University Health Network, Toronto, CA;

Inventors:

Ting Xia, Vernon Hills, IL (US);

Zhou Yu, Vernon Hills, IL (US);

Patrik Rogalla, Toronto, CA;

Bernice Hoppel, Vernon Hills, IL (US);

Assignees:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G16H 30/20 (2018.01); G06N 3/04 (2023.01); G16H 50/30 (2018.01); G16H 50/20 (2018.01);
U.S. Cl.
CPC ...
G16H 30/20 (2018.01); G06N 3/04 (2013.01); G06T 7/0014 (2013.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G06T 2207/10028 (2013.01); G06T 2207/10081 (2013.01); G06T 2207/30168 (2013.01);
Abstract

The present disclosure relates to a method for patient-specific optimization of imaging protocols. According to an embodiment, the present disclosure relates to a method for generating a patient-specific imaging protocol, comprising acquiring scout scan data, the scout scan data including scout scan information and scout scan parameters, generating a simulated image based on the acquired scout scan data, deriving a simulated dose map from the generated simulated image, determining image quality of the generated simulated image by applying machine learning to the generated simulated image, the neural network being trained to generate at least one probabilistic quality representation corresponding to at least one region of the generated simulated image, evaluating the determined image quality relative to a image quality threshold and the derived simulated dose map relative to a dosage threshold, optimizing. based on the evaluating, scan acquisition parameters and image reconstruction parameters, and generating, optimal imaging protocol parameters, wherein the optimal imaging protocol parameters maximize image quality while minimizing radiation exposure.


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