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. 07, 2025

Filed:

Mar. 25, 2021
Applicant:

Accenture Global Solutions Limited, Dublin, IE;

Inventors:

Cecil Lynch, Granite Bay, CA (US);

Kung-Chuan Hsu, Cerritos, CA (US);

Shreyas Ramesh, Mountainside, NJ (US);

Carl Matthew Dukatz, Troy, MI (US);

Felix Dominik Schiessl, Hattersheim, DE;

Tim Leonhardt, Munich, DE;

Max Howard, San Francisco, CA (US);

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
A61N 5/10 (2006.01); G05B 19/4155 (2006.01); G06F 16/242 (2019.01); G06F 17/11 (2006.01); G06N 5/01 (2023.01); G06N 10/00 (2022.01); G06N 10/60 (2022.01); G16H 20/40 (2018.01); G16H 40/40 (2018.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G16H 50/70 (2018.01);
U.S. Cl.
CPC ...
A61N 5/1031 (2013.01); G05B 19/4155 (2013.01); G06F 16/2425 (2019.01); G06F 17/11 (2013.01); G06N 10/00 (2019.01); G06N 10/60 (2022.01); G16H 20/40 (2018.01); G16H 40/40 (2018.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G16H 50/70 (2018.01); A61N 5/1045 (2013.01); G05B 2219/45117 (2013.01);
Abstract

Methods, systems, and apparatus for generating intensity modulated radiation therapy treatment plans. In one aspect, a method includes receiving data representing an optimization problem; iteratively processing, until termination criteria are met, the received data representing the optimization problem to obtain data representing a solution to the optimization problem, comprising, for each iteration: performing a classical search algorithm on an input for the iteration to determine a first solution; providing data representing the first solution to a quantum computing resource, wherein the data representing the first solution comprises a quadratic unconstrained binary optimization formulation of the optimization problem in a local region around the first solution; obtaining data representing a second solution from the quantum computing resource; and providing the data representing the second solution as input to a subsequent iteration; and initiating an action based on the data representing a solution to the optimization problem.


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