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:
Nov. 24, 2020

Filed:

Feb. 08, 2019
Applicant:

Siemens Healthcare Gmbh, Erlangen, DE;

Inventors:

Mayalen Irene Catherine Etcheverry, Lawrenceville, NJ (US);

Bogdan Georgescu, Plainsboro, NJ (US);

Sasa Grbic, Plainsboro, NJ (US);

Dorin Comaniciu, Princeton Junction, NJ (US);

Benjamin L. Odry, West New York, NJ (US);

Thomas Re, Monroe, NJ (US);

Shivam Kaushik, South Amboy, NJ (US);

Bernhard Geiger, Cranbury, NJ (US);

Mariappan S. Nadar, Plainsboro, NJ (US);

Assignee:

Siemens Healthcare GmbH, Erlangen, DE;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/70 (2017.01); G06T 3/20 (2006.01); G06T 3/40 (2006.01); G06T 3/60 (2006.01); G16H 30/40 (2018.01); G06N 20/10 (2019.01);
U.S. Cl.
CPC ...
G06T 7/70 (2017.01); G06N 20/10 (2019.01); G06T 3/20 (2013.01); G06T 3/40 (2013.01); G06T 3/60 (2013.01); G16H 30/40 (2018.01); G06T 2207/20021 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30004 (2013.01);
Abstract

System and methods are provided for localizing a target object in a medical image. The medical image is discretized into a plurality of images having different resolutions. For each respective image of the plurality of images, starting from a first image and progressing to a last image with the progression increasing in resolution, a sequence of actions is performed for modifying parameters of a target object in the respective image. The parameters of the target object comprise nonlinear parameters of the target object. The sequence of actions is determined by an artificial intelligence agent trained for a resolution of the respective image to optimize a reward function. The target object is localized in the medical image based on the modified parameters of the target object in the last image.


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