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:
Dec. 29, 2020

Filed:

Jul. 19, 2017
Applicant:

Siemens Healthcare Gmbh, Erlangen, DE;

Inventors:

Shaohua Kevin Zhou, Plainsboro, NJ (US);

Mingqing Chen, Plainsboro, NJ (US);

Hui Ding, College Park, MD (US);

Bogdan Georgescu, Plainsboro, NJ (US);

Mehmet Akif Gulsun, Princeton, NJ (US);

Tae Soo Kim, Baltimore, MD (US);

Atilla Peter Kiraly, San Jose, CA (US);

Xiaoguang Lu, West Windsor, NJ (US);

Jin-hyeong Park, Princeton, NJ (US);

Puneet Sharma, Princeton Junction, NJ (US);

Shanhui Sun, Princeton, NJ (US);

Daguang Xu, Princeton, NJ (US);

Zhoubing Xu, Plainsboro, NJ (US);

Yefeng Zheng, Princeton Junction, NJ (US);

Assignee:

Siemens Healthcare GmbH, Erlangen, DE;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06K 9/46 (2006.01); G06T 7/11 (2017.01); G06N 3/04 (2006.01); G06N 3/08 (2006.01); G06K 9/62 (2006.01); G16H 30/40 (2018.01);
U.S. Cl.
CPC ...
G06K 9/0014 (2013.01); G06K 9/4628 (2013.01); G06N 3/0445 (2013.01); G06N 3/0454 (2013.01); G06N 3/084 (2013.01); G06T 7/11 (2017.01); G06K 9/6209 (2013.01); G16H 30/40 (2018.01);
Abstract

Methods and systems for artificial intelligence based medical image segmentation are disclosed. In a method for autonomous artificial intelligence based medical image segmentation, a medical image of a patient is received. A current segmentation context is automatically determined based on the medical image and at least one segmentation algorithm is automatically selected from a plurality of segmentation algorithms based on the current segmentation context. A target anatomical structure is segmented in the medical image using the selected at least one segmentation algorithm.


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