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:
Jul. 24, 2018

Filed:

Jul. 27, 2017
Applicant:

Siemens Healthcare Gmbh, Erlangen, DE;

Inventors:

Florin Cristian Ghesu, Erlangen, DE;

Bogdan Georgescu, Plainsboro, NJ (US);

Dorin Comaniciu, Princeton Junction, NJ (US);

Assignee:

Siemens Healthcare GmbH, Erlangen, DE;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06T 7/12 (2017.01); G06N 3/08 (2006.01); G06N 3/04 (2006.01); G06F 19/00 (2018.01); G06T 7/13 (2017.01);
U.S. Cl.
CPC ...
G06T 7/12 (2017.01); G06F 19/321 (2013.01); G06N 3/0472 (2013.01); G06N 3/08 (2013.01); G06T 7/13 (2017.01); G06T 2207/10028 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30004 (2013.01);
Abstract

Multi-scale deep reinforcement learning generates a multi-scale deep reinforcement model for multi-dimensional (e.g., 3D) segmentation of an object. In this context, segmentation is formulated as learning an image-driven policy for shape evolution that converges to the object boundary. The segmentation is treated as a reinforcement learning problem, and scale-space theory is used to enable robust and efficient multi-scale shape estimation. By learning an iterative strategy to find the segmentation, the learning challenges of end-to-end regression systems may be addressed.


Find Patent Forward Citations

Loading…