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:
Mar. 15, 2016

Filed:

Aug. 04, 2014
Applicant:

Siemens Medical Solutions Usa, Inc., Malvern, PA (US);

Inventors:

Fitsum Aklilu Reda, Malvern, PA (US);

Zhigang Peng, Bluebell, PA (US);

Shu Liao, Chester Springs, PA (US);

Gerardo Hermosillo Valadez, West Chester, PA (US);

Yoshihisa Shinagawa, Downingtown, PA (US);

Yiqiang Zhan, West Chester, PA (US);

Xiang Sean Zhou, Exton, PA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06T 7/00 (2006.01); G06K 9/46 (2006.01); G06K 9/62 (2006.01);
U.S. Cl.
CPC ...
G06T 7/0089 (2013.01); G06K 9/468 (2013.01); G06K 9/6206 (2013.01); G06T 7/0028 (2013.01); G06T 7/0081 (2013.01); G06K 9/00214 (2013.01); G06T 2207/20121 (2013.01); G06T 2207/20128 (2013.01); G06T 2207/30008 (2013.01);
Abstract

Disclosed herein is a framework for segmenting articulated structures. In accordance with one aspect, the framework receives a target image, a reference image, statistical shape models, local appearance models and a learned landmark detector. The framework may automatically detect first centerline landmarks along centerlines of articulated structures in the target image using the learned landmark detector. The framework may then determine a non-rigid transformation function that registers second centerline landmarks along centerlines of articulated structures in the reference image with the first centerline landmarks. Mean shapes of the statistical shape models may then be deformed to the target image space by applying the non-rigid transformation function on the mean shapes. The framework may further search for candidate points in the mean shapes using the local appearance models. The mean shapes may be fitted to the candidate points to generate a segmentation mask.


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