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Confidence shape metric for image segmentation

[+] Author Affiliations
Qi Zou

Beijing Jiaotong University, School of Computer and Information Technology, Beijing 100044, China

Siwei Luo

Beijing Jiaotong University, School of Computer and Information Technology, Beijing 100044, China

Jingjing Zhong

National Library of China, Beijing 100081, China

Liping Yang

Beijing Jiaotong University, School of Computer and Information Technology, Beijing 100044, China

J. Electron. Imaging. 22(2), 023009 (May 10, 2013). doi:10.1117/1.JEI.22.2.023009
History: Received July 28, 2012; Revised March 2, 2013; Accepted April 15, 2013
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Abstract.  Here, we propose a confidence shape metric for level set segmentation. First, the confidence shape metric, which encodes local confidence into the matching result, is used in matching shapes and producing confidence maps. Then, based on the confidence shape prior, the level set function evolves to a desired contour. The proposed shape metric allows representation of shape variations beyond the coverage of training shapes under the level set framework, which is suitable for segmenting strongly deformed and cluttered images, especially when the set of training shapes is sparse compared with numerous intracategory variations. We evaluated the proposed approach on the challenging Weizmann dataset and computed tomography images. Experimental results indicate the advantage of confidence shape prior over shape prior without confidence under the Dice-coefficient metric.

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Citation

Qi Zou ; Siwei Luo ; Jingjing Zhong and Liping Yang
"Confidence shape metric for image segmentation", J. Electron. Imaging. 22(2), 023009 (May 10, 2013). ; http://dx.doi.org/10.1117/1.JEI.22.2.023009


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