Segmentation of biomedical images using active contour model with robust image feature and shape prior. (28th October 2013)

• Record Type: Journal Article
• Authors: Yeo, Si Yong; Xie, Xianghua; Sazonov, Igor; Nithiarasu, Perumal
• Is Part Of: International journal for numerical methods in biomedical engineering. Volume 30:Number 2(2014:Feb.)
• Page Start: 232
• Page End: 248
• Publication Date: 2013-10-28
• Subjects: Biomedical engineering -- Periodicals; Imaging systems in medicine -- Periodicals; Numerical analysis -- Periodicals; Engineering mathematics -- Periodicals; 610.28
• DOI: 10.1002/cnm.2600
• Languages: English
• ISSNs: 2040-7939

Abstract

<abstract abstract-type="main" id="cnm2600-abs-0001"> <title>SUMMARY</title> <p id="cnm2600-para-0001">In this article, a new level set model is proposed for the segmentation of biomedical images. The image energy of the proposed model is derived from a robust image gradient feature which gives the active contour a global representation of the geometric configuration, making it more robust in dealing with image noise, weak edges, and initial configurations. Statistical shape information is incorporated using nonparametric shape density distribution, which allows the shape model to handle relatively large shape variations. The segmentation of various shapes from both synthetic and real images depict the robustness and efficiency of the proposed method. Copyright © 2013 John Wiley &amp; Sons, Ltd.</p> </abstract>