Comparative study on the performance of textural image features for active contour segmentation

作     者：MORARU Luminita MOLDOVANU Simona 

作者机构：Dunarea de Jos University of GalatiGalati RO-800008Romania 

出 版 物：《Science China(Life Sciences)》 (中国科学（生命科学英文版）)

年 卷 期：2012年第55卷第7期

页      面：637-644页

核心收录：

学科分类：08[工学] 080203[工学-机械设计及理论] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 0802[工学-机械工程] 

基　　金：supported by the Project SOP HRD-EFICIENT 61445/2009 of University Dunarea de Jos of Galati Romania 

主　　题：active contour model image feature area error rate 

摘      要：We present a computerized method for the semi-automatic detection of contours in ultrasound images. The novelty of our study is the introduction of a fast and efficient image function relating to parametric active contour models. This new function is a combination of the gray-level information and first-order statistical features, called standard deviation parameters. In a comprehensive study, the developed algorithm and the efficiency of segmentation were first tested for synthetic images. Tests were also performed on breast and liver ultrasound images. The proposed method was compared with the watershed approach to show its efficiency. The performance of the segmentation was estimated using the area error rate. Using the standard devia- tion textural feature and a 5x5 kernel, our curve evolution was able to produce results close to the minimal area error rate （namely 8.88% for breast images and 10.82% for liver images）. The image resolution was evaluated using the con- trast-to-gradient method. The experiments showed promising segmentation results.