Automatic pectoral muscle boundary detection in mammograms based on Markov chain and active contour model

作     者：Lei WANG Miao-liang ZHU Li-ping DENG Xin YUAN 

作者机构：School of Computer Science and Technology Zhejiang University Hangzhou 310027 China 

出 版 物：《Journal of Zhejiang University-Science C(Computers and Electronics)》 (浙江大学学报C辑（计算机与电子（英文版）)

年 卷 期：2010年第11卷第2期

页      面：111-118页

核心收录：

学科分类：1305[艺术学-设计学（可授艺术学、工学学位）] 13[艺术学] 081104[工学-模式识别与智能系统] 08[工学] 0804[工学-仪器科学与技术] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 

基　　金：Project (No. 60505009) supported by the National Natural Science Foundation of China 

主　　题：Pectoral muscle Markov chain Active contour Mammogram 

摘      要：Automatic pectoral muscle removal on medio-lateral oblique (MLO) view of mammogram is an essential step for many mammographic processing algorithms. However,it is still a very difficult task since the sizes,the shapes and the intensity contrasts of pectoral muscles change greatly from one MLO view to another. In this paper,we propose a novel method based on a discrete time Markov chain (DTMC) and an active contour model to automatically detect the pectoral muscle boundary. DTMC is used to model two important characteristics of the pectoral muscle edge,i.e.,continuity and uncertainty. After obtaining a rough boundary,an active contour model is applied to refine the detection results. The experimental results on images from the Digital Database for Screening Mammography (DDSM) showed that our method can overcome many limitations of existing algorithms. The false positive (FP) and false negative (FN) pixel percentages are less than 5% in 77.5% mammograms. The detection precision of 91% meets the clinical requirement.