Pectoral muscle segmentation in mammograms based on homogenous texture and intensity deviation

被引：39

作者：

Li, Yanfeng ^{[1
]}

Chen, Houjin ^{[1
]}

Yang, Yongyi ^{[2
]}

Yang, Na ^{[1
]}

机构：

[1] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing, Peoples R China

[2] IIT, Dept Elect & Comp Engn, Chicago, IL 60616 USA

来源：

PATTERN RECOGNITION | 2013年 / 46卷 / 03期

基金：

高等学校博士学科点专项科研基金; 中国国家自然科学基金;

关键词：

Homogeneous texture; Image segmentation; Intensity deviation; Kalman filter; Mammogram; Pectoral muscle; IDENTIFICATION;

D O I：

10.1016/j.patcog.2012.09.021

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a novel method is proposed to segment the pectoral muscle in mammograms. First two anatomical features of the pectoral muscle, homogeneous texture and high intensity deviation are employed to identify the initial pectoral muscle edge. Then Kalman filter is used to refine the ragged initial edge. The proposed method is tested on Mammographic Image Analysis Society Mini-Mammographic (mini-MIAS) database and Digital Database for Screening Mammography (DDSM) database. The acceptable rate is 90.06% and 92% for the mini-MIAS database and the DDSM database, respectively. (C) 2012 Elsevier Ltd. All rights reserved.

引用

页码：681 / 691

页数：11

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