Paper Title:
Pectoral Muscle Segmentation for Digital Mammograms Based on Otsu Thresholding
  Abstract

The appearance of pectoral muscle in medio-lateral oblique (MLO) views of mammograms can increase the false positive in computer aided detection (CAD) of breast cancer detection. Pectoral muscle has to be identified and segmented from the breast region in a mammogram before further analysis. The main goal of this paper is to propose an accurate and efficient algorithm of pectoral muscle extraction on MLO mammograms. The proposed algorithm bases on the positional characteristic of pectoral muscle in a breast region to combine the iterative Otsu thresholding scheme and the mathematic morphological processing to find the rough border of the pectoral muscle. The multiple regression analysis is then employed on the rough border to obtain the accurate segmentation of the pectoral muscle. The presented algorithm is tested on the digital mammograms from the Mammogram Image Analysis Society (MIAS) database. The experimental results show that the pectoral muscle extracted by the presented algorithm approximately follows that extracted by an expert radiologist.

  Info
Periodical
Chapter
Chapter 8: System Modeling and Simulation
Edited by
Dongye Sun, Wen-Pei Sung and Ran Chen
Pages
4537-4541
DOI
10.4028/www.scientific.net/AMM.121-126.4537
Citation
C. C. Liu, S. S. Yu, C. Y. Tsai, T. S. Tsui, "Pectoral Muscle Segmentation for Digital Mammograms Based on Otsu Thresholding", Applied Mechanics and Materials, Vols. 121-126, pp. 4537-4541, 2012
Online since
October 2011
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$32.00
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