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Front. Inform. Technol. Electron. Eng.  2010, Vol. 11 Issue (2): 111-118    DOI: 10.1631/jzus.C0910025
    
Automatic pectoral muscle boundary detection in mammograms based on Markov chain and active contour model
Lei WANG, Miao-liang ZHU, Li-ping DENG, Xin YUAN*
School of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
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Abstract  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.

Key wordsPectoral muscle      Markov chain      Active contour      Mammogram     
Received: 09 January 2009      Published: 01 January 2010
CLC:  TP391.4  
Fund:  Project (No. 60505009) supported by the National Natural Science Foundation of China
Cite this article:

Lei WANG, Miao-liang ZHU, Li-ping DENG, Xin YUAN. Automatic pectoral muscle boundary detection in mammograms based on Markov chain and active contour model. Front. Inform. Technol. Electron. Eng., 2010, 11(2): 111-118.

URL:

http://www.zjujournals.com/xueshu/fitee/10.1631/jzus.C0910025     OR     http://www.zjujournals.com/xueshu/fitee/Y2010/V11/I2/111


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

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.

关键词: Pectoral muscle,  Markov chain,  Active contour,  Mammogram 
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