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Mass segmentation in mammogram based on SPCNN and improved vector-CV

Han Zhen-Zhong Chen Hou-Jin Li Yan-Feng Li Ju-Peng Yao Chang Cheng Lin

Mass segmentation in mammogram based on SPCNN and improved vector-CV

Han Zhen-Zhong, Chen Hou-Jin, Li Yan-Feng, Li Ju-Peng, Yao Chang, Cheng Lin
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Publishing process
  • Received Date:  14 November 2013
  • Accepted Date:  19 December 2013
  • Published Online:  05 April 2014

Mass segmentation in mammogram based on SPCNN and improved vector-CV

  • 1. School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing 100044, China;
  • 2. Center of Breast Disease, Peking University People’s Hospital, Beijing 100044, China
Fund Project:  Project supported by the National Natural Science Foundation of China (Grant Nos. 661271305, 61201363, 60972093), the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20110009110001), and the Fundamental Research Funds for the Central Universities (Grant No. 2014JBM020).

Abstract: Mass segmentation plays an important role in computer-aided diagnosis (CAD) system. The segmentation result seriously affects classifying mass as benign and malignant. By combining the simplified pulse coupled neural network (SPCNN) and the improved vector active contour without edge (vector-CV), a novel method of mass segmentation in mammogram is proposed in this paper. First, the parameters and termination conditions of SPCNN are obtained through mathematical analysis and the initial contour is segmented by SPCNN. Then, the vector CV model is accordingly modified to overcome the shortcomings of traditional CV model. Finally, combined with the initial contour, the improved vector-CV is used to segment the mass contour. The experiments implemented on the public digital database for screening mammography (DDSM) and the clinical images which are provided by the Center of Breast Disease of Peking University People’s Hospital indicate that the proposed method is better than the existing methods, especially when dealing with the dense breasts of Oriental female.

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