Mass segmentation in mammograms based on improved level set and watershed algorithm

Authors:
Jun Liu;Xiaoming Liu;Jianxun Chen;J. Tang
Affiliations:
College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, Hubei, China;College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, Hubei, China;College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, Hubei, China;College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, Hubei, China
Venue:
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Year:
2011

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Abstract

In this paper, a new mass segmentation algorithm is proposed. In the new proposed algorithm, a fully automatic marker-controlled watershed transform is first proposed to segment the mass region roughly, and then a level set is used to refine the segmentation. The new algorithm combines the advantages of both methods. The combination of the watershed based segmentation and level set method can improve the efficiency of the segmentation. Images from DDSM were used in the experiments and the results show that the new algorithm can improve the accuracy of mass segmentation.