Mass Segmentation in Mammograms Based on Improved Level Set and Watershed Algorithm

被引：0

作者：

Liu, Jun ^{[1
]}

Liu, Xiaoming ^{[1
]}

Chen, Jianxun ^{[1
]}

Tang, J. ^{[1
]}

机构：

[1] Wuhan Univ Sci & Technol, Coll Comp Sci & Technol, Wuhan, Hubei, Peoples R China

来源：

ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS: WITH ASPECTS OF ARTIFICIAL INTELLIGENCE | 2012年 / 6839卷

关键词：

Breast cancer; Mass; Segmentation; Watershed; Level set; CLASSIFICATION;

D O I：

暂无

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 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.

引用

页码：502 / 508

页数：7

共 20 条

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