Mass edge detection in mammography based on plane fitting and dynamic programming

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Mass edge detection in mammography based on plane fitting and dynamic programming

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Symposium on Applied Computing archive
Proceedings of the 2007 ACM symposium on Applied computing table of contents

Seoul, Korea

SESSION: Artificial intelligence, computational logic, and image analysis table of contents

Pages: 80 - 81

Year of Publication: 2007

ISBN:1-59593-480-4

Authors

Enmin Song	Huazhong University of Science and Technology, Wuhan, China
Luan Jiang	Huazhong University of Science and Technology, Wuhan, China
Bo Meng	Huazhong University of Science and Technology, Wuhan, China
Renchao Jin	Huazhong University of Science and Technology, Wuhan, China
Xiangyang Xu	Huazhong University of Science and Technology, Wuhan, China
Chih-Cheng Hung	Southern Polytechnic State University, Marietta, GA

Sponsor

SIGAPP: ACM Special Interest Group on Applied Computing

Publisher

ACM New York, NY, USA

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ABSTRACT

In this paper an automatic and effective method was proposed for mass segmentation in mammography. Based on the facts that mass edges are continuous and closed curves consisted of points which have larger gradient transformation, a plane fitting method and a dynamic programming technique were applied. The regions of interest (ROIs) used in this study were extracted from DDSM. The preliminary experimental results show that the segmentation algorithm performs well for various types of masses.

REFERENCES

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