Automatic Detection of Pectoral Muscle with the Maximum Intensity Change Algorithm

Zhang, Zhiyong, Lu, Joan and Yip, Yau Jim (2010) Automatic Detection of Pectoral Muscle with the Maximum Intensity Change Algorithm. In: Research and Development in Intelligent Systems. Springer. ISBN 0857291297

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Abstract

The accurate segmentation of pectoral muscle in mammograms is necessary to detect breast abnormalities in computer-aided diagnosis (CAD) of breast cancer. Based on morphological characteristics of pectoral muscle, a corner detector and the Maximum Intensity Change (MIC) algorithm were proposed in this research to detect the edge of pectoral muscle. The initial result shows that the proposed approach detected pectoral muscle with high quality.

Item Type:	Book Chapter
Additional Information:	Paper presented at AI-2010: Thirtieth SGAI International Conference on Artificial Intelligence, Cambridge, UK, 14th - 16th December 2010
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > R Medicine (General)
Schools:	School of Computing and Engineering School of Computing and Engineering > Diagnostic Engineering Research Centre School of Computing and Engineering > Diagnostic Engineering Research Centre > Measurement System and Signal Processing Research Group School of Computing and Engineering > High-Performance Intelligent Computing ?? tserg ?? School of Computing and Engineering > High-Performance Intelligent Computing > Information and Systems Engineering Group
Related URLs:	Author Author
Depositing User:	Cherry Edmunds
Date Deposited:	30 Sep 2010 14:22
Last Modified:	06 Apr 2018 12:15
URI:	http://eprints.hud.ac.uk/id/eprint/8719

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