A microcalcification detection using adaptive contrast enhancement on wavelet transform and neural network

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Microcalcification detection is an important part of early breast cancer detection. In this paper, we propose a microcalcification detection algorithm using adaptive contrast enhancement in a mammography CAD (computer-aided diagnosis) system. The proposed microcalcification detection algorithm includes two parts. One is adaptive contrast enhancement in which the enhancement filtering parameters are determined based on noise characteristics of the mammogram. The other is a multi-stage microcalcification detection. The results show that the proposed microcalcification detection algorithm is much more robust against fluctuating noisy environments.
Publisher
IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
Issue Date
2006-03
Language
English
Article Type
Article
Keywords

DIGITAL MAMMOGRAPHY

Citation

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, v.E89D, pp.1280 - 1287

ISSN
0916-8532
URI
http://hdl.handle.net/10203/20599
Appears in Collection
EE-Journal Papers(저널논문)
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