A Microcalcification Detection Using Adaptive Contrast Enhancement on Wavelet Transform and Neural Network

Ho Kyung Kang, Yong Man Ro, Sung-Min Kim

Abstract: 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.