Table of Contents
Journal of Medical Engineering
Volume 2013, Article ID 615254, 8 pages
Research Article

A Hybrid Image Filtering Method for Computer-Aided Detection of Microcalcification Clusters in Mammograms

1Research Division on Advanced Information Technology, Cyberscience Center, Tohoku University, 6-6-05 Aoba, Aramaki, Aoba-ku, Sendai 980-8579, Japan
2Graduate School of Engineering, Tohoku University, 6-6-05 Aoba, Aramaki, Aoba-ku, Sendai 980-8579, Japan
3Tohoku University Graduate School of Medicine, Tohoku University, 2-1 Seiryo-mashi, Aoba-ku, Sendai 980-8575, Japan

Received 29 October 2012; Revised 28 February 2013; Accepted 27 March 2013

Academic Editor: Valentina Camomilla

Copyright © 2013 Xiaoyong Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The presence of microcalcification clusters (MCs) in mammogram is a major indicator of breast cancer. Detection of an MC is one of the key issues for breast cancer control. In this paper, we present a highly accurate method based on a morphological image processing and wavelet transform technique to detect the MCs in mammograms. The microcalcifications are firstly enhanced by using multistructure elements morphological processing. Then, the candidates of microcalcifications are refined by a multilevel wavelet reconstruction approach. Finally, MCs are detected based on their distributions feature. Experiments are performed on 138 clinical mammograms. The proposed method is capable of detecting 92.9% of true microcalcification clusters with an average of 0.08 false microcalcification clusters detected per image.