A computer-aided detection system for automatic mammography mass identification

Authors:
Hussein Samma;Chee Peng Lim;Ali Samma
Affiliations:
School of Electrical and Electronic Engineering, University of Science Malaysia, Malaysia;School of Electrical and Electronic Engineering, University of Science Malaysia, Malaysia;School of Computer Science, University of Science Malaysia, Malaysia
Venue:
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: models and applications - Volume Part II
Year:
2010

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Abstract

Automatic detection and identification of mammography masses is important for breast cancer diagnosis. However, it is challenging to differentiate masses from normal breast regions because they usually have low contrast and a poor boundary. In this study, we present a Computer-Aided Detection (CAD) system for automatic breast mass identification. A four-stage region-based procedure is adopted for processing the mammogram images, i.e. localization, segmentation, feature extraction, and feature selection and classification. The proposed CAD system is evaluated using selected mammogram images from the Mammographic Image Analysis Society (MIAS) database. The experimental results demonstrate that the proposed CAD system is able to identify mammography masses in an automated manner, and is useful as a decision support system for breast cancer diagnosis.