Hybrid Mammogram Classification Using Rough Set and Fuzzy Classifier. (14th September 2009)

• Record Type: Journal Article
• Authors: Abu-Amara, Fadi; Abdel-Qader, Ikhlas
• Other Names: Mukherjee Jayanta Academic Editor.
• Is Part Of: International journal of biomedical imaging. Volume 2009(2009)
• Publication Date: 2009-09-14
• Subjects: Diagnostic imaging -- Periodicals; Imaging systems in medicine -- Periodicals; Imagerie pour le diagnostic; Imagerie médicale; Diagnostic imaging; Imaging systems in medicine; Diagnostic Imaging -- Periodicals; Electronic journals; Periodicals; 616.0754
• DOI: 10.1155/2009/680508
• Languages: English
• ISSNs: 1687-4188

Abstract

Abstract : We propose a computer aided detection (CAD) system for the detection and classification of suspicious regions in mammographic images. This system combines a dimensionality reduction module (using principal component analysis), a feature extraction module (using independent component analysis), and a feature subset selection module (using rough set model). Rough set model is used to reduce the effect of data inconsistency while a fuzzy classifier is integrated into the system to label subimages into normal or abnormal regions. The experimental results show that this system has an accuracy of 84.03% and a recall percentage of 87.28%.