Feature Extraction and Classification of Mammographic Masses
نویسنده
چکیده
The aim of this project is to classify the mammographic masses as benign or malignant using texture and shape features. A set of 73 mammograms is used for the analysis, out of which 41 are benign and 32 are malignant. Manually segmented masses are obtained from the DDSM, USF database [2]. Texture and shape features are extracted from the manually segmented masses. Stepwise linear discriminant analysis is used to get the optimum set of features. Maximum-likelihood classifier with linear discriminant analysis (LDA) is used for the classification. The system is tested using leave-one-out test method and an overall accuracy of about 78 % is achieved.
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تاریخ انتشار 2004