Content-Based Retrieval of Calcification Lesions in Mammography

In order to assist doctors to detect micro- calcifications, about the similar lesions retrieval problem of mammographic micro-calcification cluster, we develop a new algorithm with multi-feature fusion and relevance feedback based on the study of single feature and feature fusion using single distance measure image retrieving techniques, this method adopts multi-distance measure to calculate the similarity directing at different features. Experiment is based on mammography image database which contains 250 mammography images and each image contains calcification cluster, we verified the retrieval performance by the precision - recall ratio (PVR) of feature fusion using single distance, feature fusion using multi-distance and relevance feedback. Experimental results show that the method has a better retrieval result than these methods which based feature fusion which using single distance measurement.