抽象的

A Knowledge-Based Inferences System for the Early Detection of Brest Cancer

Mammography is considered the most effective method for early detection of breast cancers. However, it is difficult for radiologists to detect microcalcification clusters. Therefore we are proposed a computerized scheme for detecting early-stage microcalcification clusters in mammograms. Optimal set of features selected by Genetic algorithm are fed as input to Adaptive Neuro fuzzy inference system for classification of images into normal, suspect and abnormal categories. The method has been evaluated on 322 images comprising normal and abnormal images. The performance of the proposed technique is analyzed in terms convergence time. Experimental results shows that the features used are clinically significant for the accurate detection of breast tumor