Detection of masses and microcalcifications in digitalmammogram images using fuzzy logic

Abstract

Background: Detection of small breast lesions is a challenging task for radiologists. Computer aided detection(CAD) systems are implemented to aid radiologists in detecting masses and microcalcifications. This hasthe potential to raise the level of sensitivity in breast cancer detection.Objectives: To evaluate a new system to detect suggestions of suspicious small lesions.Methods: Small samples were extracted from different tissue types. Texture features were calculated, andthe best features were selected using Waikato Environment for Knowledge Analysis (WEKA) software.Subsequently, 7 selected features were used to form a decision tree. To reduce false negative cases, fuzzy logicwas used. In the implementation phase, input images were divided into 8 pixel - 8 pixel tiles. For each tile, allselected features were computed as fuzzy inputs.Results: To evaluate the technique, the suggested system was applied to 326 images obtained from the NationalCancer Society of Malaysia. Based on this application, results showed that the suggested system has anacceptable sensitivity of 85.6% and specificity of 90.7%.Conclusions: The fuzzy system is a promising technique for early detection of breast cancer.