Authors : M.N. Vimalkumar and K. HelenPrabha
Abstract: The mammographic image analysis to predict the breast cancer is research of interest now. The death rates of women are increased every year due to the lack of knowledge about the breast cancer in many parts of the world. The diagnosis is simple and survivals of the patient are high if the breast cancer is predicted at the early stage accurately. This study presents a new mammographic image analysis model to detect the cancer affected area in the breast. The proposed system consists of three processes, namely, transformation, segmentation and classification. The Non Subsampled Shearlet Transform (NSST), Robust Support Vector Machine (RSVM) and Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm are utilized for various processes. The proposed system is evaluated under two scenarios namely, visual evaluation and quantitative analysis. The quantitative evaluation reveals that the proposed system achieves a sensitivity, specificity and accuracy rate of 98.73, 96.15 and 98.36%, respectively.
M.N. Vimalkumar and K. HelenPrabha, 2016. Analysis and Diagnostic of Women Breast Cancer Using Mammographic Image. Asian Journal of Information Technology, 15: 2048-2056.