Development of a VLSI Based Real-Time System for Carcinoma Detection and Identification

Breast cancer is most common life threatening non skin malignant state in women. Accurate and early detection of breast cancer provides various chances for the survival of the diseased person. The proposed system also helps the clinical practitioner to diagnose the disease correctly. In this paper, an efficient VLSI architecture for carcinoma detection and identification is implemented. The implementation consists of three phases: pre-processing, feature extraction and disease detection and identification. Pre-processing removes the noise by arithmetic mean filters from the breast MRI image. Then the enhanced image is applied to an efficient dual scan parallel flipping architecture to extract the features using pipeline operation. The disease detection and identification can be performed better by using content aware classifier, which is based on Euclidean distance and positive estimation method. The proposed work aims at developing a VLSI system to diagnose on a particular breast cancer disease and is implemented on VERTEX-4 FPGA as it is a real time solution for disease detection and identification.