Breast cancer detection and classification in digital mammography based on Non-Subsampled Contourlet Transform (NSCT) and Super Resolution
We propose a new algorithm for breast cancer detection and classification. Our system can accurately detect the probability of benign or malign breast lesion. We utilize NSCT transform and super resolution to improve the quality of the images. The results on MIAS database show significant performance of the proposed method. Our system achieves 91.43% and 6.42% as a mean accuracy and FPR, respectively.
breast cancer mammography non-subsampled contourlet transform (nsct) computer-aided diagnosis (cad) system super resolution (sr) bi-rads