Computer Aided Detection of Suspicious Masses and Micro-Calcifications

Mammography is considered as the most effective means for breast cancer diagnosis. This paper introduces two separate techniques for mass and micro-calcification segmentation in digital mammograms. Segmentation of masses consists of three steps- background subtraction, fuzzy texture representation and entropic thresholding. Similarly micro-calcifications are also segmented in three stages - background subtraction, Laplacian of Gaussian filtering and contrast estimation followed by thresholding. Both the techniques are verified with the markings given by the radiologist and are found to be quite effective tools in diagnosing breast cancer.