Abstract
Breast cancer is second most rank disease after lung cancer between ladies around the world. Early detection declines the cancer death rate among women. Computer aided detection (CAD) system have been emerged which help the radiologists by specifying tumor region and reducing error mistake. Segmentation plays an important role in finding tumor area, i.e. Region of Interest (ROI). This paper investigates various segmentation techniques for breast cancer detection. Also, two segmentation techniques, Fuzzy C-Mean (FCM) and K-means, have been applied on mammogram images taken from MIAS database. Results shows that K-means is capable of estimating tumor region boundary as compared to FCM.
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