All over the world,breast cancer is the second most prevailing threat related to cancer among the female community. Researchers are striving hard to detect breast cancer at an early stage and provide appropriate remedial measures to extend the lifespan of cancer patients. Image segmentation is an important aspect of medical imaging. Medical images are frequently corrupted by high levels of noise and signal dropouts and thus,it results in poor contrast along boundaries. This paper surveys the segmentation methods used in processing mammographic medical images. Segmentation of these images helps in detecting the abnormalities like benign and malignant tumors and micro calcifications at early stages. The radiologist uses the CAD system for better classification of benign and malignant abnormalities from the mammograms. This survey is conducted on the various segmentation methods used in the mammograms to detect the abnormalities and explores the methods useful for better classification which will reduce false positives. © 2016,International Journal of Pharmacy and Technology. All rights reserved.