Abstract: Cancer is one of the common diseases occurring among the people all over the world. It can be due to various reasons such as different habitats, environmental disorders etc. Cancer being detected at early stages can save millions, if effective treatment is provided. It can cause damage to any part of body. Breast cancer occurs when breast cells divide rapidly to form a lump or mass known as a tumor. The detection of the breast cancer is a challenging problem, due to the structure of the cancer cells. This project presents a threshold method, for segmenting mammographic images to detect the Breast cancer in its early stages. The threshold will be determined by clustering an image based on row and column separation. The manual analysis of this samples are time consuming, inaccurate and requires intensive trained person to avoid diagnostic errors. The segmentation results will be used as a base for a Computer Aided Diagnosis system for early detection of cancer from mammographic images which will improves the chances of survival for the patient. Furthermore, the probability of the tumor to identify its type is also taken by us i.e. benign, suspicious or malignant.

Keywords: Biclustering, Image Processing, Benign, Malignant.