Hadi Roshan - Islamic Azad University( Sciences & Researches
Saeed Setayeshi - Amirkabir Industerial University
Hamid AbrishamiMoghadam - khajeNasirTosi Industerial University

Breast cancer is one of the most common conditions as well as one of the most important factors of death among women. If diagnosed correctly and in time, it may cause fewerdeath tolls. The most important method of diagnosing this type of cancer is using mammography imaging. In some cases, thediagnosis may be incorrect. In the present article, Cellular Automata is used for the diagnosis of breast cancer type micro-calsification (or tiny calciumparticle sediments). In this approach the mammography image of the alleged patient is converted to an optimum image throughpreprocessing. Next, this image is entered into acellular network to determine its cluster center. The results achieved by this approach on DDSMindicated that diagnosis based on the approachintroduced in this article can be a useful combination for the traditional methods.

Cellular Automata, Breast Cancer, Micro- calsification, Preprocessing