Diagnosis of Breast Cancer and Clustering Technique using Thermal Indicators Exposed by Infrared Images

In this paper we proceed breast cancer detection through thermal indicators at infrared images to be taken from the patient. The work is notably important according to non application of harmful radiations where are used to produce mammography images for instance. In this method it has been tried to provide people in general, easy detection of breast cancer by using image processing techniques along with computer artificial intelligence tools. In this paper we proceed Half technique to detach breast region out of thermal image and then we cluster detachments using Fuzzy K- Means method. The presented method is highly important in breast cancer detection through which, while applying the technique, there would be possibility to diagnose the cancerous region and cut it away within few seconds. In a better word, there have been used three assimilate procedures of asymmetry analysis, thermogrphy development and K- means clustering to minimize error occurrence. Since breasts with malignant tumors have higher temperature than healthy breasts and even breasts with benign tumors, in this study, we look for detecting the hottest regions of abnormal breasts which are the suspected regions. ( Hossein Ghayoumi Zadeh, Iman Abaspur Kazerouni, Javad Haddadnia. Diagnosis of Breast Cancer and Clustering Technique using Thermal Indicators Exposed by Infrared Images. Journal of American Science 2011;7(9):281-288). (ISSN: 1545-1003). http://www.americanscience.org.