http://iaeme.com/Home/journal/IJEET 188 editor@iaeme.com International Journal of Electrical Engineering & Technology (IJEET) Volume 9, Issue 4, July-August 2018, pp. 188-196. Article ID: IJEET_09_04_020 Available online at http://iaeme.com/Home/issue/IJEET?Volume=9&Issue=4 Journal Impact Factor (2018 9.1872 (Calculated by GISI) www.jifactor.com ): ISSN Print: 0976-6545 and ISSN Online: 0976-6553 © IAEME Publication AN ENHANCED DIAGNOSIS METHOD FOR CANCER TREATMENT USING FUZZY MODEL S Arulraj, K Muthusamy, D Yasararafath and R Nandhakumar Rathinam Technical Campus, FAT Coimbatore, Tamilnadu, India ABTRACT Computer aided diagnosis (CAD) systems evaluate the conspicuous structure. Most of the existing diagnosis methods used mammogram mass characteristics but in the proposed technique microcalcification (MC) characteristics are used. In this project, cancer cells are diagnosis using the steps like mammogram image, pre-processing techniques, segmentation, classification, fuzzy logic and Receiver Operating Characteristics (ROC) curve analysis. Mammogram images are collected from the National Institute of Cancer. Pre-processing technique performed using normalization and median filtering. Based on the local threshold method, segmentation is done to identify the location of microcalcification present cells. Classification technique includes Perceptron algorithm and case based reasoning (CBR) method. Perceptron algorithm is used to classify the microcalcification present cells and microcalcification absent cells.CBR is used to classify the microcalcification present cells into following classes initial, very small, small, medium, high, very high. Fuzzy logic used for decision making purpose. And system performance analyzed using ROC curve analysis. This method provides better performance (95%) compare to the previous diagnosis techniques. Key words: Diagnosis Method, Cancer Treatment, Fuzzy Model, Mammogram, Cite this Article: S Arulraj, K Muthusamy, D Yasararafath and R Nandhakumar, An Enhanced Diagnosis Method for Cancer Treatment using Fuzzy Model, International Journal of Electrical Engineering and Technology, 9(4), 2018, pp. 188-196. http://iaeme.com/Home/issue/IJEET?Volume=9&Issue=4 1. INTRODUCTION Getting a high-quality screening mammogram and having a clinical breast exam (an exam done by a health care provider) on a regular basis are the most effective ways to detect breast cancer early. As with any screening test, screening mammograms have both benefits and limitations. For example, some cancers cannot be detected by a screening mammogram but may be found by a clinical breast exam. Checking one’s own breasts for lumps or other unusual changes is called a breast self-exam, or BSE. This type of exam cannot replace regular screening mammograms or clinical breast exams. In clinical trials, BSE alone was not found to help reduce the number of deaths from