Abstract This paper, aims to reveal a comparative analysis of classifier performance of MR brain images, parti cularly for the brain tumor detection and classification. The detec tion of brain tumor stands in need of Magnetic Reso nance Imaging (MRI). The moment invariant feature extraction has been ev aluated to categorize the MRI slices as normal, benign and malignant by Neural Network (NN) classifier. In our comparative study, we examine the precision rate of aforementioned classification with extracted features and the classification of brain images with selected features by Association Rule ( AR) based NN classifier. The results are then analyzed with Receiver Operati ng Characteristics (ROC) curve and compared to illu strate the method producing higher accuracy rate in tumor recognition . Factually, our analysis proves that the classifier works below feature extraction followed by rule pruning method affords better accuracy rate.

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[20] Za ane O., Antonie M., and Mammography Classification by an Association Rule-Based Classifier, in Proceedings of International Workshop on Multimedia Data Mining , Edmonton, Canada, pp. 62 Akila Thiyagarajan presently being an professor and Head in the department of Technology at Trichy Engineering College, Trichy. She received her master degree in computer and Engineering from JJ College of engineering, Trichy. Presently she is pursuing her University, Chennai. She has 12 years of experience in teaching. Her field of interest includes digital image processing, soft computing and data mi Comparative Analysis of Classifier Performance on MR Brain Images no. 1, pp. 127-136, and Madheswaran M., Pruned Associative Classification Technique for the Medical Image Diagnosis System, in International Conference Dubai, UAE, pp. 293-297, , Traina C., and Azevedo- An Association Rule-Based Method to Support Medical Image Diagnosis IEEE Transactions on pp. 277-285, 2008. A Classification sing Associative Classification, f Computer Application, Building an Iris sing Neural Network International Journal of Advancements in Technology, vol. 2, Neural Network Based Classification and Diagnosis of Brain International Journal of Artificial vol. 1, no. 2, pp. Wang Q., Liacouras E., Miranda E., Kanamalla Classification of , available at: http://knight.cis.temple.edu/~vasilis/Publications/ , last visited 2013. , Chawla S., SooYoo D., , and Davatzikos C., f Brain Tumor Type and Grade nd Shape in a Machine Magnetic Resonance in pp. 1609-1618, 2009. and Coman A., Mammography Classification by an Association in Proceedings of International Workshop on Multimedia Data pp. 62-69, 2002. Akila Thiyagarajan ME is presently being an Assistant professor and Head in the Information Trichy Engineering College, Trichy. She received her master degree in computer science J College of engineering, Presently she is pursuing her PhD in Anna University, Chennai. She has 12 years of experience in teaching. Her field of interest includes digital image processing, soft computing and data mining. UmaMaheswari Pandurangan MBA PhD Professor and Head of the department of Computer Science Engineering Engineering, Coim completed her BE Science and Engineering) at Thiagarajar Col Engineering, Madurai, ME Engineering) at PeriyarManiammai Col Technology for Women, M University and PhD (I and Chennai in 2009. During her tenure of 17 years of engineering teaching experience she performed various roles and responsibilities as academic coordinator, ISO management Representative, Organizing secretary for National and international Conferences, ISTE chapter secretary and convener for various workshops and faculty development programs. She delivered 33 workshops and seminars for staffs and students. Her research interests are in the field of data Mining, Intelligent Computing and image processing. 14 candidates are pursuing PhD under his guidance at present. From her record, she has published her Research findings in 14 International Journals/National Journals, 21 International Conferences and 10 National Conferences. She has also authored 8 Text Books. Sh e has rendered unblemished services in various categories as member as well as university nominee of Board of Studies, Computer Science Course for 5 Autonomous colleges, Member of University level NSS Advisory Council, coordinator of various programs relating to Services to Community and Coordinator of Entrepreneurship development cell sponsored by EDI, member of ISTE, IEEE, CSI, IAENG and ICTACT. 779 UmaMaheswari Pandurangan ME, MBA PhD is presently being a Professor and Head of the nt of Computer Science and ineering, at INFO Institute of Engineering, Coimbatore. She completed her BE (Computer Engineering) at Thiagarajar College of Engineering, Madurai, ME degree (Software Engineering) at PeriyarManiammai College of Technology for Women, MBA from Madurai Kamaraj and C) at Anna University, Chennai in 2009. During her tenure of 17 years of teaching experience she performed various roles and responsibilities as academic coordinator, ISO management Representative, Organizing secretary for National and international Conferences, ISTE chapter secretary and convener for various workshops and faculty development programs. She delivered 33 workshops and seminars for staffs and students. Her search interests are in the field of data Mining, Intelligent Computing and image processing. 14 candidates are pursuing PhD under his guidance at present. From her record, she has published her Research findings in 14 International Journals/National als, 21 International Conferences and 10 National Conferences. She has also authored 8 Text Books. Sh e has rendered unblemished services in various categories as member as well as university nominee of Board of Studies, Computer Science and Engineering urse for 5 Autonomous colleges, Member of University level NSS Advisory Council, Co- coordinator of various programs relating to Services to Community and Coordinator of Entrepreneurship development cell sponsored by EDI, India. She is a life , IEEE, CSI, IAENG and ICTACT.