International Journal of Computer Application Issue 3, Volume 3 (May-June 2013) Available online on http://www.rspublication.com/ijca/ijca_index.htm ISSN: 2250-1797

In medical image analysis, classification plays an imperative role and the accessible corporeal classification plunge to congregate the requisites. Automatic image classification is emergent thriving research area and contribution diagnostician for malady to ascertain the echelon of malignant cells of brain tumor using artifical intellect Since manual classification is time devastating and bestow ambiguous classification.In the proposed methodology, features are extort from these raw images which are then fed to these classifiers as an sophisticated framework for multi-object classification of deep brain structures in MR images by consummation of Neural network and fuzzy logic as Artrifical Neural Network Fuzzy Inference System(ANFIS) functioning through explicit knowledge representation of an Fuzzy with the learning capacity of artificial feed forward neural network. This method first employs four types of tumor images including metastases, meningioma, glioma and astrocytoma Tentative outcome exemplify capable results in terms of classification accuracy and improve execution. A proportional analysis is demonstrated with the representatives of ANN and fuzzy systems to exhibit the enhanced temperament of ANFIS systems. Keywords—: ANFIS, image classification, brain tumor, MRI, Fuzzy logic ___________________________________________________________________________