Abstract: The field of medical imaging gains its importance with increase in the need of automated and efficient diagnosis in a short period of time. MRI is the most important technique, in detecting the brain tumor. In this paper data mining methods are used for classification of MRI images. A new hybrid technique based on the support vector machine (SVM) and modified fuzzy c-means for brain tumor classification is used. The purposed algorithm is a combination of support vector machine (SVM) and modified fuzzy c-means, a hybrid technique for prediction of brain tumor. In this algorithm the first stage is noise reduction using Median Filtering. Modified fuzzy c-means (FCM) clustering is used for the segmentation of the image to detect the suspicious region in brain MRI image. Texture based features such as GLCM(Gray Level Co-occurrence Matrix)features is used for extraction of feature from the brain image, after which SVM technique is applied to classify the brain MRI images, which provide accurate and more effective result for classification of brain MRI images.
Keywords: Data Mining, MRI, Modified Fuzzy C-means clustering, Gray level co-occurrence matrix (GLCM), Support Vector Machine (SVM).