Survey on Brain Tumour Detection and Classification Using Image Processing

Abstract---Medical Image Processing is a complex and challenging field nowadays. Processing of MRI images is one of the parts of this field. Automated and accurate classification of MR brain images is of importance for the analysis and interpretation of these images and many methods have been proposed Region growing is an important application of image segmentation in medical research for detection of tumour. In this an effective modified region growing technique for detection of brain tumour is used. Modified region growing includes an orientation constraint in addition to the normal intensity constrain. The performance of the proposed technique is systematically evaluated using the MRI brain images database. For validating the effectiveness of the modified region growing, the quantity rate parameter detection, the sensitivity, specificity and accuracy values will be used. Comparative analyses will be made for the normal and the modified region growing using both the Feed Forward Neural Network (FFNN) and Radial Basis Function (RBF) neural network.