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A COMBINED METHOD USING FUZZY CLUSTERING AND MGGVF SNAKE MODEL FOR BRAIN TUMOR SEGMENTATION ON MRI IMAGES

A.Rajendran, R. Dhanasekaran

The active contours or snakes and region based methods are not used separately for effective segmentation of tumor region on brain MRI images. Active contours or snakes are problems with initialization, poor convergence to boundary concavities and difficulties in forcing a snake into long, thin boundary indentations. Region based methods do not include shape and boundary information. In this paper, we combine the region-based fuzzy clustering method called Enhanced Possibilistic Fuzzy C-Means (EPFCM) and Modified Generalized Gradient vector flow (MGGVF) snake model having diffusion in the normal direction for segmenting tumor region on MRI images effectively. The EPFCM method is used for initial segmentation of tumor then result of that is used to provide initial contour for MGGVF snake model. Then it is used to determine the final contour for exact tumor boundary. The experimental results on tumor MRI images reveal that our method is more robust and accurate for brain tumor segmentation.