A Brain Tumor Detection Using K-means, Fuzzy C Means and Watershed Segmentation

Brain tumor is one of the serious diseases so it is necessary to have accurate detection. Generally by using CTscan and MRI techniques visual examination is done by doctors for detection of part of brain having tumor. In this paper three algorithms are used to perform brain tumor segmentation of MRI image. In first stage image pre-processing is performed to remove file artifacts, skull removal and median filter is applied for noise reduction. In second stage segmentation is performed on preprocessed image by k-means and FCM and watershed segmentation methods which partition the image into different regions. In third stage, thresholding and morphological operators are used to separate the part of brain having tumor from MRI image. At the end of the process the tumour is extracted from the MR image and its exact position and the shape also determined.