Brain Tumour Segmentation using Digital Image Processing

Brain tumour is a serious life- altering disease condition. It occurs by means of abnormal cells which form within the brain. Tumour Detection is one of the most important methods used in image processing. In the past few years, numerous techniques have been proposed. In this paper, we presented an abstract automated, and accurate method to classify a given MR brain image as normal or abnormal. The proposed method first employs high pass filters for noise removal from images, followed by applying medium pass filters to enhance the quality of the image. The extracted features were submitted to the segmentation technique followed by morphological filtering which avoids the unclustered regions that can inevitably be formed after segmentation of the brain MRI image for detection of tumour location. Medical Science in Image Processing is an emerging field that has proposed a lot of advanced techniques in the detection and analysis of a particular disease. Treatment of brain tumours in recent years is getting more and more challenging due to the complex structure, shape, and texture of the tumour.