Detection of human brain tumour using MRI image segmentation and morphological operators

Image Segmentation is an important and challenging factor in the field of medical sciences. It is widely used for the detection of tumours. This paper deals with detection of brain tumour from MR images of the brain. The brain is the anterior most part of the nervous system. Tumour is a rapid uncontrolled growth of cells. Magnetic Resonance Imaging (MRI) is the device required to diagnose brain tumour. The normal MR images are not that suitable for fine analysis, so segmentation is an important process required for efficiently analyzing the tumour images. Clustering is suitable for biomedical image segmentation as it uses unsupervised learning. This paper work uses K-Means clustering where the detected tumour shows some abnormality which is then rectified by the use of morphological operators along with basic image processing techniques to meet the goal of separating the tumour cells from the normal cells.