Detection and estimation of 2-D brain tumor size using fuzzy C-means clustering

Abstract

Brain tumor is the main cause of mortality among children and adults which cause the abnormal growth of mass of tissues. So exact segmentation of this tissue mass is required for the exact diagnosis of tumor. This paper presents a technique for brain tumor segmentation and detection in magnetic resonance image (MRI) using a hybrid approach of fuzzy c-means clustering followed by mathematical morphology. Further length & width is calculated based on Euclidean distance measure and an approach is applied based on calculating the height and width of tumor to approximately detect the size of tumor in 1D and 2D for estimating the cancer stages.