Brain tumor segmentation: A performance analysis using K-Means, Fuzzy C-Means and Region growing algorithm

Medical imaging is a technique that is extensively used to create images of human body for medical and research purposes. Magnetic Resonance Imaging (MRI) is a powerful visualization tool that permits to acquire images of internal anatomy of human body in a secure and non-invasive manner. Automatic brain tumor detection from MRI images has become one of the major areas of medical research. The important task in the diagnosis of brain tumor is to determine the exact location, orientation and area of the abnormal tissues. This paper discuss the performance analysis of image segmentation techniques, viz., K-Means Clustering, Fuzzy C-Means Clustering and Region Growing for detection of brain tumor from sample MRI images of brain. The performance evaluation of the above mentioned techniques is done on the basis of error percentage as compared to ground truth. The real time database is taken from Rajiv Gandhi Cancer Institute & Research Centre, Delhi, India (RGCI&RC).