Automatic brain tumor segmentation and extraction in MR images

A brain tumor or intracranial neoplasm is formed when abnormal cells get accumulated within the brain. These cells multiply in an uncontrolled manner and damage the brain tissues. Magnetic Resonance Imaging (MRI) scans are commonly used to diagnose brain tumors. However, segmenting and detecting the brain tumor manually is a tedious task for the radiologists. Hence, there is a need for automatic systems which yield accurate results. In this paper, a fully automatic method is introduced to detect brain tumors. The proposed method consists of five stages, viz., Image Acquisition, Preprocessing, Segmentation using Fuzzy C Means technique, Tumor Extraction and Evaluation. Tumor extraction is carried out by using Area and Circularity as a criteria. The results are finally verified by comparing them with the manually segmented Ground Truth. Dice coefficient is also calculated and the average dice coefficient value obtained was 0.729.