Performance Analysis of Fuzzy C Means Algorithm in Automated Detection of Brain Tumor

Image Segmentation is essential and challenging to visualize the tissue of human for analyzing the MR images. In brain MR images, the boundary of tumor tissue is highly irregular. Deformable models and Region based methods are extensively used for medical image segmentation, to locate the boundary of the tumor. Problems associated with non-linear distribution of real data, User interaction and poor convergence to the boundary region limited their usefulness. Clustering of brain tumor images, using Fuzzy C means is robust and effective for tumor localization. Even though the proposed method has high computational complexity, it shows superior results in segmentation efficiency and convergence rate. The Fuzzy C means clustering with the extension of Feature extraction and classification is very promising in the field of brain tumor detection.