Brain tumor identifications are the most common issues for recent scenario of health care community. Image processing is a dynamic research zone in medical imaging methods utilized to image the internal segments of the human body for restorative diagnosis. A brain Magnetic Resonance Imaging (MRI) scan of a single individual consists of several slices across the 3D anatomical view. Therefore, manual segmentation of brain tumors from magnetic resonance (MR) images is a challenging and time-consuming task. Automatic brain tumor diagnosis with MRI is one of the precise medical image analyses which performance can be measured only through soft computing techniques. Now a day’s many soft computing techniques are available for this desirable performance measures. Therefore a review on soft computing techniques in MRI based Brain tumor detection system is presented in this paper. In this paper, a wide spread relative study is focused on Soft computing techniques to analyze the geometric characteristics of brain tumor images for tumor detection. The main goal of this work is to emphasize the variety of automated methods which can ultimately serve to developing novel ideas for solving the health care issues of the current society.

Brain Tumor, Image processing, Magnetic Resonance Imaging (MRI), Soft Computing techniques.