Brain Tumor Identification using MRI Images

In this paper, we propose segmentation method that uses the K-means clustering technique to identify the tumor in magnetic resonance image (MRI). Brain image segmentation is one of the most important parts of clinical diagnostic tools. Brain images mostly contain noise, inhomogeneity and sometimes deviation. So in this paper K-means clustering algorithm is to convert a given RGB image into a gray scale image and then separate the position of tumor objects. This improves the tumor boundaries accurately and is less time consuming when compared to many other clustering algorithms. In the conformal radiotherapy, the tumor cells are irradiated and killed with a very high precision, avoiding damage to the neighboring healthy tissues. The main objective of this study is the design of a computer system able to detect the presence of digital images of the brain and to accurately define its borderlines