International Journal of Electronics Communication and Computer Engineering Volume 3, Issue (1) NCRTCST, ISSN 2249 –071X National Conference on Research Trends in Computer Science and Technology - 2012 All copyrights Reserved by NCRTCST-2012,Departments of Computer Science and Engineering & Information Technology,CMR College of Engineering and Technology,Hyderabad,A.P,India. Identification of Brain Tumors in 2 D MRI Using Automatic Seeded Region Growing Method Swati Tiwari R.G.P.V,S.V.I.T.S,COMPUTERSCIENCE INDORE, MADHYA PRADESH, INDIA tiwari.swati@rediffmail.com Ashish Bansal R.G.P.V,S.V.I.T.S,IT INDORE,MADHYAPRADESH, INDIA ashssi@rediffmail.com Rupali Sagar .G.P.V,S.V.I.T.S,CSE INDORE,M.P., INDIA ABSTRACT - Automated brain tumor segmentation and detection are vastly important in medical diagnostics because it provides information related to anatomical structures as well as potential abnormal tissue necessary to delineate appropriate surgical planning. As the segmentation of anatomical regions of the brain is the fundamental problem in medical image analysis. Segmentation of Brain tumor appropriately is a difficult task in MRI. The MRI image is an image that produces a high contrast images indicating regular and irregular tissues that help to discriminate the overlapping in margin of ach limb. But when the edges of tumor is not sharpen then the segmentation results are not accurate i.e. segmentation may be over or under. This may be happened due to initial stage of the tumors. So , in this paper a modified method of tumor line detection and segmentation is used to separate the irregular from the regular surrounding tissue to get a real identification of involved and noninvolved area that help the surgeon to distinguish the involved area precisely. The method proposed here is seeded region growing method to detect the tumor boundaries in 2D MRI for different cases. This method that can be validated segmentation on 2D MRI Data. In this study, after a manual segmentation procedure, this approach can be converted into fully automated approach. Keywords: Brain tumor, Magnetic resonance Imaging (MRI), Image segmentation I INTRODUCTION Segmentation is a process of identifying an object or pattern in the given work space. In this project we are considering magnetic resonance image as our work space. Actually the MRI produces a high contrast image representing each part very clearly, but sometimes due to be determined accurately so a problem of segmenting it is always there. In these cases the physiologist always need to have keen observation of the anatomical structure. But this process is too much time consuming and if the initial segmentation result is not correct then other consequent results like volume calculation also produces incorrect measurement results. There are a number of methods for brain tumor segmentation like fuzzy logic approach, neuro fuzzy approach, Random walk etc, but these all methods can produces unsatisfactory results due to unshaped edge boundaries and also the time to produce desire result is large[6] . In this paper we are proposing an automatic region growing method to segment the brain tumours. So in this method the users don’t need to select the seed point manually therefore there is no need of human intervention [2]. In this project work our assumption is that the brain tumor have grown in considerable size and their structure may be of any type like snakelike or circular shaped etc[1]. In this paper our method proposed has divided into five subparts. The output obtained from one part is taken as input to the next part II.PROPOSEDMETHOD Published by IJECCE (www.ijecce.org) 22