A Modified Method to Segment Sharp and Unsharp Edged Brain Tumors in 2 D MRI Using Automatic Seeded Region Growing Method
Mukesh Kumar1, Kamal Mehta2

1Mukesh Kmar, (M.E.) C.S.E. Department, S.S.C.E.T., Bhilai, India.
2Prof. Kamal Mehta, H.O.D,CSE Department, S.S.C.E.T. Bhilai, India.
Manuscript received on April 25, 2011. | Revised Manuscript received on May 02, 2011. | Manuscript published on May 05, 2011. | PP: 37-40 | Volume-1 Issue-2, May 2011. | Retrieval Number: A033041211
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Segmentation of Brain tumor accurately is a challenging task in MRI. The MRI image is an image that produces a high contrast images indicating regular and irregular tissues that help to distinguish the overlapping in margin of each limb. But when the edges of tumor is not sharped 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 [5]. 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 used in this paper is seeded region growing method and it was implemented using MATLAB on 25 Magnetic Resonance Images to detect the tumor boundaries in 2D MRI for different cases.
Keywords: Gray level, MRI image, Region growing, tumour, segmentation etc.