A Texture based Tumor detection and automatic Segmentation using Seeded Region Growing Method

Detection and 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. All automatic seed finding methods may suffer with the problem if there is no growth of tumor and any small white part is there. 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 method of tumor detection based on texture of the MRI and if it is detected then to segment it automatically is proposed in this paper 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 texture analysis and seeded region growing method and it was implemented using MATLAB 7.6.0.324 on 25 Magnetic Resonance Images having brain tumors and also on images without any abnormality to detect the tumor boundaries in 2D MRI for different cases.