International Conference on Advanced Computing, Communication and Networks - CCN 2011
Author(s) : KAMAL K.MEHTA, MUKESH KUMAR
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 . So , in this paper a modified method of tumor line detection and segmentation is compared with other methods like random walk , traditional seeded region growing method and graph cut method . The main aim of this paper is to determine which method is optimistic , so that it can be 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 evaluation parameters used in this paper are segmentation accuracy, execution time, automation level etc. We have implemented our project work in MATLAB 220.127.116.114(R2008a) environment and applied all these to a set of 25 images.