Accurate identification of tumor in brain is a challenging task in medical image processing and diagnosing the tumor with the use of Magnetic Resonance Image (MRI). So, identification tumor plays important role and there are many traditional segmentation methods which gives output, but it may or may not be accurate. So in this paper we compared two models which are segmentation with fusion and segmentation without fusion by comparing their performance metrics we can conclude which model gives more accurate performance metrics and is more preferable for Processing of image which helps to cure the tumor. The MRI grey scale image-based segmentation is a compound task because of unpredictability of brain tumors. In this clustering and segmentation methods are used. The main aim of this work is to compare two referable models, and which has better performance metrics where includes PSNR, MSE, SSIM, DC and gives the preferable model.
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