A Comparative Study of Region-Based Segmentation Algorithms on Brain MRI Images
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چکیده
Image Segmentation is the one of the principle component of image processing. In medical image processing the segmentation play an important role for classification, image analysis, and extraction of brain tumour, Different image segmentation methods are used for examination of medical images but efficient segmentation methods lead to accurate diagnosis. In this paper, we review the different segmentation algorithm on MRI Brain Images has been presented in order to obtain the accurate algorithm. The segmentation algorithms has been divided into four categories K-means, Fuzzy c means, Special constrained Fuzzy-c-means and Expectation Maximization. Efficient algorithm is obtained by computing the evaluation criteria such as Martin Criteria, Probability rand index and Variation of information. Index Term: K-means, Fuzzy c means, Special Constrained fuzzy c means and Expectation Maximization. Evaluation criteria such as martin criteria, Probability rand index and Variation of information
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