On ImprovedMedical Brain MR Image Segmentation Based on Truncated Skew Gaussian Mixture model usingHierarchical Clustering and EM Algorithms
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Abstract
Theuse of MRI segmentation is becoming more vital in diagnosing the cancer in the patients much effectively. There are plenty of methods available to segment the brain MR images. Among those methods, unsupervised methods are highly advised since they do not require any human interaction for segmenting with high precision. But, still there is a scope for improvement in the field of medical image segmentation. Hence,in this paper we proposed a novel approach for segmenting the MRI brain image based on Finite Truncated Skew Gaussian Mixture Model using Hierarchical Clustering algorithm. The obtained results are compared with various other techniques and the performance evaluation is performed using Image quality metrics and Segmentation metrics.
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Keywords:Finite Truncated Skew Gaussian Mixture model, Segmentation, Image quality metrics, Segmentation metrics.
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