MR-Brain Image Segmentation Using Gaussian Multiresolution Analysis and the EM Algorithm

We present a MR image segmentation algorithm based on the conventional Expectation Maximization (EM) algorithm and the multiresolution analysis of images. Although the EM algorithm was used in MRI brain segmentation, as well as, image segmentation in general, it fails to utilize the strong spatial correlation between neighboring pixels. The multiresolution-based image segmentation techniques, which have emerged as a powerful method for producing high-quality segmentation of images, are combined here with the EM algorithm to overcome its drawbacks and in the same time take its advantage of simplicity. Two data sets are used to test the performance of the EM and the proposed Gaussian Multiresolution EM, GMEM, algorithm. The results, which proved more accurate segmentation by the GMEM algorithm compared to that of the EM algorithm, are represented statistically and graphically to give deep

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