Automatic 3D Image Segmentation Using Adaptive k -means on Brain MRI

The aim of this paper is to present a fully automatic adaptive k-means segmentation algorithm for MR Images in a 3D space. We model the gray scale values of the 3D image with a White Gaussian Process and superimpose a prior model on the region process in the form of Markov Random Field. These assumptions require the use of estimators for the parameters of the two processes. This has been carried out using decreasing size windows.

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