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A multiresolution diffused expectation-maximization algorithm for medical image segmentation
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DOI：10.1016/j.compbiomed.2005.10.002.png)
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In this paper a new method for segmenting medical images is presented, the multiresolution diffused expectation-maximization (MDEM) algorithm. The algorithm operates within a multiscale framework, thus taking advantage of the fact that objects/regions to be segmented usually reside at different scales. At each scale segmentation is carried out via the expectation-maximization algorithm, coupled with anisotropic diffusion on classes, in order to account for the spatial dependencies among pixels. This new approach is validated via experiments on a variety of medical images and its performance is compared with more standard methods. (c) 2005 Elsevier Ltd. All rights reserved.
Keyword:
image segmentation
expectation-maximization
multiresolution
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