A multiresolution diffused expectation-maximization algorithm for medical image segmentation.

Giuseppe Boccignone; Paolo Napoletano; Vittorio Caggiano; Mario Ferraro

doi:10.1016/j.compbiomed.2005.10.002

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A multiresolution diffused expectation-maximization algorithm for medical image segmentation.

Giuseppe Boccignone·Paolo Napoletano·Vittorio Caggiano·Mario Ferraro

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Abstract

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.

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BibTeX RIS

Giuseppe Boccignone, Paolo Napoletano, Vittorio Caggiano, Mario Ferraro. 2005-12-13. A multiresolution diffused expectation-maximization algorithm for medical image segmentation.. https://doi.org/10.1016/j.compbiomed.2005.10.002

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