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Proceedings Paper

Mean-field and information-theoretic algorithms for direct segmentation of tomographic images
Author(s): Ian B. Kerfoot; Yoram Bresler; Andrew S. Belmont
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Paper Abstract

We apply the weak membrane model with optimization by mean field annealing to the direct segmentation of tomographic images. We also introduce models based on the minimum description length principle that include penalties for measurement error, boundary length, regions, and means. Outliers are prevented by upper and lower bound constraints on pixel values. Several models are generalized to three-dimensional images. The superiority of our models to convolution back projection is demonstrated experimentally.

Paper Details

Date Published: 29 July 1993
PDF: 8 pages
Proc. SPIE 1905, Biomedical Image Processing and Biomedical Visualization, (29 July 1993); doi: 10.1117/12.148709
Show Author Affiliations
Ian B. Kerfoot, Univ. of Illinois/Urbana-Champaign (United States)
Yoram Bresler, Univ. of Illinois/Urbana-Champaign (United States)
Andrew S. Belmont, Univ. of Illinois/Urbana-Champaign (United States)


Published in SPIE Proceedings Vol. 1905:
Biomedical Image Processing and Biomedical Visualization
Raj S. Acharya; Dmitry B. Goldgof, Editor(s)

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