Mean field and information theoretic algorithms for direct segmentation of tomographic images

Authors:
Andrew S. Belmont;Ian B. Kerfoot
Affiliations:
Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL;Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL
Venue:
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: image and multidimensional signal processing - Volume V
Year:
1993

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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, boundarv 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.