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Proceedings Paper

Bayes and medical imaging: it's time to make priors a priority
Author(s): David R. Haynor
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Paper Abstract

Bayesian approaches to the analysis of medical images have gained in popularity in the last two decades, in spite of their computational complexity, because they offer a consistent framework for dealing with problems such as model selection and the proper tradeoffs between measurements and prior expectations. A Bayesian approach to the analysis of medical images requires that one give thought to the specification of an image prior which reflects what we know about human anatomy and the broad spatial characteristics of the distribution of disease within the body. We present an approach, based on Markov random fields, to developing prior distributions for medical image analysis and show some preliminary results.

Paper Details

Date Published: 25 April 1997
PDF: 8 pages
Proc. SPIE 3034, Medical Imaging 1997: Image Processing, (25 April 1997); doi: 10.1117/12.274075
Show Author Affiliations
David R. Haynor, Univ. of Washington (United States)


Published in SPIE Proceedings Vol. 3034:
Medical Imaging 1997: Image Processing
Kenneth M. Hanson, Editor(s)

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