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25 April 1997 Bayes and medical imaging: it's time to make priors a priority
David R. Haynor
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Proceedings Volume 3034, Medical Imaging 1997: Image Processing; (1997) https://doi.org/10.1117/12.274075
Event: Medical Imaging 1997, 1997, Newport Beach, CA, United States
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.
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David R. Haynor "Bayes and medical imaging: it's time to make priors a priority", Proc. SPIE 3034, Medical Imaging 1997: Image Processing, (25 April 1997); https://doi.org/10.1117/12.274075
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KEYWORDS
Medical imaging
Image filtering
Image analysis
Data modeling
Computed tomography
Data processing
Gaussian filters
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