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Registration of PET and MR hand volumes using Bayesian Networks

Magee, Derek, Tanner, Steven, Waller, Michael, McGonagle, Dennis and Jeavons, Alan (2005) Registration of PET and MR hand volumes using Bayesian Networks. In: Computer Vision for Biomedical Image Applications: First International Workshop, CVBIA 2005, Beijing, China, October 21, 2005, Proceedings. Lecture Notes in Computer Science (3765). Springer , New York , pp. 437-448. ISBN 3-540-29411-2

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Abstract

A method for the non-rigid, multi-modal, registration of volumetric scans of human hands is presented. PET and MR scans are aligned by optimising the configuration of a tube based model using a set of Bayesian networks. Efficient optimisation is performed by posing the problem as a multi-scale, local, discrete (quantised) search, and using dynamic programming. The method is to be used within a project to study the use of high-resolution HIDAC PET imagery in investigating bone growth and erosion in arthritis.

Item Type: Book Section
Copyright, Publisher and Additional Information: Copyright © 2005 Springer. This is an author produced version of a paper published in Computer Vision for Biomedical Image Applications.
Keywords: Medical Image Analysis, Registration, Dynamic Programming, Arthritis, Hands, Bayesian Networks
Academic Units: The University of Leeds > Faculty of Medicine and Health (Leeds) > Leeds Institute of Genetics, Health and Therapeutics (LIGHT) > Academic Unit of Medical Physics (Leeds)
The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Genetics, Health and Therapeutics (LIGHT) > Academic Unit of Medical Physics (Leeds)

The University of Leeds > Faculty of Engineering (Leeds) > School of Computing (Leeds)
Depositing User: Derek R. Magee
Date Deposited: 13 Mar 2006
Last Modified: 08 Feb 2013 17:02
Status: Published
Publisher: Springer
Refereed: Yes
URI: http://eprints.whiterose.ac.uk/id/eprint/770

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