Magee, Derek, Tanner, Steven, Waller, Michael, McGonagle, Dennis and Jeavons, Alan (2005) Registration of PET and MR hand volumes using Bayesian Networks. In: Yanxi, L., Jiang, T. and Zhang, C., (eds.) 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 3-540-29411-2Full text available as:
Available under licence : See the attached licence file.
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|
|Institution:||The University of Leeds|
|Academic Units:||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:||16 Jun 2014 08:26|