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. © Springer-Verlag Berlin Heidelberg 2005.
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CITATION STYLE
Magee, D., Tanner, S., Waller, M., McGonagle, D., & Jeavons, A. P. (2005). Registration of PET and MR hand volumes using Bayesian networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3765 LNCS, pp. 437–448). https://doi.org/10.1007/11569541_44
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