PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Incorporating Prior Knowledge on Class Probabilities into Local Similarity Measures for Intermodality Image Registration
M. Hofmann, B. Schölkopf, I. Bezrukov and N.D. Cahill
In: Proceedings of the MICCAI 2009 Workshop on Probabilistic Models for Medical Image Analysis (PMMIA)(2009).


We present a methodology for incorporating prior knowledge on class probabilities into the registration process. By using knowledge from the imaging modality, pre-segmentations, and/or probabilistic atlases, we construct vectors of class probabilities for each image voxel. By defining new image similarity measures for distribution-valued images, we show how the class probability images can be nonrigidly registered in a variational framework. An experiment on nonrigid registration of MR and CT full-body scans illustrates that the proposed technique outperforms standard mutual information (MI) and normalized mutual information (NMI) based registration techniques when measured in terms of target registration error (TRE) of manually labeled fiducials.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
Brain Computer Interfaces
Theory & Algorithms
Information Retrieval & Textual Information Access
ID Code:6320
Deposited By:Bernhard Schölkopf
Deposited On:08 March 2010