Information-theoretic multi-modal image registration based on the improved fast Gauss transform: application to brain images

Authors:
Žiga Špiclin;Boštjan Likar;Franjo Pernuš
Affiliations:
Faculty of Electrical Engineering, Laboratory of Imaging Technologies, University of Ljubljana, Ljubljana, Slovenia;Faculty of Electrical Engineering, Laboratory of Imaging Technologies, University of Ljubljana, Ljubljana, Slovenia;Faculty of Electrical Engineering, Laboratory of Imaging Technologies, University of Ljubljana, Ljubljana, Slovenia
Venue:
MBIA'11 Proceedings of the First international conference on Multimodal brain image analysis
Year:
2011

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Abstract

Performances of multi-modality image registration methods that are based on information-theoretic registration criteria crucially depend on the specific computational implementation. We proposed a new implementation based on the improved fast Gauss transform so as to estimate, from all available intensity samples, the intensity density functions needed to compute the information-theoretic criteria. The proposed and several other state-of-the-art implementations were tested and compared in 3-D rigid-body registration of multi-modal brain volumes. Experimental results indicate that the proposed implementation achieves the most consistent spatial alignment of brain volumes at a subpixel accuracy.