Interpolation artefacts in mutual information-based image registration
Computer Vision and Image Understanding - Special issue on analysis of volumetric image
The Structure of Locally Orderless Images
International Journal of Computer Vision
Variational Methods for Multimodal Image Matching
International Journal of Computer Vision
Journal of Cognitive Neuroscience
Nonrigid image registration using conditional mutual information
IPMI'07 Proceedings of the 20th international conference on Information processing in medical imaging
Fast free-form deformation using graphics processing units
Computer Methods and Programs in Biomedicine
Riemannian elasticity: a statistical regularization framework for non-linear registration
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
WBIR'06 Proceedings of the Third international conference on Biomedical Image Registration
Optimization of mutual information for multiresolution image registration
IEEE Transactions on Image Processing
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Mutual Information (MI) and normalized mutual information (NMI) are popular choices as similarity measure for multimodal image registration. Presently, one of two approaches is often used for estimating these measures: The Parzen Window (PW) and the Generalized Partial Volume (GPV). Their theoretical relation has so far been unexplored. We present the direct connection between PW and GPV for NMI in the case of rigid and non-rigid image registration. Through step-by-step derivations of PW and GPV we clarify the difference and show that GPV is algorithmically inferior to PW from a model point of view as well as w.r.t. computational complexity. Finally, we present algorithms for both approaches for NMI which is comparable in speed to Sum of Squared Differences (SSD), and we illustrate the differences between PW and GPV on a number of registration examples.