The Correlation Ratio as a New Similarity Measure for Multimodal Image Registration
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Non-Rigid Matching Using Demons
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Nonrigid image registration using conditional mutual information
IPMI'07 Proceedings of the 20th international conference on Information processing in medical imaging
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The hierarchical subdivision strategy which decomposes the non-rigid matching problem into numerous local rigid transformations is a very common approach in image registration. For multi-modal images mutual information is the usual choice for the measure of patch similarity. As already recognized in the literature, the statistical consistency of mutual information is drastically reduced when it is estimated for regions covering only a limited number of image samples. This often affects the reliability of the final registration result. In this paper we present a new intensity mapping algorithm which can locally transform images of different modalities into an intermediate pseudo-modality. Integrated into the hierarchical framework, this intensity mapping uses the local joint intensity histograms of the coarsely registered sub-images and allows the use of the more robust cross-correlation coefficient for the matching of smaller patches.