Extension of the ICP algorithm to nonrigid intensity-based registration of 3D volumes
Computer Vision and Image Understanding
Alignment by Maximization of Mutual Information
International Journal of Computer Vision
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
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
Group-wise motion correction of brain perfusion images
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
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Based on the standard sum of squared differences (SSD) criterion, we develop a fast and robust multimodal image registration algorithm that incorporates a polynomial model to capture the complex relationship between the intensity values of two images. The resulting energy function can be efficiently optimized using the Gauss-Newton method in either joint or constrained fashion. Comparisons using simulated data reveal that our method has a similar capture range to that of the mutual information. Furthermore, we demonstrate accurate MR-PET registration results for images with abnormal structures.