Abstract
We propose a multimodal free-form registration algorithm that matches voxel class labels rather than image intensities. Individual voxels are displaced such as to minimize the Kullback-Leibler distance between the actual and ideal joint probability distribution of voxel class labels, which are assigned to each image individually by a previous segmentation process. We evaluate the performance of the method for inter-subject brain registration with simulated deformations, using a viscous fluid model for regularization. The root mean square difference between recovered and ground truth deformations is smaller than 1 voxel.
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D’Agostino, E., Maes, F., Vandermeulen, D., Suetens, P. (2003). An Information Theoretic Approach for Non-rigid Image Registration Using Voxel Class Probabilities. In: Gee, J.C., Maintz, J.B.A., Vannier, M.W. (eds) Biomedical Image Registration. WBIR 2003. Lecture Notes in Computer Science, vol 2717. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39701-4_13
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DOI: https://doi.org/10.1007/978-3-540-39701-4_13
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