Abstract
We propose a novel approach to landmark-based medical image registration based on the geostatical method of Kriging prediction. Our method exploits the spatial statistical relation between two images, as estimated using general-purpose registration algorithms, in order to construct an optimum predictor of the displacement field. High accuracy is achieved by using an estimated spatial model of the displacement field directly from the image data, while practically circumventing the difficulties that prevented Kriging from being widely used in image registration.
This work has been partially funded by the Spanish Government (MCyT TIC-2001-3808-C02)
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Keywords
- Ordinary Kriging
- Variogram Model
- Good Linear Unbiased Estimator
- Good Linear Unbiased Estimator
- Medical Image Registration
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Ruiz-Alzola, J., Suarez, E., Alberola-Lopez, C., Warfield, S.K., Westin, C.F. (2003). Geostatistical Medical Image Registration. In: Ellis, R.E., Peters, T.M. (eds) Medical Image Computing and Computer-Assisted Intervention - MICCAI 2003. MICCAI 2003. Lecture Notes in Computer Science, vol 2879. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39903-2_109
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DOI: https://doi.org/10.1007/978-3-540-39903-2_109
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