Image registration driven by similarity measures that are simple functions of voxel intensities is now widely used in medical applications. Validation of registration in general remains an unsolved problem; measurement of registration error usually requires manual intervention. This paper presents a general framework for automatically estimating the scale of spatial registration error. The error is estimated from a statistical analysis of the scale-space of a residual image constructed with the same assumptions used to choose the image similarity measure. The analysis identifies the most significant scale of voxel clusters in the residual image for a coarse estimate of error. A partial volume correction is then applied to estimate finer and sub-voxel displacements. We describe the algorithm and present the results of an evaluation on rigid-body registrations where the ground-truth error is known. Automated measures may ultimately provide a useful estimate of the scale of registration error. © Springer-Verlag Berlin Heidelberg 2004.
CITATION STYLE
Crum, W. R., Griffin, L. D., & Hawkes, D. J. (2004). Automatic estimation of error in voxel-based registration. In Lecture Notes in Computer Science (Vol. 3216, pp. 821–828). Springer Verlag. https://doi.org/10.1007/978-3-540-30135-6_100
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