Abstract
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.
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© 2004 Springer-Verlag Berlin Heidelberg
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Crum, W.R., Griffin, L.D., Hawkes, D.J. (2004). Automatic Estimation of Error in Voxel-Based Registration. In: Barillot, C., Haynor, D.R., Hellier, P. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004. MICCAI 2004. Lecture Notes in Computer Science, vol 3216. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30135-6_100
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DOI: https://doi.org/10.1007/978-3-540-30135-6_100
Publisher Name: Springer, Berlin, Heidelberg
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