P. Hellier, C. Barillot, E. Mémin, P. Pérez. Hierarchical estimation of a dense deformation field for 3D robust registration. IEEE Transaction on Medical Imaging, 20(5):388-402, May 2001.
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In this paper we describe a new method for medical image registration. The registration is formulated as a minimization problem involving robust estimators. We propose an efficient hierarchical optimization ramework which is both multiresolution and multigrid. An anatomical segmentation of the cortex is introduced in the adaptive partitioning of the volume on which the multigrid minimization is based. This allows to limit the estimation to the areas of interest, to accelerate the algorithm, and to refine the estimation in specified areas. At each stage of the hierarchical estimation, we refine current estimate by seeking a piecewise affine model for the incremental deformation field. The performances of this method are numerically evaluated on simulated data and its benefits and robustness are shown on a database of 18 real acquisitions
@article{Hellier01b,
Author = {Hellier, P. and Barillot, C. and Mémin, E. and Pérez, P.},
Title = {Hierarchical estimation of a dense deformation field for 3D robust registration},
Journal = {IEEE Transaction on Medical Imaging},
Volume = {20},
Number = {5},
Pages = {388--402},
Month = {May},
Year = {2001}
}
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