Extended global optimization strategy for rigid 2D/3D image registration
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Optimized hierarchical block matching for fast and accurate image registration
Image Communication
Disparity-based space-variant image deblurring
Image Communication
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We present an automatic sub-pixel registration algorithm that minimizes the mean square difference of intensities between a reference and a test data set (volumes or images). It uses spline processing, is based on a coarse-to-fine pyramid strategy, and performs minimization according to a variation of the iterative Marquardt-Levenberg (1963) scheme. The geometric deformation model is a general affine transformation that one may optionally restrict to a rigid-body (isometric scale, rotation and translation), procrustean (rotation and translation) or translational case; it also includes an optional parameter for the linear adaptation of intensity. We present several PET and fMRI experiments and show that this algorithm provides excellent results. We conclude that the multi-resolution refinement strategy is faster and more robust than a comparable single-scale one.