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There exist a wide variety of time sensitive contexts (e.g. image-guided neurosurgery (IGNS)), whereby image registration is required to be both fast and accurate if it is to be adopted clinically. Many sampling techniques have been proposed to speed up the registration process but these often come at the expense of accuracy (e.g. random). In this paper, we describe a fast and accurate multi-modal...
In this paper, we propose a new multi-scale technique for multi-modal image registration based on the alignment of selected gradient orientations of reduced uncertainty. We show how the registration robustness and accuracy can be improved by restricting the evaluation of gradient orientation alignment to locations where the uncertainty of fixed image gradient orientations is minimal, which we formally...
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