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The analysis of multi-timepoint whole-body small animal CT data is greatly complicated by the varying posture of the subjectat different timepoints. Due to these variations, correctly relating and comparing corresponding regions of interest is challenging.In addition, occlusion may prevent effective visualization of these regions of interest. To address these problems, we have developeda method that fully automatically maps the data to a standardized layout of sub-volumes, based on an articulated atlas registration.We have dubbed this process articulated planar reformation, or APR. A sub-volume can be interactively selected for closer inspectionand can be compared with the corresponding sub-volume at the other timepoints, employing a number of different comparative visualization approaches. We provide an additional tool that highlights possibly interesting areas based on the change of bone densitybetween timepoints. Furthermore we allow visualization of the local registration error, to give an indication of the accuracy of theregistration. We have evaluated our approach on a case that exhibits cancer-induced bone resorption.
small animal imaging, comparative visualization, multi-timepoint, molecular imaging, articulated planar reformation

J. Dijkstra et al., "Articulated Planar Reformation for Change Visualization in Small Animal Imaging," in IEEE Transactions on Visualization & Computer Graphics, vol. 16, no. , pp. 1396-1404, 2010.
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