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Investigation of motion-corrected VOI reconstruction for freely moving small animals with microPET

机译:用microPET对运动自如的小动物进行运动校正的VOI重建的研究

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We are developing an imaging system that enables the brain of a freely moving animal to be imaged with microPET while simultaneously observing its behaviour. Towards this end, we investigated the feasibility of reconstructing a motion-tracked volume of interest (VOI) in the presence of an extraneous activity compartment with unknown motion. A dual phantom study was performed to simulate movements of a freely moving animal. Both phantoms were moved through discrete positions but only one phantom (representing the head) was tracked. The multiple acquisition frames (MAF) and LOR rebinning methods were applied based on the measured motion of the tracked phantom. We also investigated alternative approaches that are hybrids of these two methods. We found that LOR rebinning causes up to 90% ‘lost events’ (events that would have been measured had motion not occurred) when applied to a freely moving target and this fraction can be significantly reduced using the hybrid approaches, resulting in improved image quality. The MAF-based motion correction yields good results but is not practical for unconstrained motion due to the assumption of no motion within each time segment. We conclude that it is feasible to reconstruct a target VOI in the presence of extraneous activity whose motion is unknown, provided the target motion is accurately tracked.
机译:我们正在开发一种成像系统,该系统可以使用microPET对自由移动的动物的大脑进行成像,同时观察其行为。为此,我们研究了在存在未知运动的无关活动隔室的情况下重建运动跟踪的感兴趣体积(VOI)的可行性。进行了双重幻像研究,以模拟自由移动的动物的运动。两种体模都通过不连续的位置移动,但只跟踪了一个体模(代表头部)。基于跟踪的体模的测量运动,应用了多个采集帧(MAF)和LOR重新组合方法。我们还研究了这两种方法的混合使用的替代方法。我们发现,将LOR重新绑定应用于自由移动的目标时,最多会造成90%的“丢失事件”(如果没有运动,本来可以测量的事件),并且使用混合方法可以显着降低这一比例,从而改善了图像质量。基于MAF的运动校正可产生良好的结果,但由于假设每个时间段内没有运动,因此对于无约束运动不切实际。我们得出结论,在目标运动被未知的情况下,如果目标运动被精确跟踪,则在目标运动未知的情况下重建目标VOI是可行的。

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