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Organ concentration quantification for small animal PET images by registration with a statistical mouse atlas

机译:通过统计小鼠图谱注册,对小动物PET图像进行器官浓度定量

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This study focuses on quantification of probe concentration in major organs of small animal micro-PET images. In order to delineate organ ROIs, a statistical mouse atlas is registered to the micro-PET image. This statistical atlas is trained from 22 organ-labeled micro-CT images using Principle Component Analysis (PCA). By tuning the shape-controlling parameters of the atlas, we are able to adapt the atlas anatomy to fit the individual subject of the micro-PET image. To reduce the spillover effect, voxel confidence values are computed and are used to calculate confidence-weighted mean concentration of each organ. Experiments were performed on both simulated images and in-vivo micro-PET emission images. Results showed that the registration-based yielded comparable accuracy to the quantification based-on ground truth organ regions, and the confidence-weighted averaging obtains more accurate results than direct averaging of organ concentrations.
机译:这项研究的重点是对小动物微型PET影像的主要器官中的探针浓度进行定量。为了描绘器官ROI,将统计的小鼠图谱注册到微型PET图像。使用主成分分析(PCA)从22个器官标记的微型CT图像中训练该统计图集。通过调整地图集的形状控制参数,我们能够调整地图集的解剖结构以适合微型PET图像的各个对象。为了减少溢出效应,将计算体素置信值,并将其用于计算每个器官的置信度加权平均浓度。在模拟图像和体内微型PET发射图像上均进行了实验。结果表明,基于配准的结果与基于地面真实器官区域的定量结果具有可比的准确性,并且置信加权平均比直接平均器官浓度获得更准确的结果。

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