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Organ Concentration Quantification for Small Animal PET Images by Registration with a Statistical Mouse Atlas

机译:通过与统计鼠标图集的登记的小动物PET图像器官浓度量化

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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:本研究重点研究了小动物微宠物图像主要器官探针浓度的定量。为了描绘器官ROI,将统计鼠标图集注册到微宠物图像。使用原理成分分析(PCA),该统计阿特拉斯从22个器官标记的微CT图像训练。通过调整图表的形状控制参数,我们能够适应地图集解剖结构以适应微宠物图像的个体主体。为了减少溢出效应,计算体素置信度值,并用于计算每个器官的置信均匀平均浓度。在模拟图像和体内微宠物发射图像上进行实验。结果表明,基于注册的基于对地面真理器官区的定量产生的可比精度,置信度平均比器官浓度的直接平均获得更准确的效果。

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