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Direct reconstruction of PET receptor binding parametric images using a simplified reference tissue model

机译:使用简化的参考组织模型直接重建PET受体结合参数图像

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Molecular imaging using dynamic positron emission tomography (PET) can provide in vivo images of physiologically or biochemically important parameters. Direct reconstruction of parametric images from dynamic PET sinograms is statistically more efficient than the conventional indirect methods, which perform image reconstruction and kinetic modeling in two separate steps. Most existing direct reconstruction methods are derived based on a known blood input function. This paper presents a direct reconstruction algorithm using a simplified reference tissue model, which does not require a blood input function. We have derived a minorization-maximization algorithm to find the penalized maximum likelihood solution. Computer simulations show that the proposed method has better bias-variance tradeoff than the conventional indirect method for estimating parametric images of receptor binding potential using dynamic PET.
机译:使用动态正电子发射断层扫描(PET)的分子成像可以提供具有生理或生物化学重要参数的体内图像。从动态PET正弦图直接重建参数图像在统计上比传统的间接方法更有效,传统的间接方法在两个单独的步骤中执行图像重建和动力学建模。大多数现有的直接重建方法都是​​基于已知的血液输入函数得出的。本文提出了一种使用简化的参考组织模型的直接重建算法,该模型不需要血液输入功能。我们派生了一个最小化最大化算法来找到被惩罚的最大似然解。计算机仿真表明,与使用动态PET估计受体结合潜力的参数化图像的常规间接方法相比,该方法具有更好的偏差-偏差权衡。

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