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Iterative reconstruction for bioluminescence tomography based on an adaptive region shrinking strategy

机译:基于自适应区域收缩策略的生物发光层析成像的迭代重建

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The main challenge of bioluminescence tomography (BLT) is the ill-posed, non-unique nature of the inverse problem. To get reliable reconstruction, permissible source region is a commonly used a priori knowledge in the inverse procedure. In this paper, to accurately reveal 3D distribution of bioluminescent sources from limited boundary measurement, we propose an iterative reconstruction method incorporating adaptive algebraic reconstruction technique (AART) and adaptively shrinking permissible source region. AART algorithm is applied to get the solution without permissible region. Base on the distribution of the solution, we calculate the expectation and the covariance matrix and then derive the parameters for determining a cuboid-shaped region. Simulation experiments on a 3D digital mouse and an in vivo experiment are conducted to validate the feasibility and evaluate the performance of the proposed reconstruction method. The reconstructed results demonstrate the shrinking strategy is helpful for improving the stability of inverse algorithm.
机译:生物发光断层扫描(BLT)的主要挑战是逆问题的弊端,非独特性。为了获得可靠的重建,允许的源区域是常用过程中常用的先验知识。在本文中,为了准确地揭示来自有限的边界测量的生物发光源的3D分布,我们提出了一种迭代重建方法,包括自适应代数重建技术(AART)和自适应地收缩允许源区。 AART算法应用于获取不允许区域的解决方案。基于解决方案的分布,我们计算期望和协方差矩阵,然后导出用于确定长方体形状的参数。进行了3D数字鼠标的仿真实验和体内实验,以验证可行性,评价所提出的重建方法的性能。重建结果证明了收缩策略有助于提高逆算法的稳定性。

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