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Comparative studies of lp-regularization-based reconstruction algorithms for bioluminescence tomography

机译:基于l p 正则化的生物发光层析成像重建算法的比较研究

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Inverse source reconstruction is the most challenging aspect of bioluminescence tomography (BLT) because of its ill-posedness. Although many efforts have been devoted to this problem, so far, there is no generally accepted method. Due to the ill-posedness property of the BLT inverse problem, the regularization method plays an important role in the inverse reconstruction. In this paper, six reconstruction algorithms based on lp regularization are surveyed. The effects of the permissible source region, measurement noise, optical properties, tissue specificity and source locations on the performance of the reconstruction algorithms are investigated using a series of single source experiments. In order to further inspect the performance of the reconstruction algorithms, we present the double sources and the in vivo mouse experiments to study their resolution ability and potential for a practical heterogeneous mouse experiment. It is hoped to provide useful guidance on algorithm development and application in the related fields.
机译:逆源重建由于其不适性而成为生物发光层析成像(BLT)最具挑战性的方面。尽管已经为解决这个问题做出了许多努力,但是到目前为止,还没有普遍接受的方法。由于BLT反问题的不适定性,正则化方法在反重构中起着重要作用。本文研究了六种基于lp正则化的重构算法。使用一系列单源实验研究了允许的源区域,测量噪声,光学特性,组织特异性和源位置对重建算法性能的影响。为了进一步检查重构算法的性能,我们提出了双重来源和体内小鼠实验,以研究其分辨能力和进行实际异种小鼠实验的潜力。希望为算法开发和相关领域的应用提供有益的指导。

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