Intelligent Medical Research Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
J Biophotonics. 2011 Nov;4(11-12):824-39. doi: 10.1002/jbio.201100049. Epub 2011 Oct 11.
As a novel molecular imaging technology, bioluminescence tomography (BLT) has become an important tool for biomedical research in recent years, which can perform a quantitative reconstruction of an internal light source distribution with the scattered and transmitted bioluminescent signals measured on the external surface of a small animal. However, BLT is severely ill-posed because of complex photon propagation in the biological tissue and limited boundary measured data with noise. Therefore, sufficient a priori knowledge should be fused for the uniqueness and stability of BLT solution. Permissible source region strategy and spectrally resolved measurements are two kinds of a priori knowledge commonly used in BLT reconstruction. This paper compares their performance with simulation and in vivo heterogeneous mouse experiments. In order to improve the efficiency of large-scale source restoration, this paper introduces an efficient iterative shrinkage thresholding method that not only has faster convergence rate but also has better reconstruction accuracy than the modified Newton-type optimization approach. Finally, a discussion of these two kinds of a priori knowledge is given based on the comparison results.
作为一种新型的分子成像技术，生物发光断层成像（BLT）近年来已成为生物医学研究的重要工具，它可以通过测量小动物外表面上的散射和透射生物发光信号，对内部光源分布进行定量重建。然而，由于生物组织中复杂的光子传播和有限的边界测量数据存在噪声，BLT 存在严重的不适定性。因此，应该融合足够的先验知识，以确保 BLT 解的唯一性和稳定性。允许的源区域策略和光谱分辨测量是 BLT 重建中常用的两种先验知识。本文通过模拟和体内异质小鼠实验比较了它们的性能。为了提高大规模源重建的效率，本文引入了一种高效的迭代收缩阈值方法，该方法不仅具有更快的收敛速度，而且比改进的牛顿型优化方法具有更好的重建精度。最后，根据比较结果对这两种先验知识进行了讨论。
