Sparse reconstruction for quantitative bioluminescence tomography based on the incomplete variables truncated conjugate gradient method
Sparse reconstruction for quantitative bioluminescence tomography based on the incomplete variables truncated conjugate gradient method
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DOI：
10.1364/oe.18.024825
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发表时间：
2010-11-22
期刊：
影响因子：
3.8
通讯作者：
Tian, Jie
中科院分区：
文献类型：
--
作者：
He, Xiaowei;Liang, Jimin;Tian, Jie
提出了一种用于生物发光层析成像(BLT)的不完全变量截断共轭梯度(IVTCG)方法。考虑到BLT场景中光源稀疏和表面测量不足的特点，我们将稀疏诱导(L(1)范数)正则化项和二次误差项结合起来求解逆问题。通过限制每次迭代更新的变量数量，并结合变量分裂策略来更有效地找到搜索方向，即使在没有允许源区域的先验信息和多光谱测量的情况下，它也可以获得快速和稳定的源重建。在小鼠图谱上的数值实验验证了该方法的有效性。小鼠体内实验结果进一步表明，它有可能成为一种实用的BLT系统。(C)2010年美国光学学会
In this paper, we present an incomplete variables truncated conjugate gradient (IVTCG) method for bioluminescence tomography (BLT). Considering the sparse characteristic of the light source and insufficient surface measurement in the BLT scenarios, we combine a sparseness-inducing (l(1) norm) regularization term with a quadratic error term in the IVTCG-based framework for solving the inverse problem. By limiting the number of variables updated at each iterative and combining a variable splitting strategy to find the search direction more efficiently, it obtains fast and stable source reconstruction, even without a priori information of the permissible source region and multispectral measurements. Numerical experiments on a mouse atlas validate the effectiveness of the method. In vivo mouse experimental results further indicate its potential for a practical BLT system. (C) 2010 Optical Society of America