School of Computer Science and Technology and the Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi’an 710071, China.
IEEE Trans Biomed Eng. 2010 Oct;57(10):2583-6. doi: 10.1109/TBME.2010.2059024. Epub 2010 Jul 15.
Bioluminescence tomography (BLT) is an inherent ill-posed inverse problem to reconstruct the internal source in 3-D with limited measurements on the external surface. In most BLT studies so far, a relatively small permissible source region or multispectral approach is typically used to enhance the stability or quality of the solution. In this letter, considering the sparsity characteristic of the light source, BLT is reformulated as a least absolute shrinkage and selection operator (LASSO) problem with l(1) regularization, and then, a fast reconstruction algorithm named as stagewise fast LASSO is proposed for solving this problem. Numerical simulations of a 3-D mouse atlas under different noise levels demonstrate that the proposed algorithm is robust against measurement noise, and it can achieve high computational efficiency and accurate localization of source even without any permissible region constraint.
生物发光断层成像（BLT）是一种固有的不适定反问题，需要在外表面的有限测量下重建 3-D 内部源。在迄今为止的大多数 BLT 研究中，通常使用相对较小的允许源区域或多光谱方法来增强解决方案的稳定性或质量。在这封信中，考虑到光源的稀疏特性，BLT 被重新表述为具有 l(1)正则化的最小绝对值收缩和选择算子（LASSO）问题，然后提出了一种名为分阶段快速 LASSO 的快速重建算法来解决这个问题。在不同噪声水平下的 3-D 鼠标图谱的数值模拟表明，所提出的算法对测量噪声具有鲁棒性，即使没有任何允许区域约束，它也可以实现高计算效率和源的准确定位。
