生物发光断层成像是一种新型光学分子影像技术.基于稀疏正则化的迭代算法在解决重建中病态问题起着关键的作用.将4 种典型的基于l1正则化的迭代算法(内点法、同伦算法、一阶方法和拉格朗日算法)应用于重建过程中,分别进行数学推导,并从重建精度和重建速度方面进行了实验对比和性能评估.实验结果表明尽管4 种方法均能较好地重建出光源位置,但时间代价和重建能量大小上存在差异,据此结果为不同情况下重建算法的选取提出建议.

Bioluminescence tomography (BLT) has recently emerged as a promising preclinical imaging modality.Iterative methods based on sparse regularization play a critical role in solving the ill-posed BLT inverse problem.Four kinds of typical iterative methods based on l1 regularization were briefly introduced and applied to reconstruct the bioluminescent source location and intensity,which include interior-point methods,homotopy methods,firstorder methods,and augmented Lagrangian methods.Numerical experiments on a digital inhomogeneous mouse model and in vivo experiments were conducted to evaluate the performance of these methods in terms of localization accuracy,reconstructed intensity and power.