连续化原对偶有效集的生物发光断层成像算法  

Bioluminescence Tomography Algorithm Based on Primal Dual Active Set with Continuation

作　　者：余景景[1] 李玲蔚 唐沁 Yu Jingjing;Li Lingwei;Tang Qin(School of Physics and Information Technology,Shaanxi Normal University,Xi'an,Shaanxi 710119,China)

机构地区：[1]陕西师范大学物理学与信息技术学院,陕西西安710119

出　　处：《中国激光》2021年第7期157-167,共11页Chinese Journal of Lasers

基　　金：国家自然科学基金(11871321);陕西省国际科技合作与交流计划项目(2018KW-066)。

摘　　要：为克服生物发光断层成像(BLT)的不适定性,获得稳定的光源重建结果,本文提出了一种基于连续化原对偶有效集(PDASC)的多光谱BLT重建算法,该算法将原对偶有效集算法(PDAS)与连续化技术相结合,可以自动调节正则化参数,从而获得全局最优解。多组数字鼠仿真实验验证了该算法的有效性和稳定性,且与原对偶有效集算法、硬阈值追踪法(HTP)相比,所提PDASC重建算法在不同光源设置下的各量化指标均表现更优,在体小鼠实验结果进一步证明了该算法在实际应用中的潜力。Objective To overcome the ill-posedness of the bioluminescence tomography(BLT)reconstruction problem and obtain stable reconstruction results,researchers combined different prior information and regularization techniques to design various reconstruction algorithms.Among them,biological tissue structure information,a permissible source region,multi-spectral measurement information,and light source distribution sparseness are priori information widely used in reconstruction.The reconstruction algorithm based on regularization is divided into convex and non-convex optimization methods according to whether the objective function is non-convex.Although the regularization models of these reconstruction algorithms are different,the regularization parameter play a significant role in the reconstruction process,which directly affects the reconstructed image quality.Thus,the selection of the optimal parameters has always been a challenging problem for research.In this study,we proposed a multi-spectral BLT reconstruction method based on primal dual active set with continuation(PDASC)algorithm.The proposed method combines the primal dual active set(PDAS)algorithm with continuity technology,which can automatically adjust the regularization parameter to obtain a globally optimal solution.Methods In this study,the iterative algorithm,PDASC,contains inner and outer iterations.The inner iteration part is the PDAS algorithm,which determines the active set based on the primal and dual variables.It then updates the primal and dual variables by solving the least square problem of the active set.The outer iteration combines the continuity technology of the regularization parameter.In the PDASC algorithm,the stopping criterion in the continuity technology directly affects the determination of the regularization parameter.Thus,it is essential to select an appropriate stopping criterion.If the noise level is known,we can choose the deviation principle as the stopping criterion.However,it is not easy to accurately estimate the noise leve

关 键 词：医用光学 生物发光断层成像 连续化原对偶有效集算法 光源重建 稀疏重建 逆问题 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] Q632[自动化与计算机技术—计算机科学与技术]