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基于改进谱投影梯度算法的X射线发光断层成像 被引量:6

X-ray luminescence computed tomography based on improved spectral projected gradient algorithm
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摘要 X射线发光断层成像(XLCT)是一种可同时获得解剖结构和功能信息的新型分子影像技术,在早期肿瘤检测与放疗方面具有重要应用潜力,但由于测量信息少,成像模型复杂等原因,其断层重建一直是挑战性难题。本文采用非单调Barzilai-Borwein梯度(NBBG)算法来求解重建问题目标函数。每次迭代中,谱投影梯度方法近似为L1范数约束的最小二乘问题。Barzilai-Borwein梯度法获得相应的更新方向,提高算法的收敛速度。采用非单调性线性搜索策略构建最优步长,保证全局收敛性。通过将Barzilai-Borwein梯度法和非单调性搜索结合,在保证全局收敛的同时,克服了选取精确步长带来较大计算量的缺点。数值仿真实验和物理实验得到的基于NBBG算法的单光原重建位置误差分别为0.68和0.94mm,与分裂增广拉格朗日收缩算法(SALSA)相比,本文方法在重建精度、鲁棒性和重建效率等方面都获得了较优的结果。 X-ray Luminescence Computed Tomography (XLCT),a novel imaging technique which can obtain anatomical structure and functional information simultaneously,has an important application prospect in early tumor detection and radiotherapy.But due to the less measurement and complex imaging model,the tomography reconstruction always is a challenging problem.This paper presents a gradient algorithm based on Non-monotone Barzilai-Borwein(NBBG) to obtain the optimal solution of the objective.In each iteration,a spectral gradient-projection method approximately was minimized as a least-squares problem with an explicit L1-regularized constraint.The Barzilai-Borwein was employed to get the appropriate updating direction,further to improve the convergence speed of the proposed method.In addition,anonmonotone line search strategy was applied to build the optimal step length,which guarantees global convergence.The combination of nonmonotone line Barzilai-Borwein step length search strategy with spectral projected gradient method not only can ensure the global convergence,but also can reduce the computational cost of selecting exact step-size.From numerical simulation experiments and the physical experiment,the Location Errors (LE) of single target reconstruction based on NBBG are 0.68 and 0.94 mm respectively.Compared with Split Augmented Lagrangian Shrinkage Algorithm (SALSA),NBBG can obtain better results in terms of LE,robustness and efficiency.
出处 《光学精密工程》 EI CAS CSCD 北大核心 2017年第1期42-49,共8页 Optics and Precision Engineering
基金 国家自然科学基金资助项目(No.61372046 No.11571012 No.61640418) 中国博士后科学基金资助项目 陕西省科技计划资助项目(No.2015KW-002) 陕西省自然科学研究计划资助项目(No.2015JM6322) 陕西省教育厅基金资助项目(No.15JK1726) 陕西省教育厅专项科研计划资助项目(No.14JK1578 No.16JK1772) 西北大学自然科学基金资助项目(No.338020006 No.338050003) 西北大学研究生创新项目(No.YZZ15096)
关键词 光学分子影像 X射线发光断层成像(XLCT) 图像重建 梯度算法 optical molecular imaging X-ray Luminescence Computed Tomography(XLCT) image reconstruction gradient algorithm
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  • 1贺小伟.生物发光断层成像中光源重建逆问题研究[D].西安:西安电子科技大学,2011.
  • 2WEISSLEDER R, PITTET J M. Imaging in the era of molecular oncology[J]. Nature, 2008,452 : 580-589.
  • 3YU J J,CHENG J X,HOU Y Q,et al.. Sparse re- construction for fluorescence molecular tomography via a fast iterative algorithm[J]. Journal of Innova- tive Optical Health Sciences, 2014,7 (3) .. 488-488.
  • 4PRATX G, CARPENTER C M,SUN C,et al.. X- ray luminescence computed tomography via selective excitation., a feasibility study[J]. IEEE Transactions on Medical Imaging, 2010,29 (12) : 1992-1999.
  • 5CONG W, SHEN H, WANG G. Spectrally resolving and scattering-compensated X-ray luminescence/flu- orescence computed tomography[J]. Journal of Biomedical Optics ,2011,16(6), :066014-1-7.
  • 6LI C, ANULFO M D, SIMON R C, et al.. Numerical simulation of X-ray luminescence optical tomography for small-animal imaging [J]. Journal of Biomedical Optics, 2011,19 (4) : 046002-1-10.
  • 7CHEN D M,ZHU S,YI H J,et al.. Cone beam X ray luminescence computed tomography: a feasibility study[J]. Medical Physics, 2013,40 (3) : 031111- 1-14.
  • 8LIU X, LIAO Q, WANG H. Fast X-ray luminescence computed tomography imaging [J]. IEEE Transac tions on Biomedical Engineering, 2014, 61 (6): 1621-1627.
  • 9PRATX G, CARPENTER C M,SUN C,et al.. Tomographic molecular imaging of X ray excitable nanoparticles[J]. Optics Letters, 2010,35 (20): 3345-334,7.
  • 10周晓青,王倩,范颖,秦转萍,刘明,高峰,赵会娟.面向大数据量的扩散光层析成像快速重建算法[J].光学学报,2013,33(4):156-165. 被引量:3

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