A new total variational regularization method for nonlinear inverse problems in fluorescence molecular tomography
作者: Li LiChen ChenBo Bi
作者单位: 1School of Mathematics, Harbin Institute of Technology, Harbin, 150001, PR China
2School of Mathematics and Statics, Northeast Petroleum University, Daqing, 163318, PR China
刊名: Journal of Computational and Applied Mathematics, 2020, Vol.365
来源数据库: Elsevier Journal
DOI: 10.1016/j.cam.2019.112408
关键词: Ill-posed problemsTotal variational regularizationBregman distanceHomotopy
原始语种摘要: Abstract(#br)Fluorescence molecular tomography (FMT) is an imaging way of in vivo optical imaging, which is widely used in biomedical photon imaging for its higher sensitivity. For years, the propagation process of photons in tissue is simulated based on the equation of radiative transfer. In this work, we analyze an inverse problem in FMT, which uses the reading of body surface detector to reconstruct the optical parameter distribution. We propose a novel total variational regularization method to solve the absorption parameter inversion problem in FMT. The proof of the proposed method is also provided. Finally, numerical experiments demonstrate the feasibility of the proposed method.
全文获取路径: Elsevier  (合作)

  • regularization 正则化
  • variational 变化的
  • tomography 断层x 线摄影
  • inverse 逆的
  • propose 提议
  • imaging 图像形成
  • molecular 分子的
  • demonstrate 说明
  • reconstruct 改建
  • detector 探测器检波器