title: Efficient reconstruction method for L1 regularization in fluorescence molecular tomography.
abstract: Fluorescence molecular tomography (FMT) is a promising technique for in vivo small animal imaging. In this paper, the sparsity of the fluorescent sources is considered as the a priori information and is promoted by incorporating L1 regularization. Then a reconstruction algorithm based on stagewise orthogonal matching pursuit is proposed, which treats the FMT problem as the basis pursuit problem. To evaluate this method, we compare it to the iterated-shrinkage-based algorithm with L1 regularization. Numerical simulations and physical experiments show that the proposed method can obtain comparable or even slightly better results. More importantly, the proposed method was at least 2 orders of magnitude faster in these experiments, which makes it a practical reconstruction algorithm.
authors.affiliation: Medical Image Processing Group, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
authors.forename: Dong
authors.initials: D
authors.lastname: Han
authors.forename: Xin
authors.initials: X
authors.lastname: Yang
authors.forename: Kai
authors.initials: K
authors.lastname: Liu
authors.forename: Chenghu
authors.initials: C
authors.lastname: Qin
authors.forename: Bo
authors.initials: B
authors.lastname: Zhang
authors.forename: Xibo
authors.initials: X
authors.lastname: Ma
authors.forename: Jie
authors.initials: J
authors.lastname: Tian
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D003952:Diagnostic Imaging; D005453:Fluorescence; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008962:Models, Theoretical; D009369:Neoplasms / Q000175:diagnosis; D019047:Phantoms, Imaging; D014054:Tomography / Q000379:methods*