title: Reconstruction of fluorescence molecular tomography via a nonmonotone spectral projected gradient pursuit method.
abstract: Fluorescence molecular tomography (FMT) is a promising imaging technique in preclinical research, enabling three-dimensional location of the specific tumor position for small animal imaging. However, FMT presents a challenging inverse problem that is quite ill-posed and ill-conditioned. Thus, the reconstruction of FMT faces various challenges in its robustness and efficiency. We present an FMT reconstruction method based on nonmonotone spectral projected gradient pursuit (NSPGP) with /₁-norm optimization. At each iteration, a spectral gradient-projection method approximately minimizes a least-squares problem with an explicit one-norm constraint. A nonmonotone line search strategy is utilized to get the appropriate updating direction, which guarantees global convergence. Additionally, the Barzilai-Borwein step length is applied to build the optimal step length, further improving the convergence speed of the proposed method. Several numerical simulation studies, including multisource cases as well as comparative analyses, have been performed to evaluate the performance of the proposed method. The results indicate that the proposed NSPGP method is able to ensure the accuracy, robustness, and efficiency of FMT reconstruction. Furthermore, an in vivo experiment based on a heterogeneous mouse model was conducted, and the results demonstrated that the proposed method held the potential for practical applications of FMT.
authors.affiliation: Chinese Academy of Sciences, Key Laboratory of Molecular Imaging of Chinese Academy of Sciences, Institute of Automation, No.95 Zhongguancun East Road, Haidian District, Beijing 100190, China.
authors.forename: Jinzuo
authors.initials: J
authors.lastname: Ye
authors.affiliation: Chinese Academy of Sciences, Key Laboratory of Molecular Imaging of Chinese Academy of Sciences, Institute of Automation, No.95 Zhongguancun East Road, Haidian District, Beijing 100190, China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Du
authors.affiliation: Beijing Jiaotong University, School of Computer and Information Technology, Department of Biomedical Engineering, No.3 Shangyuancun, Haidian District, Beijing 100044, China.
authors.forename: Yu
authors.initials: Y
authors.lastname: An
authors.affiliation: Chinese Academy of Sciences, Key Laboratory of Molecular Imaging of Chinese Academy of Sciences, Institute of Automation, No.95 Zhongguancun East Road, Haidian District, Beijing 100190, China.
authors.forename: Chongwei
authors.initials: C
authors.lastname: Chi
authors.affiliation: Chinese Academy of Sciences, Key Laboratory of Molecular Imaging of Chinese Academy of Sciences, Institute of Automation, No.95 Zhongguancun East Road, Haidian District, Beijing 100190, China.
authors.forename: Jie
authors.initials: J
authors.lastname: Tian
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D021621:Imaging, Three-Dimensional / Q000379:methods*; D051379:Mice; D008807:Mice, Inbred BALB C; D064847:Multimodal Imaging; D061848:Optical Imaging / Q000379:methods*; D014054:Tomography / Q000379:methods*