title: Fast and robust reconstruction for fluorescence molecular tomography via a sparsity adaptive subspace pursuit method.
abstract: Fluorescence molecular tomography (FMT), as a promising imaging modality, can three-dimensionally locate the specific tumor position in small animals. However, it remains challenging for effective and robust reconstruction of fluorescent probe distribution in animals. In this paper, we present a novel method based on sparsity adaptive subspace pursuit (SASP) for FMT reconstruction. Some innovative strategies including subspace projection, the bottom-up sparsity adaptive approach, and backtracking technique are associated with the SASP method, which guarantees the accuracy, efficiency, and robustness for FMT reconstruction. Three numerical experiments based on a mouse-mimicking heterogeneous phantom have been performed to validate the feasibility of the SASP method. The results show that the proposed SASP method can achieve satisfactory source localization with a bias less than 1mm; the efficiency of the method is much faster than mainstream reconstruction methods; and this approach is robust even under quite ill-posed condition. Furthermore, we have applied this method to an in vivo mouse model, and the results demonstrate the feasibility of the practical FMT application with the SASP method.
authors.affiliation: Key Laboratory of Molecular Imaging of Chinese Academy of Sciences, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
authors.forename: Jinzuo
authors.initials: J
authors.lastname: Ye
authors.affiliation: Key Laboratory of Molecular Imaging of Chinese Academy of Sciences, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
authors.forename: Chongwei
authors.initials: C
authors.lastname: Chi
authors.affiliation: Chengdu Institute of Huawei Technologies Co. Ltd., Chengdu, Sichuan 611731, China.
authors.forename: Zhenwen
authors.initials: Z
authors.lastname: Xue
authors.affiliation: Key Laboratory of Molecular Imaging of Chinese Academy of Sciences, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
authors.forename: Ping
authors.initials: P
authors.lastname: Wu
authors.affiliation: Beijing Jiaotong University, School of Computer and Information Technology, Department of Biomedical Engineering, Beijing 100044, China.
authors.forename: Yu
authors.initials: Y
authors.lastname: An
authors.affiliation: Beijing Jiaotong University, School of Computer and Information Technology, Department of Biomedical Engineering, Beijing 100044, China.
authors.forename: Han
authors.initials: H
authors.lastname: Xu
authors.affiliation: Northeastern University, Sino-Dutch Biomedical and Information Engineering School, Shenyang, Liaoning 110819, China.
authors.forename: Shuang
authors.initials: S
authors.lastname: Zhang
authors.affiliation: Key Laboratory of Molecular Imaging of Chinese Academy of Sciences, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
authors.forename: Jie
authors.initials: J
authors.lastname: Tian
keywords: (100.3010) Image reconstruction techniques; (100.3190) Inverse problems; (110.6955) Tomographic imaging; (170.3660) Light propagation in tissues; (170.3880) Medical and biological imaging; (290.1990) Diffusion; (290.7050) Turbid media