title: Automatic selection of regularization parameters for dynamic fluorescence molecular tomography: a comparison of L-curve and U-curve methods.
abstract: Dynamic fluorescence molecular tomography (FMT) is a promising technique for the study of the metabolic process of fluorescent agents in the biological bodyin vivo, and the quality of the parametric images relies heavily on the accuracy of the reconstructed FMT images. In typical dynamic FMT implementations, the imaged object is continuously monitored for more than 50 minutes. During each minute, a set of the fluorescent measurements is acquired and the corresponding FMT image is reconstructed. It is difficult to manually set the regularization parameter in the reconstruction of each FMT image. In this paper, the parametric images obtained with the L-curve and U-curve methods are quantitatively evaluated through numerical simulations, phantom experiments andin vivoexperiments. The results illustrate that the U-curve method obtains better accuracy, stronger robustness and higher noise-resistance in parametric imaging. Therefore, it is a promising approach to automatic selection of the regularization parameters for dynamic FMT.
authors.affiliation: Tsinghua University, School of Medicine, Department of Biomedical Engineering, Beijing 100084, China.
authors.forename: Maomao
authors.initials: M
authors.lastname: Chen
authors.affiliation: Tsinghua University, School of Medicine, Department of Biomedical Engineering, Beijing 100084, China.
authors.forename: Han
authors.initials: H
authors.lastname: Su
authors.affiliation: Tsinghua University, School of Medicine, Department of Biomedical Engineering, Beijing 100084, China.
authors.forename: Yuan
authors.initials: Y
authors.lastname: Zhou
authors.affiliation: Tsinghua University, School of Medicine, Department of Biomedical Engineering, Beijing 100084, China.
authors.forename: Chuangjian
authors.initials: C
authors.lastname: Cai
authors.affiliation: Tsinghua University, School of Medicine, Department of Biomedical Engineering, Beijing 100084, China.
authors.forename: Dong
authors.initials: D
authors.lastname: Zhang
authors.affiliation: Tsinghua University, School of Medicine, Department of Biomedical Engineering, Beijing 100084, China; Tsinghua University, Center for Biomedical Imaging Research, Beijing, 100084, China.
authors.forename: Jianwen
authors.initials: J
authors.lastname: Luo
keywords: (100.3190) Inverse problems; (170.3010) Image reconstruction techniques; (170.3880) Medical and biological imaging; (170.6960) Tomography