Modified forward model for eliminating the time-varying impact in fluorescence molecular tomography.
In conventional fluorescence molecular tomography, the distribution of fluorescent contrast agents is reconstructed with the assumption of constant concentration during data acquisition for each image frame. However, the concentration of fluorescent contrast target is usually time-varying in experiments or in-vivo studies. In this case, the reconstruction methods cannot be directly applied to the fluorescence measurements without considering the time-varying effects of concentration. We propose a modified forward model by dividing the fluorescence yield distribution into two parts: one is a constant representing the spatial distribution of the fluorescent target and the other is an impact factor representing the effects of the concentration change and other possible factors. By extracting spatial distribution information from the reconstruction result, the location and volume of the fluorescent target can be obtained accurately. Both simulation and phantom experiments are carried out and the results indicate that, by using the modified forward model, the quality of reconstruction could be significantly improved in terms of accurate localization and strong anti-noise ability.
Tsinghua University, School of Medicine, Department of Biomedical Engineering, Beijing 100084, China.
Wei
W
He
Tsinghua University, School of Medicine, Department of Biomedical Engineering, Beijing 100084, China.
Guanglei
G
Zhang
Tsinghua University, School of Medicine, Department of Biomedical Engineering, Beijing 100084, China.
Huangsheng
H
Pu
Tsinghua University, School of Medicine, Department of Biomedical Engineering, Beijing 100084, China.
Fei
F
Liu
Xidian University, School of Life Sciences and Technology, Xi'an 710071, China.
Xu
X
Cao
Tsinghua University, School of Medicine, Department of Biomedical Engineering, Beijing 100084, ChinacTsinghua University, Center for Biomedical Imaging Research, Beijing 100084, China.
Jianwen
J
Luo
Tsinghua University, School of Medicine, Department of Biomedical Engineering, Beijing 100084, China.
Jing
J
Bai
D000818:Animals; D003198:Computer Simulation; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007208:Indocyanine Green / Q000737:chemistry / Q000493:pharmacokinetics; D008099:Liver / Q000737:chemistry / Q000378:metabolism; D008168:Lung / Q000737:chemistry / Q000378:metabolism; D051379:Mice; D061848:Optical Imaging / Q000379:methods*; D019047:Phantoms, Imaging; D014054:Tomography / Q000379:methods*
D007208:Indocyanine Green