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Cheng J, Zhang P, Liu F, Liu J, Hui H, Tian J, Luo J. Encoder-decoder deep learning network for simultaneous reconstruction of fluorescence yield and lifetime distributions. BIOMEDICAL OPTICS EXPRESS 2022; 13:4693-4705. [PMID: 36187270 PMCID: PMC9484427 DOI: 10.1364/boe.466349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 08/03/2022] [Accepted: 08/03/2022] [Indexed: 06/16/2023]
Abstract
A time-domain fluorescence molecular tomography in reflective geometry (TD-rFMT) has been proposed to circumvent the penetration limit and reconstruct fluorescence distribution within a 2.5-cm depth regardless of the object size. In this paper, an end-to-end encoder-decoder network is proposed to further enhance the reconstruction performance of TD-rFMT. The network reconstructs both the fluorescence yield and lifetime distributions directly from the time-resolved fluorescent signals. According to the properties of TD-rFMT, proper noise was added to the simulation training data and a customized loss function was adopted for self-supervised and supervised joint training. Simulations and phantom experiments demonstrate that the proposed network can significantly improve the spatial resolution, positioning accuracy, and accuracy of lifetime values.
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Affiliation(s)
- Jiaju Cheng
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Peng Zhang
- Department of Biomedical Engineering, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Fei Liu
- Beijing Advanced Information and Industrial Technology Research Institute, Beijing Information Science and Technology University, Beijing 100192, China
| | - Jie Liu
- Department of Biomedical Engineering, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
| | - Hui Hui
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Jie Tian
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing 100191, China
| | - Jianwen Luo
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
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Cheng J, Zhang P, Cai C, Gao Y, Liu J, Hui H, Tian J, Luo J. Depth-recognizable time-domain fluorescence molecular tomography in reflective geometry. BIOMEDICAL OPTICS EXPRESS 2021; 12:3806-3818. [PMID: 34457381 PMCID: PMC8367269 DOI: 10.1364/boe.430235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 05/27/2021] [Accepted: 05/27/2021] [Indexed: 06/13/2023]
Abstract
Conventional fluorescence molecular tomography (FMT) reconstruction requires photons penetrating the whole object, which limits its applications to small animals. However, by utilizing reflective photons, fluorescence distribution near the surface could be reconstructed regardless of the object size, which may extend the applications of FMT to surgical navigation and so on. Therefore, time-domain reflective fluorescence molecular tomography (TD-rFMT) is proposed in this paper. The system excites and detects the emission light from the same angle within a field of view of 5 cm. Because the detected intensities of targets depend strongly on the depth, the reconstruction of targets in deep regions would be evidently affected. Therefore, a fluorescence yield reconstruction method with depth regularization and a weighted separation reconstruction strategy for lifetime are developed to enhance the performance for deep targets. Through simulations and phantom experiments, TD-rFMT is proved capable of reconstructing fluorescence distribution within a 2.5-cm depth with accurate reconstructed yield, lifetime, and target position(s).
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Affiliation(s)
- Jiaju Cheng
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Peng Zhang
- Department of Biomedical Engineering, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Chuangjian Cai
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Yang Gao
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Jie Liu
- Department of Biomedical Engineering, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
| | - Hui Hui
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Jie Tian
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing 100191, China
| | - Jianwen Luo
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
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Konovalov AB, Vlasov VV, Uglov AS. Early-photon reflectance fluorescence molecular tomography for small animal imaging: Mathematical model and numerical experiment. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2021; 37:e03408. [PMID: 33094558 DOI: 10.1002/cnm.3408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Revised: 10/04/2020] [Accepted: 10/17/2020] [Indexed: 06/11/2023]
Abstract
The paper presents an original approach to time-domain reflectance fluorescence molecular tomography (FMT) of small animals. It is based on the use of early arriving photons and state-of-the-art compressed-sensing-like reconstruction algorithms and aims to improve the spatial resolution of fluorescent images. We deduce the fundamental equation that models the imaging operator and derive analytical representations for the sensitivity functions which are responsible for the reconstruction of the fluorophore absorption coefficient. The idea of fluorescence lifetime tomography with our approach is also discussed. We conduct a numerical experiment on 3D reconstruction of box phantoms with spherical fluorescent inclusions of small diameters. For modeling measurement data and constructing the sensitivity matrix we assume a virtual fluorescence tomograph with a scanning fiber probe that illuminates and collects light in reflectance geometry. It provides for large source-receiver separations which correspond to the macroscopic regime. Two compressed-sensing-like reconstruction algorithms are used to solve the inverse problem. These are the algebraic reconstruction technique with total variation regularization and our modification of the fast iterative shrinkage-thresholding algorithm. Results of our numerical experiment show that our approach is capable of achieving as good spatial resolution as 0.2 mm and even better at depths to 9 mm inclusive.
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Affiliation(s)
- Alexander B Konovalov
- Computational Center, Federal State Unitary Enterprise "Russian Federal Nuclear Center - Zababakhin All-Russia Research Institute of Technical Physics,", Snezhinsk, Russia
- Laboratory of Molecular Imaging, Bach Institute of Biochemistry, Research Center of Biotechnology of the Russian Academy of Sciences, Moscow, Russia
| | - Vitaly V Vlasov
- Computational Center, Federal State Unitary Enterprise "Russian Federal Nuclear Center - Zababakhin All-Russia Research Institute of Technical Physics,", Snezhinsk, Russia
- Laboratory of Molecular Imaging, Bach Institute of Biochemistry, Research Center of Biotechnology of the Russian Academy of Sciences, Moscow, Russia
| | - Alexander S Uglov
- Computational Center, Federal State Unitary Enterprise "Russian Federal Nuclear Center - Zababakhin All-Russia Research Institute of Technical Physics,", Snezhinsk, Russia
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Zhang P, Liu J, Hui H, An Y, Wang K, Yang X, Tian J. Linear scheme for the direct reconstruction of noncontact time-domain fluorescence molecular lifetime tomography. APPLIED OPTICS 2020; 59:7961-7967. [PMID: 32976471 DOI: 10.1364/ao.398967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 08/07/2020] [Indexed: 06/11/2023]
Abstract
Direct reconstruction of the noncontact time-domain fluorescence molecular lifetime tomography (TD-FMLT) with current nonlinear algorithms has suffered from complexity and heavy computation loads of the physical model for a large imaging area in TD-FMLT. In this work, we discretize the system matrix along time points and apply a linearized reconstruction algorithm using the fused least absolute shrinkage and selection operator method. The reconstructed yield map and object geometry are used as a priori information to mitigate the ill conditions. This approach is implemented on a fully noncontact TD-FMLT system equipped with a femtosecond pulse laser and a high-speed, time-gated camera. We validate the methodology using both numerical simulations and inhomogeneous phantom experiments. The results exhibit good localization accuracy for fluorescent targets and an efficient computation capability for the reconstruction of fluorescence lifetime in noncontact TD-FMLT. We envision that the proposed linear scheme for the direct reconstruction method in noncontact TD-FMLT has a significant potential for in vivo preclinical studies.
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Abstract
This article reviews the past and current statuses of time-domain near-infrared spectroscopy (TD-NIRS) and imaging. Although time-domain technology is not yet widely employed due to its drawbacks of being cumbersome, bulky, and very expensive compared to commercial continuous wave (CW) and frequency-domain (FD) fNIRS systems, TD-NIRS has great advantages over CW and FD systems because time-resolved data measured by TD systems contain the richest information about optical properties inside measured objects. This article focuses on reviewing the theoretical background, advanced theories and methods, instruments, and studies on clinical applications for TD-NIRS including some clinical studies which used TD-NIRS systems. Major events in the development of TD-NIRS and imaging are identified and summarized in chronological tables and figures. Finally, prospects for TD-NIRS in the near future are briefly described.
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