Institutional Repository of Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
| Encoder-decoder deep learning network for simultaneous reconstruction of fluorescence yield and lifetime distributions | |
Cheng, Jiaju1; Zhang, Peng2,3 ; Liu, Fei4; Liu, Jie2; Hui, Hui3; Tian, Jie3,5; Luo, Jianwen1
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| Source Publication | BIOMEDICAL OPTICS EXPRESS
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| ISSN | 2156-7085 |
| 2022-09-01 | |
| Volume | 13Issue:9Pages:4693-4705 |
| Corresponding Author | Luo, Jianwen(luo_jianwen@tsinghua.edu.cn) |
| 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.(c) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement |
| DOI | 10.1364/BOE.466349 |
| WOS Keyword | MOLECULAR TOMOGRAPHY ; MODEL |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | National Natural Science Foundation of China[61871022] ; National Natural Science Foundation of China[61871251] ; National Natural Science Foundation of China[62027901] |
| Funding Organization | National Natural Science Foundation of China |
| WOS Research Area | Biochemistry & Molecular Biology ; Optics ; Radiology, Nuclear Medicine & Medical Imaging |
| WOS Subject | Biochemical Research Methods ; Optics ; Radiology, Nuclear Medicine & Medical Imaging |
| WOS ID | WOS:000863048100006 |
| Publisher | Optica Publishing Group |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/50383 |
| Collection | 中国科学院分子影像重点实验室 |
| Corresponding Author | Luo, Jianwen |
| Affiliation | 1.Tsinghua Univ, Dept Biomed Engn, Sch Med, Beijing 100084, Peoples R China 2.Beijing Jiaotong Univ, Dept Biomed Engn, Sch Comp & Informat Technol, Beijing 100044, Peoples R China 3.Chinese Acad Sci, CAS Key Lab Mol Imaging, Inst Automat, Beijing 100190, Peoples R China 4.Beijing Informat Sci & Technol Univ, Beijing Adv Informat & Ind Technol Res Inst, Beijing 100192, Peoples R China 5.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Med, Beijing 100191, Peoples R China |
| Recommended Citation GB/T 7714 | Cheng, Jiaju,Zhang, Peng,Liu, Fei,et al. Encoder-decoder deep learning network for simultaneous reconstruction of fluorescence yield and lifetime distributions[J]. BIOMEDICAL OPTICS EXPRESS,2022,13(9):4693-4705. |
| APA | Cheng, Jiaju.,Zhang, Peng.,Liu, Fei.,Liu, Jie.,Hui, Hui.,...&Luo, Jianwen.(2022).Encoder-decoder deep learning network for simultaneous reconstruction of fluorescence yield and lifetime distributions.BIOMEDICAL OPTICS EXPRESS,13(9),4693-4705. |
| MLA | Cheng, Jiaju,et al."Encoder-decoder deep learning network for simultaneous reconstruction of fluorescence yield and lifetime distributions".BIOMEDICAL OPTICS EXPRESS 13.9(2022):4693-4705. |
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