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 | |
发表期刊 | BIOMEDICAL OPTICS EXPRESS |
ISSN | 2156-7085 |
2022-09-01 | |
卷号 | 13期号:9页码:4693-4705 |
通讯作者 | Luo, Jianwen(luo_jianwen@tsinghua.edu.cn) |
摘要 | 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 |
关键词[WOS] | MOLECULAR TOMOGRAPHY ; MODEL |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[61871022] ; National Natural Science Foundation of China[61871251] ; National Natural Science Foundation of China[62027901] |
项目资助者 | National Natural Science Foundation of China |
WOS研究方向 | Biochemistry & Molecular Biology ; Optics ; Radiology, Nuclear Medicine & Medical Imaging |
WOS类目 | Biochemical Research Methods ; Optics ; Radiology, Nuclear Medicine & Medical Imaging |
WOS记录号 | WOS:000863048100006 |
出版者 | Optica Publishing Group |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/50383 |
专题 | 中国科学院分子影像重点实验室 |
通讯作者 | Luo, Jianwen |
作者单位 | 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 |
推荐引用方式 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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