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Encoder-decoder deep learning network for simultaneous reconstruction of fluorescence yield and lifetime distributions

文献类型：期刊论文

作者Cheng, Jiaju5; Zhang, Peng3,4; Liu, Fei1; Liu, Jie4; Hui, Hui3; Tian, Jie2,3; Luo, Jianwen5
刊名BIOMEDICAL OPTICS EXPRESS
出版日期2022-09-01
卷号13期号:9页码:4693-4705
ISSN号2156-7085
DOI10.1364/BOE.466349
通讯作者Luo, Jianwen(luo_jianwen@tsinghua.edu.cn)
英文摘要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
WOS关键词MOLECULAR TOMOGRAPHY ; MODEL
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]
WOS研究方向Biochemistry & Molecular Biology ; Optics ; Radiology, Nuclear Medicine & Medical Imaging
语种英语
出版者Optica Publishing Group
WOS记录号WOS:000863048100006
资助机构National Natural Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/50382]  
专题自动化研究所_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.Beijing Informat Sci & Technol Univ, Beijing Adv Informat & Ind Technol Res Inst, Beijing 100192, Peoples R China
2.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Med, Beijing 100191, Peoples R China
3.Chinese Acad Sci, CAS Key Lab Mol Imaging, Inst Automat, Beijing 100190, Peoples R China
4.Beijing Jiaotong Univ, Dept Biomed Engn, Sch Comp & Informat Technol, Beijing 100044, Peoples R China
5.Tsinghua Univ, Dept Biomed Engn, Sch Med, Beijing 100084, 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.

入库方式： OAI收割

来源：自动化研究所

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