Simple and Robust Deep Learning Approach for Fast Fluorescence Lifetime Imaging
文献类型:期刊论文
作者 | Wang, Quan3; Li, Yahui2; Xiao, Dong3; Zang, Zhenya3; Jiao, Zi'ao3; Chen, Yu1; Li, David Day Uei3 |
刊名 | SENSORS |
出版日期 | 2022-10 |
卷号 | 22期号:19 |
ISSN号 | 1424-8220 |
关键词 | fluorescence lifetime imaging (FLIM) deep learning imaging analysis |
DOI | 10.3390/s22197293 |
产权排序 | 2 |
英文摘要 | Fluorescence lifetime imaging (FLIM) is a powerful tool that provides unique quantitative information for biomedical research. In this study, we propose a multi-layer-perceptron-based mixer (MLP-Mixer) deep learning (DL) algorithm named FLIM-MLP-Mixer for fast and robust FLIM analysis. The FLIM-MLP-Mixer has a simple network architecture yet a powerful learning ability from data. Compared with the traditional fitting and previously reported DL methods, the FLIM-MLP-Mixer shows superior performance in terms of accuracy and calculation speed, which has been validated using both synthetic and experimental data. All results indicate that our proposed method is well suited for accurately estimating lifetime parameters from measured fluorescence histograms, and it has great potential in various real-time FLIM applications. |
语种 | 英语 |
出版者 | MDPI |
WOS记录号 | WOS:000867063400001 |
源URL | [http://ir.opt.ac.cn/handle/181661/96194] |
专题 | 条纹相机工程中心 |
通讯作者 | Wang, Quan |
作者单位 | 1.Univ Strathclyde, Dept Phys, Glasgow G4 0NG, Lanark, Scotland 2.Xian Inst Opt & Precis Mech, Key Lab Ultrafast Photoelect Diagnost Technol, Xian 710049, Peoples R China 3.Univ Strathclyde, Dept Biomed Engn, Glasgow G4 0RU, Lanark, Scotland |
推荐引用方式 GB/T 7714 | Wang, Quan,Li, Yahui,Xiao, Dong,et al. Simple and Robust Deep Learning Approach for Fast Fluorescence Lifetime Imaging[J]. SENSORS,2022,22(19). |
APA | Wang, Quan.,Li, Yahui.,Xiao, Dong.,Zang, Zhenya.,Jiao, Zi'ao.,...&Li, David Day Uei.(2022).Simple and Robust Deep Learning Approach for Fast Fluorescence Lifetime Imaging.SENSORS,22(19). |
MLA | Wang, Quan,et al."Simple and Robust Deep Learning Approach for Fast Fluorescence Lifetime Imaging".SENSORS 22.19(2022). |
入库方式: OAI收割
来源:西安光学精密机械研究所
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