Acta Photonica Sinica, Volume. 51, Issue 6, 0618002(2022)
A Fluorescence Lifetime Retrieval Algorithm Based on LSTM Neural Network
Fig. 1. TCSPC method for fluorescence lifetime detection
Fig. 2. Flow chart of the construction of the LSTM neural network model
Fig. 3. Structure of LSTM
Fig. 4. Test results of the same neurons with the different layers
Fig. 5. Test results of the different neurons with the same layers
Fig. 6. The structure of the network
Fig. 7. Histogram of fluorescence lifetime decay
Fig. 8. The restoration results of 32×32 array
Fig. 9. Comparison of CMM,LSM and LSTM retrieval range
Fig. 10. The comparison of array imaging when
Fig. 11. The comparison of array imaging when
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Biyu YANG, Yue XU. A Fluorescence Lifetime Retrieval Algorithm Based on LSTM Neural Network[J]. Acta Photonica Sinica, 2022, 51(6): 0618002
Category: Microscopy
Received: Jan. 17, 2022
Accepted: Feb. 22, 2022
Published Online: Sep. 23, 2022
The Author Email: XU Yue (yuex@njupt.edu.cn)