Literature DB >> 27244414

Artificial neural network approaches for fluorescence lifetime imaging techniques.

Gang Wu, Thomas Nowotny, Yongliang Zhang, Hong-Qi Yu, David Day-Uei Li.   

Abstract

A novel high-speed fluorescence lifetime imaging (FLIM) analysis method based on artificial neural networks (ANN) has been proposed. In terms of image generation, the proposed ANN-FLIM method does not require iterative searching procedures or initial conditions, and it can generate lifetime images at least 180-fold faster than conventional least squares curve-fitting software tools. The advantages of ANN-FLIM were demonstrated on both synthesized and experimental data, showing that it has great potential to fuel current revolutions in rapid FLIM technologies.

Year:  2016        PMID: 27244414     DOI: 10.1364/OL.41.002561

Source DB:  PubMed          Journal:  Opt Lett        ISSN: 0146-9592            Impact factor:   3.776


  14 in total

1.  Deep learning-based mesoscopic fluorescence molecular tomography: an in silico study.

Authors:  Feixiao Long
Journal:  J Med Imaging (Bellingham)       Date:  2018-09-04

2.  Fast fit-free analysis of fluorescence lifetime imaging via deep learning.

Authors:  Jason T Smith; Ruoyang Yao; Nattawut Sinsuebphon; Alena Rudkouskaya; Nathan Un; Joseph Mazurkiewicz; Margarida Barroso; Pingkun Yan; Xavier Intes
Journal:  Proc Natl Acad Sci U S A       Date:  2019-11-12       Impact factor: 11.205

3.  High Resolution Fluorescence Lifetime Maps from Minimal Photon Counts.

Authors:  Mohamadreza Fazel; Sina Jazani; Lorenzo Scipioni; Alexander Vallmitjana; Enrico Gratton; Michelle A Digman; Steve Pressé
Journal:  ACS Photonics       Date:  2022-02-10       Impact factor: 7.077

Review 4.  Deep Learning in Biomedical Optics.

Authors:  Lei Tian; Brady Hunt; Muyinatu A Lediju Bell; Ji Yi; Jason T Smith; Marien Ochoa; Xavier Intes; Nicholas J Durr
Journal:  Lasers Surg Med       Date:  2021-05-20

5.  Deep-learning-based ghost imaging.

Authors:  Meng Lyu; Wei Wang; Hao Wang; Haichao Wang; Guowei Li; Ni Chen; Guohai Situ
Journal:  Sci Rep       Date:  2017-12-19       Impact factor: 4.379

6.  Fluorescence lifetime imaging microscopy: fundamentals and advances in instrumentation, analysis, and applications.

Authors:  Rupsa Datta; Tiffany M Heaster; Joe T Sharick; Amani A Gillette; Melissa C Skala
Journal:  J Biomed Opt       Date:  2020-05       Impact factor: 3.170

7.  Generative adversarial network enables rapid and robust fluorescence lifetime image analysis in live cells.

Authors:  Yuan-I Chen; Yin-Jui Chang; Shih-Chu Liao; Trung Duc Nguyen; Jianchen Yang; Yu-An Kuo; Soonwoo Hong; Yen-Liang Liu; H Grady Rylander; Samantha R Santacruz; Thomas E Yankeelov; Hsin-Chih Yeh
Journal:  Commun Biol       Date:  2022-01-11

8.  Simple phasor-based deep neural network for fluorescence lifetime imaging microscopy.

Authors:  Laurent Héliot; Aymeric Leray
Journal:  Sci Rep       Date:  2021-12-13       Impact factor: 4.379

9.  Phase imaging with an untrained neural network.

Authors:  Fei Wang; Yaoming Bian; Haichao Wang; Meng Lyu; Giancarlo Pedrini; Wolfgang Osten; George Barbastathis; Guohai Situ
Journal:  Light Sci Appl       Date:  2020-05-06       Impact factor: 17.782

10.  Dynamic fluorescence lifetime sensing with CMOS single-photon avalanche diode arrays and deep learning processors.

Authors:  Dong Xiao; Zhenya Zang; Natakorn Sapermsap; Quan Wang; Wujun Xie; Yu Chen; David Day Uei Li
Journal:  Biomed Opt Express       Date:  2021-05-17       Impact factor: 3.732

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