Deep-learning based dual-view light-field microscopy enabling high-resolution 3D imaging of dense signals

Lanxin Zhu; Chengqiang Yi; Guo Li; Yuxuan Zhao; Peng Fei

doi:10.1364/BODA.2021.DTh2A.3

Biophotonics Congress 2021
OSA Technical Digest (Optica Publishing Group, 2021),
paper DTh2A.3
•https://doi.org/10.1364/BODA.2021.DTh2A.3

Deep-learning based dual-view light-field microscopy enabling high-resolution 3D imaging of dense signals

Lanxin Zhu, Chengqiang Yi, Guo Li, Yuxuan Zhao, and Peng Fei

Bio-Optics: Design and Application 2021

Washington, DC United States
12–16 April 2021
ISBN: 978-1-943580-85-9

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L. Zhu, C. Yi, G. Li, Y. Zhao, and P. Fei, "Deep-learning based dual-view light-field microscopy enabling high-resolution 3D imaging of dense signals," in Biophotonics Congress 2021, C. Boudoux, K. Maitland, C. Hendon, M. Wojtkowski, K. Quinn, M. Schanne-Klein, N. Durr, D. Elson, F. Cichos, L. Oddershede, V. Emiliani, O. Maragò, S. Nic Chormaic, N. Pégard, S. Gibbs, S. Vinogradov, M. Niedre, K. Samkoe, A. Devor, D. Peterka, P. Blinder, and E. Buckley, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper DTh2A.3.

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Abstract

Poor performance on reconstructing dense signals is the major weakness of light-field microscopy. We report a deep-learning-based dual-view light-field microscopy which can reconstruct highly dense signals with high resolution.

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