Needle-based deep-neural-network imaging method

Ruipeng Guo; Soren Nelson; Ekata Mitra; Rajesh Menon

doi:10.1364/ISA.2021.ITh5D.3

OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP)
OSA Technical Digest (Optica Publishing Group, 2021),
paper ITh5D.3
•https://doi.org/10.1364/ISA.2021.ITh5D.3

Needle-based deep-neural-network imaging method

Ruipeng Guo, Soren Nelson, Ekata Mitra, and Rajesh Menon

Imaging Systems and Applications 2021

Washington, DC United States
19–23 July 2021
ISBN: 978-1-943580-89-7

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Machine Learning and Imaging II (ITh5D)

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R. Guo, S. Nelson, E. Mitra, and R. Menon, "Needle-based deep-neural-network imaging method," in OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP), H. Hua, B. Javidi, M. Martinez-Corral, O. Matoba, A. Stern, S. Thibault, T. Alieva, J. Ke, F. Willomitzer, F. Okten, P. Silveira, P. Banerjee, E. Stoykova, D. Chu, J. Park, F. Imai, C. Joo, M. Digman, D. Gardner, S. Gladysz, D. LeMaster, S. Basu, and O. Korotkova, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper ITh5D.3.

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Abstract

With a U-net architecture, we experimentally demonstrate the potential of 3D imaging using computational cannula microscopy. In addition, we build a camera based on cannula, which achieves a large effective demagnification of 127× with DNN.

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