Deep learning approach for solving the missing cone problem in optical diffraction tomography

Joowon Lim; Ahmed B. Ayoub; Demetri Psaltis

doi:10.1364/COSI.2020.CF4C.5

Imaging and Applied Optics Congress
OSA Technical Digest (Optica Publishing Group, 2020),
paper CF4C.5
•https://doi.org/10.1364/COSI.2020.CF4C.5

Deep learning approach for solving the missing cone problem in optical diffraction tomography

Joowon Lim, Ahmed B. Ayoub, and Demetri Psaltis

Computational Optical Sensing and Imaging 2020

Washington, DC United States
22–26 June 2020
ISBN: 978-1-943580-77-4

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Microscopy and Polarimetry (CF4C)

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J. Lim, A. B. Ayoub, and D. Psaltis, "Deep learning approach for solving the missing cone problem in optical diffraction tomography," in Imaging and Applied Optics Congress, OSA Technical Digest (Optica Publishing Group, 2020), paper CF4C.5.

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Abstract

We present a deep neural network approach for solving the long standing missing cone problem in optical diffraction tomography. We demonstrate the performance of the proposed method using experimental data as well as simulations.

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