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20182021
most citedReliable deep-learning-based phase imaging with uncertainty quantification

206 citations · 302 across the 6 of their papers we have counts for

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7 papers · 1 filter

physics.optics202184 cited

Deep learning in biomedical optics

Lei Tian, Brady Hunt, Muyinatu A. Lediju Bell +5

This article reviews deep learning applications in biomedical optics with a particular emphasis on image formation. The review is organized by imaging domains within biomedical opt…

physics.optics2021

Large-scale holographic particle 3D imaging with the beam propagation model

Hao Wang, Waleed Tahir, Jiabei Zhu +1

We develop a novel algorithm for large-scale holographic reconstruction of 3D particle fields. Our method is based on a multiple-scattering beam propagation method (BPM) combined w…

physics.optics2021

Acousto-optic Ptychography

Moriya Rosenfeld, Daniel Doktofsky, Gil Weinberg +3

Acousto-optic imaging (AOI) enables optical-contrast imaging deep inside scattering samples via localized ultrasound-modulation of scattered light. While AOI allows optical investi…

physics.optics2020

Displacement-agnostic coherent imaging through scatter with an interpretable deep neural network

Yuzhe Li, Shiyi Cheng, Yujia Xue +1

Coherent imaging through scatter is a challenging task in computational imaging. Both model-based and data-driven approaches have been explored to solve the inverse scattering prob…

physics.optics2020

Single-Shot 3D Widefield Fluorescence Imaging with a Computational Miniature Mesoscope

Yujia Xue, Ian G. Davison, David A. Boas +1

Fluorescence imaging is indispensable to biology and neuroscience. The need for large-scale imaging in freely behaving animals has further driven the development in miniaturized mi…

physics.optics2019

High-speed in vitro intensity diffraction tomography

Jiaji Li, Alex Matlock, Yunzhe Li +3

We demonstrate a label-free, scan-free {\it intensity} diffraction tomography technique utilizing annular illumination (aIDT) to rapidly characterize large-volume 3D refractive ind…