activity
20122021
most citedPhase recovery and holographic image reconstruction using deep learning in neural networks

1.1k citations · 2.1k across the 9 of their papers we have counts for

collaborators
Showing 2020 · eess.IVShow all

5 papers · 2 filters

eess.IV2020

Deep learning-based virtual refocusing of images using an engineered point-spread function

Xilin Yang, Luzhe Huang, Yilin Luo +4

We present a virtual image refocusing method over an extended depth of field (DOF) enabled by cascaded neural networks and a double-helix point-spread function (DH-PSF). This netwo…

eess.IV2020★ 27 cited

Label-free detection of Giardia lamblia cysts using a deep learning-enabled portable imaging flow cytometer

Zoltan Gorocs, David Baum, Fang Song +8

We report a field-portable and cost-effective imaging flow cytometer that uses deep learning to accurately detect Giardia lamblia cysts in water samples at a volumetric throughput…

eess.IV2020★ 156 cited

Misalignment Resilient Diffractive Optical Networks

Deniz Mengu, Yifan Zhao, Nezih T. Yardimci +3

As an optical machine learning framework, Diffractive Deep Neural Networks (D2NN) take advantage of data-driven training methods used in deep learning to devise light-matter intera…

eess.IV2020

Single-shot autofocusing of microscopy images using deep learning

Yilin Luo, Luzhe Huang, Yair Rivenson +1

We demonstrate a deep learning-based offline autofocusing method, termed Deep-R, that is trained to rapidly and blindly autofocus a single-shot microscopy image of a specimen that…

eess.IV2020

Digital synthesis of histological stains using micro-structured and multiplexed virtual staining of label-free tissue

Yijie Zhang, Kevin de Haan, Yair Rivenson +3

Histological staining is a vital step used to diagnose various diseases and has been used for more than a century to provide contrast to tissue sections, rendering the tissue const…