Super resolution label-free dark-field microscopy by deep learning-Reference-Cited by-同舟云学术

Super resolution label-free dark-field microscopy by deep learning

Published:2024 Issue:9 Volume:16 Page:4703-4709
ISSN:2040-3364
Container-title:Nanoscale
language:en
Short-container-title:Nanoscale

Author:

Lei Ming¹^ORCID,Zhao Junxiang¹,Zhou Junxiao¹^ORCID,Lee Hongki¹,Wu Qianyi¹,Burns Zachary¹,Chen Guanghao¹,Liu Zhaowei¹²

Affiliation:

1. Department of Electrical and Computer Engineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, California, 92093, USA

2. Materials Science and Engineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA

Abstract

In this work, we propose a deep learning based framework which doubles the resolution in traditional dark field imaging after being trained on a dataset simulated with the forward imaging model.

Funder

Gordon and Betty Moore Foundation

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/NR/D3NR04294D

Reference49 articles.

1. Label-Free Super-Resolution Imaging Techniques

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5. Incident Dark-Field Illumination: a New Method for Microcirculatory Study

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