Deep-Learning as a Design Tool in Localization Microscopy

Yoav Shechtman

doi:10.1364/FIO.2023.FTh3A.2

Frontiers in Optics + Laser Science 2023 (FiO, LS)
Technical Digest Series (Optica Publishing Group, 2023),
paper FTh3A.2
•https://doi.org/10.1364/FIO.2023.FTh3A.2

Deep-Learning as a Design Tool in Localization Microscopy

Yoav Shechtman

Frontiers in Optics 2023

Tacoma, Washington United States
9–12 October 2023
ISBN: 978-1-957171-29-6

From the session
Machine Learning Theme: Inverse Design and Machine Learning (FTh3A)

Not Accessible

Your library or personal account may give you access

Get PDF
Email
Share
Get Citation
Copy Citation Text
Y. Shechtman, "Deep-Learning as a Design Tool in Localization Microscopy," in Frontiers in Optics + Laser Science 2023 (FiO, LS), Technical Digest Series (Optica Publishing Group, 2023), paper FTh3A.2.

Export Citation
- BibTex
- Endnote (RIS)
- HTML
- Plain Text
Citation alert
Save article

Abstract

I will discuss deep learning as a tool for optical system design in cases where traditional design metrics are elusive, focusing on point-spread function engineering for localization microscopy. Super-resolution using DL will also be discussed.

PDF Article

More Like This

Three-Dimensional Localization Microscopy by Deep Learning

Elias Nehme, Boris Ferdman, Daniel Freedman, Lucien E. Weiss, Racheli Gordon-Soffer, Tal Naor, Reut Orange Kedem, Onit Alalouf, Tomer Michaeli, and Yoav Shechtman
3W3G.5 3D Image Acquisition and Display: Technology, Perception and Applications (3D) 2021

Snapshot multi-PSF 3D single-molecule localization microscopy using deep learning

Hayato Ikoma, Yifan Peng, Michael Broxton, and Gordon Wetzstein
CW3B.3 Computational Optical Sensing and Imaging (COSI) 2020

End-to-End Learning for Computational Microscopy

Laura Waller
FTh2A.1 Frontiers in Optics (FiO) 2023

Previous Article Next Article