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, Yoav Shechtman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this talk I will describe how joint optimization of the microscope’s point-spread-function alongside the image processing algorithm, both using neural nets, enables dense emitter fitting for super-resolution microscopy and other challenging volumetric microscopy applications.

Original languageEnglish
Title of host publication3D Image Acquisition and Display
Subtitle of host publicationTechnology, Perception and Applications, 3D 2021
PublisherThe Optical Society
ISBN (Electronic)9781557528209
StatePublished - 2021
Event3D Image Acquisition and Display: Technology, Perception and Applications, 3D 2021 - Part of Imaging and Applied Optics Congress 2021 - Virtual, Online, United States
Duration: 19 Jul 202123 Jul 2021

Publication series

NameOptics InfoBase Conference Papers

Conference

Conference3D Image Acquisition and Display: Technology, Perception and Applications, 3D 2021 - Part of Imaging and Applied Optics Congress 2021
Country/TerritoryUnited States
CityVirtual, Online
Period19/07/2123/07/21

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Mechanics of Materials

Fingerprint

Dive into the research topics of 'Three-dimensional localization microscopy by deep learning'. Together they form a unique fingerprint.

Cite this