R
Racheli Gordon
Researcher at Technion – Israel Institute of Technology
Publications - 4
Citations - 268
Racheli Gordon is an academic researcher from Technion – Israel Institute of Technology. The author has contributed to research in topics: Deep learning & Microscopy. The author has an hindex of 4, co-authored 4 publications receiving 156 citations.
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Journal ArticleDOI
DeepSTORM3D: dense 3D localization microscopy and PSF design by deep learning
Elias Nehme,Daniel Freedman,Racheli Gordon,Boris Ferdman,Lucien E. Weiss,Onit Alalouf,Tal Naor,Reut Orange,Tomer Michaeli,Yoav Shechtman +9 more
TL;DR: DeepSTORM3D uses deep learning for accurate localization of point emitters in densely labeled samples in three dimensions for volumetric localization microscopy with high temporal resolution, as well as for optimal point-spread function design.
Journal ArticleDOI
DeepSTORM3D: dense three dimensional localization microscopy and point spread function design by deep learning
Elias Nehme,Daniel Freedman,Racheli Gordon,Boris Ferdman,Lucien E. Weiss,Onit Alalouf,Reut Orange,Tomer Michaeli,Yoav Shechtman +8 more
TL;DR: This work trains a neural network to receive an image containing densely overlapping PSFs of multiple emitters over a large axial range and output a list of their 3D positions, then uses the network to design the optimal PSF for the multi-emitter case.
Posted Content
Dense three dimensional localization microscopy by deep learning
TL;DR: This work trains a neural net to receive an image containing densely overlapping PSFs of multiple emitters over a large axial range, and outputs a list of their 3D positions, which are then used to design the optimal PSF for the multi-emitter case.
Journal ArticleDOI
Publisher Correction: DeepSTORM3D: dense 3D localization microscopy and PSF design by deep learning.
Elias Nehme,Daniel Freedman,Racheli Gordon,Boris Ferdman,Lucien E. Weiss,Onit Alalouf,Tal Naor,Reut Orange,Tomer Michaeli,Yoav Shechtman +9 more
TL;DR: An amendment to this paper has been published and can be accessed via a link at the top of the paper.