PT  - JOURNAL ARTICLE
AU  - Lucas von Chamier
AU  - Romain F. Laine
AU  - Johanna Jukkala
AU  - Christoph Spahn
AU  - Daniel Krentzel
AU  - Elias Nehme
AU  - Martina Lerche
AU  - Sara Hernández-Pérez
AU  - Pieta K. Mattila
AU  - Eleni Karinou
AU  - Séamus Holden
AU  - Ahmet Can Solak
AU  - Alexander Krull
AU  - Tim-Oliver Buchholz
AU  - Martin L. Jones
AU  - Loïc A Royer
AU  - Christophe Leterrier
AU  - Yoav Shechtman
AU  - Florian Jug
AU  - Mike Heilemann
AU  - Guillaume Jacquemet
AU  - Ricardo Henriques
TI  - ZeroCostDL4Mic: an open platform to use Deep-Learning in Microscopy
AID  - 10.1101/2020.03.20.000133
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 2020.03.20.000133
4099  - http://biorxiv.org/content/early/2020/08/11/2020.03.20.000133.short
4100  - http://biorxiv.org/content/early/2020/08/11/2020.03.20.000133.full
AB  - The resources and expertise needed to use Deep Learning (DL) in bioimaging remain significant barriers for most laboratories. We present https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki, a platform simplifying access to DL by exploiting the free, cloud-based computational resources of Google Colab. https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki allows researchers to train, evaluate, and apply key DL networks to perform tasks including segmentation, detection, denoising, restoration, resolution enhancement and image-to-image translation. We demonstrate the application of the platform to study multiple biological processes.Competing Interest StatementThe authors have declared no competing interest.