Technology
ZeroCostDL4Mic
GitHub:
- HenriquesLab/ZeroCostDL4Mic
Publication: Chamier et al. Nature Communications 2021
- 624
ZeroCostDL4Mic is an open-source platform that aims to make deep learning more accessible for microscopy image analysis. It allows researchers with limited coding or computing expertise to easily train, evaluate, and apply deep learning models for various bioimage analysis tasks.
ZeroCostDL4Mic runs on Google Colab, a free cloud service, so deep learning needs no hardware purchase. It is a set of Jupyter notebooks with graphical interfaces that walk the user through training and applying a model.
Some key features of ZeroCostDL4Mic:
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Gives free access to Colab GPUs for training, removing the need for a local server.
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Implements deep learning models for common microscopy tasks: segmentation, object detection, image restoration, super-resolution microscopy and image-to-image translation.
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The notebooks have an easy-to-use interface allowing non-experts to train models by uploading their data and configuring parameters with minimal coding.
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Measures model performance with quantitative quality control metrics, so a model can be tuned and checked before it is used on real data.
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Support for data augmentation and transfer learning to improve model performance and simplify the training process.
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Trained models can be exported and used with other platforms like ImageJ or Fiji. The notebooks can also be combined into analysis pipelines.
ZeroCostDL4Mic puts deep learning within reach of microscopy researchers by letting them train and apply models on free cloud computing. Someone with little technical background can use current methods on their own imaging data, and because the code is open and modular, experienced users can build on it. It should speed up the uptake of deep learning in bioimage analysis.
Publications featuring ZeroCostDL4Mic
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AI4Life Open Calls and Public Challenges: why, how, and what we have learned Vera Galinova, Mehdi Seifi, Beatriz Serrano Solano, Kristína Lidayová, Damian Dalle Nogare, Agustín Andrés Corbat, Joshua Talks, Edoardo Giacomello, Estibaliz Gómez-de-Mariscal, Mariana G. Ferreira, Caterina Fuster-Barceló, Juan Manuel Battagliotti, Carlos García-López-de-Haro, Benjamin Salmon, Melisande Croft, Si Young Yie, Guillermo Rey-Paniagua, Xiaotian Hu, Sungjun Cho, Aagam Sheth, Chhayansh Porwal, Xiaomeng Li, AI4Life Consortium, Ricardo Henriques, Xinyang Li, Alexander Krull, Anna Klemm, Arrate Muñoz Barrutia, Anna Kreshuk, Wei Ouyang, Florian Jug, Joran Deschamps Preprint published in bioRxiv, July 2026 Technologies: BioImage Model Zoo (), CARE (), DL4MicEverywhere (), mAIcrobe (), Nuclear-Pores as references and ZeroCostDL4Mic () Funded by: Chan Zuckerberg Initiative (CZI), The Kavli Foundation, and The Wellcome Trust, ERC, H2021, H2022 and La Caixa Foundation DOI: 10.64898/2026.07.21.739486 |
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VLab4Mic: prediction of structural resolvability in super-resolution microscopy Damián Martínez, Bruno M. Saraiva, Tayla Shakespeare, Mark Bates, Dylan M. Owen, Christophe Leterrier, Mario Del Rosario, Ricardo Henriques Preprint published in bioRxiv, June 2026 Technologies: EZInput (), mAIcrobe (), nano-org, NanoJ (), NanoJ-SQUIRREL (), Nuclear-Pores as references and ZeroCostDL4Mic () Funded by: Chan Zuckerberg Initiative (CZI), The Kavli Foundation, and The Wellcome Trust, CZI, EMBO, ERC, H2022 and La Caixa Foundation DOI: 10.64898/2026.06.02.729521 |
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Packaging Jupyter notebooks as installable desktop apps using LabConstrictor Iván Hidalgo-Cenalmor, Marcela Xiomara Rivera Pineda, Bruno M Saraiva, Ricardo Henriques, Guillaume Jacquemet Preprint published in arXiv, March 2026 Technologies: CARE (), CellTracksColab (), DL4MicEverywhere (), mAIcrobe () and ZeroCostDL4Mic () Funded by: Chan Zuckerberg Initiative (CZI), The Kavli Foundation, and The Wellcome Trust, EMBO, ERC, H2022 and La Caixa Foundation DOI: 10.48550/arXiv.2603.10704 |
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Roadmap on deep learning for microscopy Giovanni Volpe, Carolina Wählby, Lei Tian, Michael Hecht, Artur Yakimovich, Kristina Monakhova, Laura Waller, Ivo F Sbalzarini, Christopher A Metzler, Mingyang Xie, Kevin Zhang, Isaac CD Lenton, Halina Rubinsztein-Dunlop, Daniel Brunner, Bijie Bai, Aydogan Ozcan, Daniel Midtvedt, Hao Wang, Nataša Sladoje, Joakim Lindblad, Jason T Smith, Marien Ochoa, Margarida Barroso, Xavier Intes, Tong Qiu, Li-Yu Yu, Sixian You, Yongtao Liu, Maxim A Ziatdinov, Sergei V Kalinin, Arlo Sheridan, Uri Manor, Elias Nehme, Ofri Goldenberg, Yoav Shechtman, Henrik K Moberg, Christoph Langhammer, Barbora Špačková, Saga Helgadottir, Benjamin Midtvedt, Aykut Argun, Tobias Thalheim, Frank Cichos, Stefano Bo, Lars Hubatsch, Jesus Pineda, Carlo Manzo, Harshith Bachimanchi, Erik Selander, Antoni Homs-Corbera, Martin Fränzl, Kevin de Haan, Yair Rivenson, Zofia Korczak, Caroline Beck Adiels, Mite Mijalkov, Dániel Veréb, Yu-Wei Chang, Joana B Pereira, Damian Matuszewski, Gustaf Kylberg, Ida-Maria Sintorn, Juan C Caicedo, Beth A Cimini, Muyinatu A Lediju Bell, Bruno M Saraiva, Guillaume Jacquemet, Ricardo Henriques, Wei Ouyang, Trang Le, Estibaliz Gómez-de-Mariscal, Daniel Sage, Arrate Muñoz-Barrutia, Ebba Josefson Lindqvist, Johanna Bergman Paper published in Journal of Physics: Photonics, January 2026 Technologies: BioImage Model Zoo (), CARE (), mAIcrobe () and ZeroCostDL4Mic () Funded by: CZI, EMBO, ERC and H2021 DOI: 10.1088/2515-7647/ae0fd1 |
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EZInput: A Cross-Environment Python Library for Easy UI Generation in Scientific Computing Bruno M Saraiva, Iván Hidalgo-Cenalmor, António D Brito, Damián Martínez, Tayla Shakespeare, Guillaume Jacquemet, Ricardo Henriques Preprint published in arXiv, January 2026 Technologies: DL4MicEverywhere (), mAIcrobe (), NanoJ-eSRRF (), NanoPyx () and ZeroCostDL4Mic () Funded by: Chan Zuckerberg Initiative (CZI), The Kavli Foundation, and The Wellcome Trust, CZI, EMBO, ERC, H2021 and H2022 DOI: 10.48550/arXiv.2601.08859 |
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PhotoFiTT: a quantitative framework for assessing phototoxicity in live-cell microscopy experiments Mario Del Rosario, Estibaliz Gómez-de-Mariscal, Leonor Morgado, Raquel Portela, Guillaume Jacquemet, Pedro M. Pereira, Ricardo Henriques Paper published in Nature Communications, December 2025 Technologies: mAIcrobe (), PhotoFiTT () and ZeroCostDL4Mic () Funded by: Chan Zuckerberg Initiative (CZI), The Kavli Foundation, and The Wellcome Trust, CZI, EMBO, ERC, FCT, H2021 and H2022 DOI: 10.1038/s41467-025-66209-6 |
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CLEM-Reg: an automated point cloud-based registration algorithm for volume correlative light and electron microscopy Daniel Krentzel, Matouš Elphick, Marie-Charlotte Domart, Christopher J Peddie, Romain F Laine, Cameron Shand, Ricardo Henriques, Lucy M Collinson, Martin L Jones Paper published in Nature Methods, September 2025 Technologies: BioImage Model Zoo (), CARE (), DL4MicEverywhere (), Rescale4DL () and ZeroCostDL4Mic () Funded by: CZI, ERC, H2021 and H2022 DOI: 10.1038/s41592-025-02794-0 |
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The nucleoid of rapidly growing Escherichia coli localizes close to the inner membrane and is organized by transcription, translation, and cell geometry Christoph Spahn, Stuart Middlemiss, Estibaliz Gómez-de-Mariscal, Ricardo Henriques, Helge B. Bode, Séamus Holden, Mike Heilemann Paper published in Nature Communications, April 2025 Technologies: CARE (), DeepBacs () and ZeroCostDL4Mic () Funded by: EMBO, ERC, H2021 and H2022 DOI: 10.1038/s41467-025-58723-4 |
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This Microtubule Does Not Exist: Super‐Resolution Microscopy Image Generation by a Diffusion Model Alon Saguy, Tav Nahimov, Maia Lehrman, Estibaliz Gómez‐de‐Mariscal, Iván Hidalgo‐Cenalmor, Onit Alalouf, Ashwin Balakrishnan, Mike Heilemann, Ricardo Henriques, Yoav Shechtman Paper published in Small Methods, January 2025 Technologies: CARE () and ZeroCostDL4Mic () Funded by: Chan Zuckerberg Initiative (CZI), The Kavli Foundation, and The Wellcome Trust, CZI, EMBO, ERC, H2021 and H2022 DOI: 10.1002/smtd.202400672 |
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DL4MicEverywhere: deep learning for microscopy made flexible, shareable and reproducible Iván Hidalgo-Cenalmor, Joanna W. Pylvänäinen, Mariana G. Ferreira, Craig T. Russell, Alon Saguy, Ignacio Arganda-Carreras, Yoav Shechtman, Guillaume Jacquemet, Ricardo Henriques, Estibaliz Gómez-de-Mariscal Paper published in Nature Methods, May 2024 Technologies: BioImage Model Zoo (), DL4MicEverywhere () and ZeroCostDL4Mic () Funded by: EMBO, ERC, H2021 and H2022 DOI: 10.1038/s41592-024-02295-6 |
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Harnessing artificial intelligence to reduce phototoxicity in live imaging Estibaliz Gómez-de-Mariscal, Mario Del Rosario, Joanna W. Pylvänäinen, Guillaume Jacquemet, Ricardo Henriques Perspective published in Journal of Cell Science, February 2024 Technologies: BioImage Model Zoo (), CARE (), DeepBacs (), NanoJ-eSRRF (), NanoJ-SQUIRREL (), NanoJ-SRRF () and ZeroCostDL4Mic () Funded by: CZI, EMBO, ERC, H2021 and H2022 DOI: 10.1242/jcs.261545 |
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CellTracksColab is a platform that enables compilation, analysis, and exploration of cell tracking data Estibaliz Gómez-de-Mariscal, Hanna Grobe, Joanna W Pylvänäinen, Laura Xénard, Ricardo Henriques, Jean-Yves Tinevez, Guillaume Jacquemet Paper published in PLOS Biology, January 2024 Technologies: CARE (), CellTracksColab () and ZeroCostDL4Mic () DOI: 10.1371/journal.pbio.3002740 |
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Transertion and cell geometry organize the Escherichia coli nucleoid during rapid growth Christoph Spahn, Stuart Middlemiss, Estibaliz Gómez-de-Mariscal, Ricardo Henriques, Helge B. Bode, Séamus Holden, Mike Heilemann Preprint published in bioRxiv, October 2023 Technologies: CARE (), DeepAutoFocus (), DeepBacs () and ZeroCostDL4Mic () Funded by: EMBO, ERC, H2021 and H2022 DOI: 10.1101/2023.10.16.562172 |
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Live-cell imaging in the deep learning era Joanna W Pylvänäinen, Estibaliz Gómez-de-Mariscal, Ricardo Henriques, Guillaume Jacquemet Review published in Current Opinion in Cell Biology, January 2023 Technologies: BioImage Model Zoo (), CARE (), DeepBacs (), Fast4DReg (), NanoJ (), NanoJ-Fluidics () and ZeroCostDL4Mic () Funded by: CZI, EMBO, ERC and H2021 DOI: 10.1016/j.ceb.2023.102271 |
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Fast4DReg–fast registration of 4D microscopy datasets Joanna W Pylvänäinen, Romain F Laine, Bruno MS Saraiva, Sujan Ghimire, Gautier Follain, Ricardo Henriques, Guillaume Jacquemet Paper published in Journal of Cell Science, January 2023 Technologies: CARE (), Fast4DReg (), NanoJ () and ZeroCostDL4Mic () Funded by: CZI and ERC DOI: 10.1242/jcs.260728 |
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Mapping molecular complexes with super-resolution microscopy and single-particle analysis Afonso Mendes, Hannah S. Heil, Simao Coelho, Christophe Leterrier, Ricardo Henriques Review published in Open Biology, July 2022 Technologies: NanoJ-VirusMapper, Nuclear-Pores as references and ZeroCostDL4Mic () Funded by: EMBO, ERC and Wellcome Trust DOI: 10.1098/rsob.220079 |
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DeepBacs for multi-task bacterial image analysis using open-source deep learning approaches Christoph Spahn, Estibaliz Gómez-de-Mariscal, Romain F. Laine, Pedro M. Pereira, Lucas von Chamier, Mia Conduit, Mariana G. Pinho, Guillaume Jacquemet, Séamus Holden, Mike Heilemann, Ricardo Henriques Paper published in Communications Biology, July 2022 Technologies: BioImage Model Zoo (), CARE (), DeepBacs (), NanoJ (), NanoJ-SQUIRREL () and ZeroCostDL4Mic () Funded by: CZI, ERC, FCT and Wellcome Trust DOI: 10.1038/s42003-022-03634-z |
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Bioimage model zoo: a community-driven resource for accessible deep learning in bioimage analysis Wei Ouyang, Fynn Beuttenmueller, Estibaliz Gómez-de-Mariscal, Constantin Pape, Tom Burke, Carlos Garcia-López-de-Haro, Craig Russell, Lucía Moya-Sans, Cristina de-la-Torre-Gutiérrez, Deborah Schmidt, Dominik Kutra, Maksim Novikov, Martin Weigert, Uwe Schmidt, Peter Bankhead, Guillaume Jacquemet, Daniel Sage, Ricardo Henriques, Arrate Muñoz-Barrutia, Emma Lundberg, Florian Jug, Anna Kreshuk Preprint published in BioRxiv, January 2022 Technologies: BioImage Model Zoo (), CARE () and ZeroCostDL4Mic () Funded by: CZI, EMBO, ERC and H2021 DOI: 10.1101/2022.06.07.495102 |
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Democratising deep learning for microscopy with ZeroCostDL4Mic Lucas von Chamier, Romain F. Laine, Johanna Jukkala, Christoph Spahn, Daniel Krentzel, Elias Nehme, Martina Lerche, Sara Hernández-Pérez, Pieta K. Mattila, Eleni Karinou, Séamus Holden, Ahmet Can Solak, Alexander Krull, Tim-Oliver Buchholz, Martin L. Jones, Loïc A. Royer, Christophe Leterrier, Yoav Shechtman, Florian Jug, Mike Heilemann, Guillaume Jacquemet, Ricardo Henriques Paper published in Nature Communications, April 2021 Technologies: CARE (), NanoJ (), NanoJ-SQUIRREL (), NanoJ-SRRF () and ZeroCostDL4Mic () Funded by: EMBO, ERC and Wellcome Trust News: AZO Life Sciences, Drug Target Review, Nanotechnology Now and The Medical News Blogs: Microbiome Digest - Bik's Picks DOI: 10.1038/s41467-021-22518-0 |
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Funding contributing to ZeroCostDL4Mic
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VirusAwareScopes: Machine Learning-Driven Adaptive Microscopy for Long-Term Viral Infection Studies Ricardo Henriques Alias: VirusAwareScopes Funded by: La Caixa Foundation - Health Research Duration: November 2025 - October 2028 Publications: 4 |
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SMALS: Smart Microscopy for Adaptative Live Super-resolution imaging to elucidate the initial steps of the HIV viral transmission Estibaliz Gómez-de-Mariscal Alias: SMALS Funded by: FCT - CEEC Individual Duration: April 2024 - May 2026 |
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Quinoline-Derived Foldamers: A novel approach to combat antibiotic multiresistant and persistent Pedro M. Mateus, Pedro Matos Pereira, Ricardo Henriques Funded by: FCT - LS4Future Seed Funding Duration: March 2024 - September 2024 |
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3D Nanoscope: a highly accessible, high-performance device for live cell nanoscopy Arturo G. Vesga Alias: 3DNanoScope4All Funded by: Marie Curie - HORIZON TMA MSCA Postdoctoral Fellowships Duration: March 2024 - February 2026 |
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Sub-cellular Metabolic Compartmentalization During Oocyte Development Zita Carvalho dos Santos, Ricardo Henriques, Jorge Carvalho Funded by: CZI - Measuring Metabolism Across Scales Duration: January 2024 - December 2026 |
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Real-Time high-content Super-Resolution Imaging of ES Cell States Eran Meshorer, Ricardo Henriques, Anna Kreshuk, Sandrine Lévêque-Fort, Nicolas Bourg, Genevieve Almouzni Alias: RT-SuperES Funded by: H2022 - EIC Pathfinder Open Duration: July 2023 - June 2027 Publications: 21 |
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Artificial Intelligence for Image Data Analysis in the Life Sciences Anna Kreshuk, Florian Jug, Ricardo Henriques, Wei Ouyang, Arrate Muñoz-Barrutia, Emma Lundberg, Matthew Hartley Alias: AI4Life Funded by: H2021 - INFRA Duration: September 2022 - August 2025 Publications: 21 |
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VP-CLEM-KIT: a pipeline for democratising volumetric visual proteomics Lucy Collinson, Ricardo Henriques, Paul French Funded by: CZI - Visual Proteomics Imaging Duration: December 2021 - June 2024 Publications: 19 |