Artificial Intelligence for Image Data Analysis in the Life Sciences
Alias: AI4Life
Agency: H2021
Type: INFRA
Principal Investigator: Anna Kreshuk, Florian Jug
Investigators: Anna Kreshuk, Florian Jug, Ricardo Henriques, Wei Ouyang, Arrate Muñoz-Barrutia, Emma Lundberg, Matthew Hartley
Start-date: September 2021
End-date: August 2025
DOI: 10.3030/101057970
Agency: H2021
Type: INFRA
Principal Investigator: Anna Kreshuk, Florian Jug
Investigators: Anna Kreshuk, Florian Jug, Ricardo Henriques, Wei Ouyang, Arrate Muñoz-Barrutia, Emma Lundberg, Matthew Hartley
Start-date: September 2021
End-date: August 2025
DOI: 10.3030/101057970
The project aims to help life scientists apply machine learning for image analysis by providing sustainable research infrastructure services. It will build an open repository of AI models for bioimage analysis and offer services to deliver these to non-experts. The initiative seeks to prepare life scientists to exploit AI methods and drive adoption of best practices through ample training activities, open standards, and community contributions. Its consortium unites AI researchers, imaging platform providers, European research infrastructures, and open source image analysis tools to unlock the potential of AI for the life sciences.
Technology explored
Supported publications
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Structural Repetition Detector - multi-scale quantitative mapping of molecular complexes through microscopy Afonso Mendes, Bruno M Saraiva, Guillaume Jacquemet, Joao I Mamede, Christophe Leterrier, Ricardo Henriques Preprint published in bioRxiv, September 2024 Technologies: Nuclear-Pores as references and SReD Funded by: CZI, EMBO, ERC, H2021 and H2022 DOI: 10.1101/2024.09.16.613204 |
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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 Preprint published in bioRxiv, July 2024 Technologies: DL4MicEverywhere, PhotoFiTT and ZeroCostDL4Mic Funded by: CZI, EMBO, ERC, FCT, H2021 and H2022 DOI: 10.1101/2024.07.16.603046 |
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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 News: Labonline, MSN, AZoRobotics and Aamuset Kaupunkimedia Blogs: news-medical.net DOI: 10.1038/s41592-024-02295-6 |
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The rise of data‐driven microscopy powered by machine learning Leonor Morgado, Estibaliz Gómez‐de‐Mariscal, Hannah S. Heil, Ricardo Henriques Review published in Journal of Microscopy, March 2024 Technologies: NanoJ and NanoJ-Fluidics Funded by: CZI, EMBO, ERC, FCT, H2021 and H2022 DOI: 10.1111/jmi.13282 |
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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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Nano-org, a functional resource for single-molecule localisation microscopy data Sandeep Shirgill, Daniel J Nieves, Jeremy A Pike, Mohammad A Ahmed, Mohammed HH Baragilly, Kylie Savoye, Jonathan Worboys, Khodor Hazime, Adrian Garcia, David J Williamson, Ricardo Henriques, Steven F Lee, Dylan M Owen Preprint published in bioRxiv, January 2024 Technologies: nano-org Funded by: EMBO, ERC, H2021 and H2022 DOI: 10.1101/2024.08.06.606779 |
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High-fidelity 3D live-cell nanoscopy through data-driven enhanced super-resolution radial fluctuation Romain F. Laine, Hannah S. Heil, Simao Coelho, Jonathon Nixon-Abell, Angélique Jimenez, Theresa Wiesner, Damián Martínez, Tommaso Galgani, Louise Régnier, Aki Stubb, Gautier Follain, Samantha Webster, Jesse Goyette, Aurelien Dauphin, Audrey Salles, Siân Culley, Guillaume Jacquemet, Bassam Hajj, Christophe Leterrier, Ricardo Henriques Paper published in Nature Methods, November 2023 Technologies: NanoJ, NanoJ-eSRRF, NanoJ-SQUIRREL, NanoJ-SRRF, NanoPyx and Nuclear-Pores as references Funded by: CZI, EMBO, ERC, FCT, H2021, H2022, InnOValley and Wellcome Trust News: Photonics.com, The Science Times, Optics.org and Phys.org Blogs: Springer Nature Protocols and Methods Community DOI: 10.1038/s41592-023-02057-w |
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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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NanoPyx - super-fast bioimage analysis powered by adaptive machine learning Bruno M. Saraiva, Inês M. Cunha, António D. Brito, Gautier Follain, Raquel Portela, Robert Haase, Pedro M. Pereira, Guillaume Jacquemet, Ricardo Henriques Preprint published in bioRxiv, August 2023 Technologies: NanoJ, NanoJ-eSRRF, NanoJ-SQUIRREL, NanoJ-SRRF, NanoJ-VirusMapper and NanoPyx Funded by: CZI, EMBO, ERC, FCT, H2021 and H2022 DOI: 10.1101/2023.08.13.553080 |
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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, DeepBacs, Fast4DReg, NanoJ, NanoJ-eSRRF, NanoJ-Fluidics and ZeroCostDL4Mic Funded by: CZI, EMBO, ERC and H2021 DOI: 10.1016/j.ceb.2023.102271 |
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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 Published in Small Methods, January 2023 Technologies: ZeroCostDL4Mic Funded by: CZI, EMBO, ERC, H2021 and H2022 DOI: 10.1002/smtd.202400672 |
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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 Preprint published in arXiv, January 2023 Technologies: BioImage Model Zoo, CARE and ZeroCostDL4Mic Funded by: CZI, EMBO, ERC and H2021 DOI: 10.48550/arXiv.2303.03793 |
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Trimethine cyanine dyes as NA-sensitive probes for visualization of cell compartments in fluorescence microscopy Daria Aristova, Roman Selin, Hannah Sophie Heil, Viktoriia Kosach, Yuriy Slominsky, Sergiy Yarmoluk, Vasyl Pekhnyo, Vladyslava Kovalska, Ricardo Henriques, Andriy Mokhir Paper published in ACS omega, January 2022 Funded by: EMBO, ERC and H2021 DOI: 10.1021/acsomega.2c05231 |
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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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