Published: 2022-07-08
AI4LIFE is a Horizon Europe-funded project that brings together the computational and life science communities. Its goal is to empower life science researchers to harness the full potential of Artificial Intelligence (AI) and Machine Learning (ML) methods for bioimage analysis – and in particular microscopy image analysis, by providing services, and developing standards aimed at both developers and users. With a consortium of ten partners, AI4LIFE promises to create harmonized and interoperable AI tools & methods via Open calls and public challenges and bring these developments to researchers via strategic outreach and advanced training. The services provided and solutions developed within the AI4LIFE framework are crucial to solving today’s microscopy image analysis problems and will contribute to boosting the pace of biological and medical insights and discovery in the coming years.
A bridge between the life sciences and computer sciences
The AI4LIFE consortium is coordinated by Euro-BioImaging ERIC, the ESFRI research infrastructure for open access to biological and biomedical imaging services, and is made up of 10 partners, bringing together leading AI/ML researchers and developers of popular open source image analysis tools, as well as providers of European-scale storage and compute services, and representatives of diverse European Life Sciences Research Infrastructures.
AI4LIFE builds on existing efforts in the domain of image analysis, in order to better share, integrate and consolidate the development of new tools and drive their adoption by the user community. The project has a two-fold strategy:
• To provide the infrastructure and services that will enable all imaging scientists to reap the benefits of the new state-of-the-art of image analysis tools.
• To support and foster method developers, enabling them to put their latest methods into the hands of end-users in wet labs and imaging facilities.
Democratizing access to AI for image analysis
The consortium partners will build an open, accessible, community-driven repository of FAIR pre-trained AI models and develop services to deliver these models to life scientists, including those without substantial computational expertise.
To do so, the project partners will strive to:
• Democratize availability of AI-based image analysis methods as FAIR services;
• Provide integrated access to cloud computing resources for evaluation of pre-trained models;
• Establish standards for submission, storage of and FAIR access to reference data, reference annotations (ground-truth), trained AI models, and trainable AI methods;
• Simplify model deployment, sharing, and dissemination of AI-based methods as a new developer-facing service;
• Organize Open Calls and Challenges for outstanding image analysis problems in the EU Mission areas of the Horizon Europe framework programme;
• Empower common image analysis platforms by AI tools;
• Organize outreach and training events for life scientists via targeted image analysis courses and workshops as well as by participation in the largest international conferences.
AI4LIFE Partners
AI4LIFE will be a crucial dedicated infrastructure for the bioimage computing domain. It will build on the expertise of the partners in developing and maintaining popular, open-source and user-friendly tools and resources including:
• FIJI/ImageJ and CSBDeep by Florian Jug's team at Human Technopole, Milan
• Ilastik by Anna Kreshuk's team at EMBL, Heidelberg
• BioImage Archive by Matthew Hartley's team at EMBL-EBI
• DeepImageJ by Arrate Muñoz-Barrutia's team at University Carlos III, Madrid
• Human Protein Atlas and ImJoy by Emma Lundberg's team and Wei Ouyang at KTH, Sweden
• ZeroCostDL4Mic by Ricardo Henriques' team at Institute Gulbenkian, Lisbon
Together these partners will deliver a unified approach and standards for sharing AI-based models in a specialized BioImage Model Zoo.
The project also includes users and developers from various fields brought together by the different Research Infrastructures:
• Euro-BioImaging ERIC for Biological and Biomedical imaging
• Instruct-ERIC for structural biology
• EU-OPENSCREEN ERIC for chemical screening
• EMPHASIS for plant phenotyping
• EMBRC ERIC for marine biology
These partners will ensure that the services developed in AI4LIFE are accepted and used by a wide range of life scientists.
Furthermore, project consortium members are embedded in the European Open Science Cloud (EOSC) and other pan-national andor global initiatives, and represent a wide range of life science domains, from structural biology and chemistry, to plant biology and marine science. All members are qualified to prepare life scientists for responsible use of AI methods while driving community contributions of new models and interoperability between analysis tools.
For more information about our project and to follow it as it develops, please continue to visit our website (www.eurobioimaging.eu) or follow us on social media (Twitter, LinkedIn).