Category: News

Euro-BioImaging’s Virtual Pub sessions have been a weekly event every Friday since the beginning of the pandemic back in the spring of 2020.
On March 1st, 2024, the session was dedicated to showcasing the tools developed within AI4Life presented by experts among the project partners. Attendees had the opportunity to learn about the BioImage Model Zoo, BioEngine, the BioImage.IO chatbot, and Open Calls and Challenges.

• Anna Kreshuk, Group Leader at EMBL Heidelberg and scientific coordinator of AI4Life (together with Florian Jug), provided an overview of AI4Life & the BioImage Model Zoo.
• Wei Ouyang, Assistant Professor at KTH and leader of the AICell Lab at SciLifeLab, Sweden, introduced BioEngine.
• Caterina Fuster-Barceló, Post-doctoral researcher at Universidad Carlos III de Madrid (UC3M), presented the BioImage.IO chatbot.
• Vera Galinova, bioimage analyst and research software engineer at Human Technopole, showcased the first Open Call selected projects and future Challenges.

The session recording is now available for public access, so if you missed it, here’s your opportunity to catch up!

This past February, the AI4Life project was one of the efforts that took part on the stage at the Effectively Communicating Bioimage Analysis Workshop, held from the 12th to the 15th. Organised by The Company of Biologists and Focal Plane, the event proved to be a resounding success, drawing in members of the AI4Life project alongside a host of other well-established members of our great community.

The workshop served as a critical platform for exchange over some of the bioimage analysis community’s most pressing challenges. 

Among the highlights was the participation of Florian Jug from the HT in Milan, who captivated the audience as one of the invited speakers. Jug presented the AI4Life project and its initiatives, including the BioImage Model Zoo and Open Calls, showcasing the remarkable progress and achievements of the project over recent years. His presentation underscored the project’s efforts in bridging the divide between life scientists and developers, earning widespread admiration for its contributions.

Caterina Fuster-Barceló, representing the Universidad Carlos III de Madrid, Spain, also made significant contributions as part of the early-career researchers funded to attend. Chosen from numerous applications, Caterina represented the deepImageJ team, a Community Partner of the BioImage Model Zoo. She introduced the latest developments of the BioImage.IO Chatbot, a tool designed to address the challenges faced by deepImageJ and bioimage analysis at large.

The workshop not only served as a venue for learning and sharing but also as an opportunity for participants to connect with both new and familiar faces in a friendly and engaging environment. The event’s success reflects the community’s collective effort to foster an atmosphere conducive to growth, collaboration, and fun.

AI4Life stands at the forefront of reducing the gap between AI method development and biological imaging, offering essential services through European transnational and virtual access infrastructures. The project’s participation in the workshop is a testament to its commitment to advancing the field of bioimage analysis, marking yet another milestone in its journey towards integrating AI-based methods into the life sciences.

We’ve launched a new section on our website dedicated to guiding you on how to engage with our project.

Are you looking to participate, collaborate, or simply learn more about AI4Life? Our new section has all the answers. Find out how you can contribute, connect, and engage with us effortlessly!

Explore the new section: https://ai4life.eurobioimaging.eu/engage/ 

The Bioimage Analysis software BiaPy has officially joined the BioImage Model Zoo as a Community Partner! This means that the BiaPy software supports the BioImage.io format for deep learning models.

BiaPy is an open source Python library to easily build bioimage analysis pipelines based on deep-learning approaches. The library supports the image processing of 2D, 3D and multichannel microscopy image data. Specifically, BiaPy contains ready-to-use solutions for tasks such as semantic segmentation, instance segmentation, object detection, image denoising, single image super-resolution and image classification, as well as self-supervised learning alternatives.

At present, BiaPy Jupyter notebooks already exporting BioImage.io compatible models are accessible through the BioImage Model Zoo. A future expansion of the current offer by adding a variety of models, including transformers, is expected. The integration of BiaPy in the BioImage Model Zoo aims to enhance the library’s visibility, foster greater collaboration, and serve the community better by increasing the variety of advanced image processing approaches, which significantly empowers the field of BioImage Analysis.

We’re happy to share our latest resource: the AI4Life factsheet! This document provides a comprehensive overview all the important outputs and accomplishments of the project at a glance.

We’ll continuously update this Factsheet to ensure it remains a current resource. Whether you’re preparing a presentation, seeking project insights, or diving into the project’s accomplishments, this Factsheet is what you are looking for.

Feel free to explore and use the AI4Life Factsheet in your outreach activities!

AI4Life recently participated in a series of Machine Learning mini-hackathons hosted by NFDI4DataScience at ZB MED in Cologne (Germany). Our team engaged in two different sessions, aiming to define the Machine Learning lifecycle and to discuss the metadata required for each step.

Machine Learning Lifecycle (21-22 November 2023)
Throughout the two-day event, our objectives revolved around defining the lifecycle steps, creating a graphical representation and fostering compliance with FAIR principles. To extend the discussion to the broader community, the outcomes have been presented at the RDA FAIR4ML Interest Group.

Metadata for Machine Learning (23-24 November 2023)
This session focused on mapping metadata, datasets and applications across various platforms like the DOME registry, Bioimage.io, OpenML, and schema.org, significantly contributing to standardizing ML metadata.

AI4Life’s participation in these mini-hackathons underlines the project’s commitment to enhancing the BioImage Model Zoo models specification to make them interoperable with resources outside the imaging community.

These events carried out during the Machine Learning hackathon at ZB MED sponsored by NFDI4DataScience. NFDI4DataScience is a consortium funded by the German Research Foundation (DFG), project number 460234259.

Introducing the BioImage.IO Chatbot, a game-changer for the bioimage analysis community. This cutting-edge AI-driven assistant is revolutionizing how biologists, bioimage analysts, and developers interact with advanced tools. The BioImage.IO Chatbot excels in delivering personalized responses, code generation, and execution, as demonstrated by various usage examples.

The BioImage.IO Chatbot draws from diverse sources, including databases like ELIXIR bio.tools, documentation from different tools and softwares such as deepImageJ or ImJoy, and the BioImage Model Zoo documentation, ensuring tailored, context-aware answers. The result? Personalized responses that cater to users’ unique requirements.

Distinguished by its versatility, the chatbot adeptly handles both simple and technical queries, ensuring that it remains a valuable asset to users of all backgrounds. What’s more, we are enthusiastic about fostering a community-driven ecosystem. We encourage individuals to integrate their documentation and data sources into our knowledge base, thereby enriching the experience for everyone.

As we prepare for the upcoming beta testing phase (sign up here), join us in witnessing how the BioImage.IO Chatbot is reshaping the landscape of bioimage analysis. Be a part of this transformative journey!

For a detailed overview, check out our preprint.

After a highly successful 2nd General Assembly in Heidelberg, AI4Life took advantage of the gathered members and organized a Hackathon & Solvathon. The event was held from October 10th to 13th, 2023, with a total of 25 participants.

Two parallel events ran during this period:

• Hackathon: Focused on building and deploying AI tools for bioimage analysis, enhancing scalability and FAIRness. Participants engaged in discussions, formed interest groups around projects, and collaborated on various web & cloud bioimage analysis topics.
  The Hackathon members participated in a number of projects:
  • EDAM & bio.tools collaboration with AI4Life
  • Segment Anything in the BioEngine
  • Segment Anything in the BioImage Model Zoo
  • bioimageio Python packages
  • bioimageio uploader
  • ChatBot for the BioImage Model Zoo
  • Documentation improvement
  • Kubernetes BioEngine on Google Cloud
  • Semantic Segmentation of cartilaginous tissue
• Solvathon: Experts from AI4Life and beyond worked together on the 8 selected open-call projects. Detailed progress updates on these projects will be shared soon.

Both tracks achieved remarkable outcomes. Stay tuned for the next event!

A new video has been released through our YouTube channel. We asked the participants of the recent Hackathon & Solvathon for a word that describes AI4Life. Hear what they said below!