AI4Life

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Outcomes of the hackathon on web and cloud infrastructure for AI-powered bioimage analysis

Outcomes of the Hackathon on Web and Cloud infrastructure for AI-powered bioimage analysis

by Caterina Fuster-Barceló

The AI4Life Hackathon on Web and Cloud Infrastructure for AI-Powered BioImage Analysis recently took place at SciLifeLab in Stockholm, Sweden. Organized by Wei Ouyang of KTH Sweden, in partnership with AI4Life and Global BioImaging, the event aimed to bring together experts in the field to discuss and design advanced web/cloud infrastructure for bioimage analysis using AI tools. Participants from both academia and industry worldwide attended, showcasing platforms like BioImage Model Zoo, Fiji, ITK, Apeer, Knime, ImJoy, Piximi, Icy, and deepImageJ. Read more in this article written by the project partners in FocalPlane.

 

 

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Outcomes of the hackathon “Deep Learning in Java”

Outcomes of the Hackathon “deep Learning in Java”

Milan, 6-10 February 2023

by Florian Jug

Global BioImaging and AI4Life organized a hackathon in Milan from February 6-10, 2023. The overarching goal of this event was to improve the accessibility of Deep Learning methods in Java-based image analysis tools and libraries. The event was held at the Human Technopole and was attended by a total of 21 participants from various parts of the world. 

The participants, representing tools such as bioimage.io, deepImageJ, Fiji, Icy, ImageJ, ImJoy, and QuPath, self-organized into topic-groups on day one and then tackled various challenges to bridge the system gap between typically python-based deep learning methods and Java (i.e. ImgLib2 based) image processing. 

These topic-groups made significant progress on different fronts over the 5-day event. A more in-depth report will soon be made available as an BioHackrXiv preprint. Among the highlights was the integration of a library by Carlos Garcia and colleagues (model-runner-java) into deepImageJ (and therefore into Fiji) and several other participants using this new way of running deep learning models on images opened in ImgLib2 containers (e.g. directly from Fiji). This was even pushed to extremes by combining the execution of models live from within BigDataViewer, e.g., enabling lazy prediction on terabyte sized datasets.

Additionally, another topic-group explored alternative ways to use the model-runner-java library, by directly sharing memory between native python processes and running Java VMs. Similar solutions exist (see for example imglyb or PyImageJ), but the newly explored idea is not any longer based on sub-processes but instead on inter-process communication. The big advantage of this approach is that parallel processes can be started independently, hook into each other on demand using shared memory, work together but die alone.

All participants are now continuing to flesh out the work that was started during the event and releases of updated versions of deepImageJ and a Fiji and Icy based deep learning integration are on their way. These updates will benefit hundreds of users world-wide.

 
AcknowledgementS
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event report

Outcomes of the AI4Life & BioImage Archive FAIR AI Workshop

AI4Life & BIOIMAGE ARCHIVE FAIR AI WORKSHOP

Online, 24-25 January 2023

 

AI4Life & BioImage Archive FAIR AI Workshop

by Matthew Hartley and Teresa Zulueta-Coarasa

Artificial Intelligence (AI) and deep learning (DL) are transforming the way we analyse biological images, benefitting particularly the processing of large and heterogenous image datasets. The development of these AI models relies on high-quality annotated images, which will determine the model’s performance, robustness, and scalability. Therefore, providing open access to useful, annotated datasets adhering to the FAIR principles (Findability, Accessibility, Interoperability and Reusability), is essential for the development, reproducibility, and reuse of AI models. However, sharing biological image AI datasets is challenging due to the lack of standards for representing annotation data widely adopted across the community.

The BioImage Archive (BIA), EMBL-EBI’s data resource for open life sciences image data, provides general purpose deposition services for any imaging dataset accompanying a publication, as well as reference image data. As part of the AI4Life project, we want to improve the BIA’s support for image annotations as part of AI-ready datasets and to develop annotation standards for the community. 

To this end, we held a virtual workshop on the 24 and 25 of January with 46 community experts from various backgrounds, including data generators, annotators, curators, AI researchers and software developers. The participants discussed four main topics:

  • What are the important types of annotation to record, and what extra information/metadata should accompany them?
  • What are the useful ways (formats, metadata) to share and present annotation data?
  • How should we support/allow/encourage sharing and archival of annotations?
  • What are our community recommendations to accelerate AI methods development through sharing AI image annotations, what are the missing pieces?

Each topic was first discussed in breakout rooms and afterwards each group presented their conclusions to the rest of the participants. This approach resulted in lively and insightful discussions and a series of recommendations.

The immediate output from the workshop will be a white paper, co-authored by the workshop participants, summarising community recommendations. Furthermore, The BIA team is now working on transforming the workshop outcomes into metadata standards for AI datasets, and into software and tools to facilitate the deposition and sharing of AI images and annotations.

Beyond these outputs, we expect that the workshop recommendations will help annotation generators and consumers work together more effectively, facilitating the construction of benchmark collections of datasets to test model generalisation and reuse. Thank you to all the participants for their valuable contributions!

AcknowledgementS
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event report

BioHackathon Europe 2022

Biohackathon europe 2022

Paris, 7-11 November 2022

by Beatriz Serrano-Solano

AI4Life was present this year at the BioHackathon Europe 2022, which took place in November at Campus Des Berges de Seine, near Paris. Since 2018, ELIXIR Europe has been organising the BioHackathon to bring together both ELIXIR and non-ELIXIR members to work on projects aligned with the ELIXIR Platforms, Communities or Focus Groups.

The participation of AI4Life was focused on two projects:
Project 9: Disseminating FAIR Machine Learning Models via BioModels
Project 17: Metadata schemas supporting Linked Open Science (with a focus on reproducibility)

Through the interaction with these two projects, we explored the collaboration of the BioImage Model Zoo with databases like BioModels, by discussing the minimum metadata that would allow the interoperability between such resources. We also engaged with more initiatives like Bioschemas, the DOME recommendations, the EDAM ontology and the ELIXIR Machine Learning Focus Group.

We will be happy to continue these interactions, and we look forward to our future collaboration and participation in similar events.

AcknowledgementS
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event report

AI4Life First Hackathon

FIRST AI4LIFE HACKATHON

Heidelberg, 27-28 October 2022

by Beatriz Serrano-Solano

During the kick-off meeting in October 2022, the AI4Life project partners discussed and identified various topics that the team will be tackling over the next 3 years. Following up on the meeting outcomes, a two-day hackathon was organized to start working on those specific topics and challenges that came out of the discussion. Throughout the two-day event, participants were able to make significant progress, and soon after the beginning of the event, the first success stories started to arise. More of these events will follow during the 3 years of the project to keep the momentum and the collaboration going. Thank you to all the participants!

AcknowledgementS
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event report

Kick-off meeting in Heidelberg

Kick-off meeting

Heidelberg, 25-26 October 2022

by Beatriz Serrano-Solano

AI4Life European project is a collaborative effort that brings together 10 partners from 8 different European countries. Those partners include 4 European Research Infrastructures, covering a broad scope of scientific use cases: marine biology (EMBRC), plant phenotyping (EMPHASIS), compound screening (EU-OPENSCREEN) and structural biology (Instruct). The project is funded with a budget of 4 million euros, which will be used to bridge the gap between the computational and life science communities. AI4Life will last for 3 years, during which time the team will work together to achieve the project’s objectives:
  1. Democratized availability of AI-based image analysis methods.
  2. Establish standards for the submission, storage and FAIR access.
  3. Simple model deployment, sharing, and dissemination through a new developer-facing service.
  4. Organize Open Calls and Challenges for image analysis problems.
  5. Empower common image analysis platforms with AI integration.
  6. Organizing outreach and training events i.e. image analysis courses/workshops and participation in international conferences.

AI4Life officially started in September and kicked off at the end of October 2022. During the kick-off meeting, experts from across Europe gathered in Heidelberg for two days, during which the participants actively engaged in discussions about the timeline, milestones, deliverables and work distribution among the partners, and agreed on a plan for the next few months. The team members are also committed to maintaining an open line of communication with the audience and keeping them informed of the project’s progress throughout the duration of the project. 

Overall, the team had a productive meeting, and we are excited to begin working together.  Thank you to all the organizers, speakers, and participants!

Program
Time Topic Speaker/s
09:00 – 09:10 Welcome Rachel Robinson-Lehtinen
09:10 – 09:40 Introduction to AI4Life & Euro-BioImaging ERIC John Eriksson
09:40 – 09:50 Interactions with other Horizon Europe funded projects Antje Keppler
09:50 – 10:55 Interactions with partner RIs Aastha Mathur, Davide de Cioccio, Roland Pieruschka,
Katja Herzog, Silke Schumacher
10:55 – 11:00 Coffee Break
11:00 – 11:30 Message from the European Commission Project Adviser Antonio Ventura
European Research Executive Agency
11:30 – 12:00 EOSC and costing for cloud resources Peter Maccallum
CTO ELIXIR
12:00 – 13:00 Lunch & Group Photo
13:00 – 13:25 Project administration, timelines & reporting (WP1: Project Management) Rachel Robinson-Lehtinen
Appointment of the Executive Board
Appointment of the Open Calls Selection Committee
13:25 – 15:30 Introduction of Scientific Topics Anna Kreshuk & Florian Jug
WP2: User services & computing infrastructures Wei Ouyang
WP3: Direct support Arrate Muñoz
Discussion Anna Kreshuk & Florian Jug
15:30 – 15:40 Coffee Break
15:40 – 17:45 WP4: Contributing services Ricardo Henriques
WP5: Data, model & computing standards Matthew Hartley
WP6: Support for open calls, challenges & new services Florian Jug
WP7: Communication, outreach & training Aastha Mathur, Marianna Childress-Poli
Discussion Anna Kreshuk & Florian Jug
19:15 Dinner
Time Topic
09:00 – 12:30 Workshop on technical discussions / Pressing issues raised in Day 1
AcknowledgementS