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AI4Life at the 5th NEUBIAS Conference

AI4Life at the 5th NEUBIAS Conference

by Estibaliz Gómez-de-Mariscal

The 5th NEUBIAS Conference took place in Porto during the week of May 8th, 2023. It brought together experts in BioImage Analysis for the Defragmentation Training School and the Open Symposium. AI4Life actively participated in the event, contributing to both parts and covering topics from zero code Deep Learning tools, the Bioimage Model Zoo, BiaPy, Segment Anything for Microscopy, among others. Estibaliz Gómez-de-Mariscal has written a post in FocalPlane summarising the discussions and outcomes.

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AI4Life at Focus on Microscopy

AI4Life at Focus on Microscopy

14 April 2023

by Estibaliz Gómez de Mariscal

AI4Life was present this year at the Focus on Microscopy (FOM) 2023 conference in Porto, Portugal. 

FOM is a yearly conference series presenting the latest innovations in optical microscopy and its applications to life sciences. 

This year, the BioImage Model Zoo was presented again in one of the two dedicated oral sessions for image analysis under the title “BioImage Model Zoo: Accessible AI models for microscopy image analysis in one-click”. We highlight two of the most exciting discussion topics around AI4Life: “We need more deep-learning model benchmarks tailored for direct applications in life sciences” and “How can I upload my work to the BioImage Model Zoo”.

Remarkably, this year there was for the first time a dedicated section about smart microscopy where hybrid approaches using deep learning for adaptive optics and data-driven acquisitions were presented.

AcknowledgementS
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past events

Workshop: Towards FAIR AI image data

Workshop: Towards FAIR AI image data

Date

Venue

Description

24-25 January, 2023

Online

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. The BIA currently supports basic deposition of image annotations together with corresponding images. As part of the recently awarded Horizon Europe project, AI4LIFE, we would like to improve the BioImage Archive’s support for image annotations as part of AI-ready datasets.
In particular, we wish to make deposited annotations as widely usable as possible, adhering to the FAIR principles of Findability, Accessibility, Interoperability and Reusability. This is particularly challenging for image annotations, since there are few standards for representing annotation data that are widely adopted across the community.
Towards this end, we will hold a workshop involving participants from the bioimaging AI community, including data generators, annotators, AI researchers and software/tool developers.