e-learning
Using BioImage.IO models for image analysis in Galaxy
Abstract
Deep learning models are increasingly used in bioimage analysis to perform processing steps such as segmentation, classification, and restoration tasks (e.g.,. The BioImage Model Zoo, (BioImage.IO) is a repository that provides access to pre-trained AI models, sharing a common metadata model that allows their reuse in different tools and platforms.
About This Material
This is a Hands-on Tutorial from the GTN which is usable either for individual self-study, or as a teaching material in a classroom.
Questions this will address
- How can I apply a pre-trained deep learning model to an image?
- How does the BioImage.IO format integrate with Galaxy?
- What kind of outputs are generated by the model?
Learning Objectives
- Learn how to run a BioImage.IO model using Galaxy
- Understand how to format image inputs and model axes
- Interpret and download the model output
Licence: Creative Commons Attribution 4.0 International
Keywords: AI, Imaging, bioimaging
Target audience: Students
Resource type: e-learning
Version: 5
Status: Active
Prerequisites:
- FAIR Bioimage Metadata
- Introduction to Galaxy Analyses
- REMBI - Recommended Metadata for Biological Images – metadata guidelines for bioimaging data
Learning objectives:
- Learn how to run a BioImage.IO model using Galaxy
- Understand how to format image inputs and model axes
- Interpret and download the model output
Date modified: 2025-04-16
Date published: 2025-04-09
Contributors: Anup Kumar, Beatriz Serrano-Solano, Björn Grüning, Diana Chiang Jurado, Leonid Kostrykin, Saskia Hiltemann
Scientific topics: Imaging
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