e-learning
Parameter tuning and optimization - Evaluating nuclei segmentation with Galaxy
Abstract
Parameter tuning is super important in image analysis.
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
- What are the challenges of using the same settings for every biological image, and how does parameter tuning address these challenges?
- How can we choose the best filters for preprocessing images for nuclei segmentation?
Learning Objectives
- Understand the importance of parameter tuning in bioimage analysis for achieving accurate results
- Learn how to perform parameter tuning for segmentation in Galaxy
Licence: Creative Commons Attribution 4.0 International
Keywords: Imaging, bioimaging
Target audience: Students
Resource type: e-learning
Version: 1
Status: Active
Prerequisites:
- FAIR Bioimage Metadata
- Introduction to Galaxy Analyses
- REMBI - Recommended Metadata for Biological Images – metadata guidelines for bioimaging data
Learning objectives:
- Understand the importance of parameter tuning in bioimage analysis for achieving accurate results
- Learn how to perform parameter tuning for segmentation in Galaxy
Date modified: 2025-04-28
Date published: 2025-04-28
Contributors: Beatriz Serrano-Solano, Leonid Kostrykin, Riccardo Massei
Scientific topics: Imaging
External resources:
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