e-learning
Voronoi segmentation
Abstract
Voronoi segmentation is a technique used to divide an image or space into regions
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 do I partition an image into regions based on which object they are nearest to (Voronoi segmentation)?
- How should images be preprocessed before applying Voronoi segmentation?
- How can I overlay two images?
- How can Voronoi segmentation be used to analyze spatial relationships?
- How can extracted image properties be used to categorize identified objects?
Learning Objectives
- How to perform Voronoi Segmentation in Galaxy.
- How to extract a single channel from an image.
- How to overlay two images.
- How to count objectives in a layer map.
Licence: Creative Commons Attribution 4.0 International
Keywords: Imaging, imageanalysis, segmentation, voronoi
Target audience: Students
Resource type: e-learning
Version: 3
Status: Active
Prerequisites:
- FAIR Bioimage Metadata
- Introduction to Galaxy Analyses
- Introduction to Image Analysis using Galaxy
- REMBI - Recommended Metadata for Biological Images – metadata guidelines for bioimaging data
Learning objectives:
- How to perform Voronoi Segmentation in Galaxy.
- How to extract a single channel from an image.
- How to overlay two images.
- How to count objectives in a layer map.
Date modified: 2025-05-27
Date published: 2025-05-13
Contributors: Beatriz Serrano-Solano, Björn Grüning, Even Moa Myklebust, Leonid Kostrykin
Scientific topics: Imaging
External resources:
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