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- Introduction to Image Analysis 2026
- Programme
Monday 18 May
10:00 – 11:30
Session 1: Introduction & Installations
Session One: Introduction & Installations
11:45 – 13:15
Session 2: Image Pre-Processing, Segmentation & Analysis
Session Two: Image Pre-Processing, Segmentation & Analysis
14:25 – 15:45
Session 3: Assembling Pipelines and Interpreting Results
Session Three: Assembling Pipelines and Interpreting Results
16:00 – 17:30
16:00 - 17:30 Session 4: Extending Analyses to Three Dimensions
Session four: Extending Analyses to Three Dimensions
Tuesday 19 May
09:00 – 10:30
Session 5: Using GitHub for Code Version Control
Session Five: Using GitHub for Code Version Control
10:45 – 12:15
Session 6: Using Jupyter Notebooks for Reproducible Analysis - Part 1
Session Six: Using Jupyter Notebooks for Reproducible Analysis - Part 1
13:15 – 14:45
Session 7: Using Jupyter Notebooks for Reproducible Analysis - Part 2
Session Seven: Using Jupyter Notebooks for Reproducible Analysis - Part 2
15:00 – 16:30
Session Eight: Introduction to Batch Processing with Jupyter Notebooks
Session Eight: Introduction to Batch Processing with Jupyter Notebooks
16:30 – 18:00
Session 9: Extending Analyses to Three Dimensions in Python
Session Nine: Extending Analyses to Three Dimensions in Python
Wednesday 20 May
09:00 – 10:30
Session 10: Using Napari for Image Visualisation
Session Ten: Using Napari for Image Visualisation
10:45 – 12:15
Session 11: Introduction to Machine Learning for Image Analysis - Part 1
Session Eleven: Introduction to Machine Learning for Image Analysis - Part 1
13:15 – 14:45
Session 12: Introduction to Machine Learning for Image Analysis - Part 2
Session Twelve: Introduction to Machine Learning for Image Analysis - Part 2