QuPath Introductory course 2026

The course intends to give a brief introduction (Theoretical & Practical) to the use of QuPath (free open-source software for "Quantitative Pathology") for analysis of tiled & stitched large image datasets, such as those obtained with slide scanners from Histopathology and Bioimaging Platforms.

The course will include:

1) Introduction to image analysis basic concepts (4th May)

2) Introduction to QuPath software (5th-6th May)

• Data visualization and representation 
• Image segmentation
• Classification with machine learning
• Brief introduction to deep learning with QuPath extensions and automation with groovy workflows
• Exercises

REQUIREMENTS: 

Trainees must bring their own laptop, power supply, mouse and must have had previous contact with ImageJ/FIJI at a basic level.

Trainees must attend all sessions in person, this is mandatory.

Typology: In Person. 

Trainees will follow lectures and exercise with local trainers in a room. Some lectures will be broadcasted by other trainers remotely from Portugal/Netherlands. Overall, the course will happen simultaneously across several nodes. 

Capacity/audience: 18 trainees. The course is ideally suited to PhD candidates, Postdocs and research staff whose work requires to visualize and/or analyze large tissue sections images (e.g. H&E, fluorescence, etc...).

Participants selection: The organizers will select applicants based on adequacy of the training content to motivations of the applicants, and if needed based on homogeneous distribution across groups.