Introduction to Bioimage Analysis using QuPath

Past workshop material


QuPath is a user-friendly, cross-platform, open-source software designed for digital pathology and whole slide image analysis. Since its initial release in 2017, it has become an essential tool for researchers who analyze brightfield (H&E, H-DAB) and fluorescence images.

The Image Analysis Collaboratory is running a workshop over two afternoons. Participation will be limited to ~20 people. The format will be a combination of tutorials and hands-on exercises (you will need a laptop with a decent size screen and admin privileges).


Wednesday 18th September 2024, 1 PM to 5 PM
Friday 20th September 2024, 1 PM to 5 PM


Harvard Medical School in Longwood, Boston, MA.



Skill level:



None, except a laptop and interest in learning some bioimage analysis.
If you are already somewhat advanced (you code your own workflows), this level is perhaps not for you, though you might want to learn about QuPath specifically.
Participation both days is required—if you can only make it one of the days, please apply for the next workshop.


First half-day:

  1. Introduction to digital image analysis, w. focus on bio-images
  2. Introduction to QuPath: general concepts (load an image, staining vectors, user-interface)
  3. Cell detection, features and cell classification
  4. Measurements export

Second half-day:

  1. Cell classification (machine learning-based)
  2. Tissue detection
  3. Density maps and spatial measurements
  4. Advanced topics (scripts, batch process)


Free of charge.


We will open for applications some time in advance—to be notified, please join our mailing list, if you didn’t already. If you have any questions, please feel free to reach out to Antoine Ruzette.

Deadline for application:



Mostly based on your short motivation. In case of oversubscription, the available spaces will be distributed evenly between labs and departments.


Our workshops are often oversubscribed by a factor of two or three, so please be considerate to your fellow applicants and let us know well in advance if you are accepted and cannot make it.

Looking forward to see you there
Antoine Ruzette, Federico Gasparoli, Ranit Karmakar, Maria Theiss, and Simon F. Nørrelykke.