QuPath aims to help improve the speed, objectivity and reproducibility of digital pathology analysis and biomarker interpretation by offering an open, powerful, flexible, extensible software platform for whole slide image analysis.
QuPath has been developed for research applications at the Centre for Cancer Research & Cell Biology at Queen's University Belfast, as part of research projects funded by Invest Northern Ireland and Cancer Research UK.
The primary publication describing QuPath is now available open access - please cite it if you use QuPath in your work!
Other publications involving QuPath are listed in the documentation.
The QuPath Bio-Formats extension received a major update in January 2018. Lots of bug fixes and performance improvements now mean that more whole slide formats work better and faster with QuPath.
Read more about the update here.
In the meantime, don't forget there's a QuPath forum at Google Groups, where questions are asked, ideas are shared, and announcements are made.
Fast, flexible image viewer capable of displaying whole slide images (often > 30 GB uncompressed) using dynamic color transforms (e.g. stain separation) and tracking slide navigation
Nuclear, cytoplasmic & membranous biomarkers can all be quantified quickly using automated segmentation algorithms combined with trainable cell classification
Automated dearraying of Tissue Microarrays and the ability to view related cores side-by-side
Powerful tumor identification algorithms can be applied directly to slides of interest - including slides stained for immune cells - without the need to stain for a separate tumor marker
Large image regions are split into tiles where necessary, and these tiles analyzed in parallel with efficient algorithms - giving fast results without requiring specialist hardware
Apply object classification with the default ‘out-of-the-box’ random forest classifier (from OpenCV), or create highly-customized algorithms by tuning the choice of classifier, parameters and features used
Extensive tools for slide navigation, annotating areas, exporting image regions or counting cells - either manually, or using automated cell detection
Workflows provide guided analysis for common tasks, or users can devise their own approaches by running commands in any order, which are automatically logged for reproducibility
Analysis can be tailored to different stains and scanners using advanced stain estimation, visualization & optimization tools
Experienced users can enter commands and write scripts to perform sophisticated, customized analysis using QuPath’s powerful, efficient hierarchical data structures
Exchange data with open source tools (e.g. ImageJ), or read images from a variety of sources, including cloud-based hosting
Create interactive results tables, histograms, scatterplots & survival curves directly within QuPath, or export results in standard formats to import into other software if required
View measurements in context by color coding objects according to their features, e.g. to identify hotspots or visualize cell distributions for immuno-oncology applications
QuPath has been developed as a cross-platform application that runs on Windows, Mac OS X and Linux to support a wide range of applications and image types across pathology and the biosciences