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Welcome to the QuPath wiki!
This is the main place for QuPath documentation, to help you become familiar with using QuPath for whole slide image analysis.
You can download QuPath from the Latest Release page.
Below are some of the main features of the QuPath software. If you want to learn more, please use the links on the right sidebar to get started.
Whole slide viewing
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
Tissue Microarray support
Automated dearraying of Tissue Microarrays and the ability to view related cores side-by-side
Sophisticated tumor identification
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
Flexible object classification
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
User-friendly automated analysis
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
Analytics & export
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
The QuPath software has been developed as part of projects that have received funding from:
- Invest Northern Ireland (RDO0712612)
- Cancer Research UK Accelerator (C11512/A20256)