QuPath

QuPath is the open-source standard for whole-slide image analysis in digital pathology. It handles the gigapixel slides that break general-purpose image software, and it does so well enough that it has become the default in a great many pathology and tissue-analysis groups.

What it does

It supports whole-slide formats directly, with tools for tissue and cell detection, tumour region annotation, biomarker scoring, stain deconvolution for brightfield IHC, and object classification trained interactively on your own annotations. Scripting in Groovy makes analyses reproducible and batchable across slide cohorts.

Strengths

• Free and open source, purpose-built for whole-slide images.
• Handles gigapixel files that defeat general image tools.
• Interactive classifier training without writing code.
• Scriptable for reproducible cohort-scale analysis.
• Strong support for brightfield IHC and multiplex fluorescence.

Limitations

Whole-slide work is memory-hungry and a capable workstation is effectively required. The learning curve is meaningful for anyone without image-analysis background, and interactively trained classifiers are only as good as the annotations behind them — they encode the annotator’s bias faithfully. Clinical use requires validation well beyond installing it.