QuPath: Open source software for digital pathology image analysis
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Abstract
QuPath is new bioimage analysis software designed to meet the growing need for a user-friendly, extensible, open-source solution for digital pathology and whole slide image analysis. In addition to offering a comprehensive panel of tumor identification and high-throughput biomarker evaluation tools, QuPath provides researchers with powerful batch-processing and scripting functionality, and an extensible platform with which to develop and share new algorithms to analyze complex tissue images. Furthermore, QuPath's flexible design makes it suitable for a wide range of additional image analysis applications across biomedical research.
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Frameworks such as TensorFlow and PyTorch support AI model development, while tools like QuPath enable image annotation and analysis.
“On the software side, frameworks such as TensorFlow and PyTorch support AI model development, while tools like QuPath enable image annotation and analysis [44].”
From Artificial Intelligence in Dermatopathology: An Update and Review of the Current Literature (2026) · cites this paper as [44]
The Introduction (page not provided) describes QuPath as whole-slide image analysis software with annotation and visualization tools, supporting the QuPath portion of the sentence. Our copy does not address TensorFlow or PyTorch or their role in AI model development, so it does not support that portion. (LLM, conf=0.84)
Experimental — accuracy not yet measuredStandardized open-source tools, collaborative multi-institutional annotation efforts, and AI-assisted annotation workflows reduce manual burden.
“Emerging solutions include standardized open-source tools (e.g., QuPath) [44], collaborative multi-institutional annotation efforts, and AI-assisted annotation workflows that reduce manual burden [45].”
From Artificial Intelligence in Dermatopathology: An Update and Review of the Current Literature (2026) · cites this paper as [44]
Ultrastructural analyses were performed using QuPath on images blinded to both animal and group.
“The microglial ultrastructural analyses was performed using QuPath (v.0.4.4) [71] on images blinded to both animal and group, following an adaptation from our previous work [56, 64].”
From Sex chromosomes and sex hormones differently shape microglial properties during normal physiological conditions in the adult mouse hippocampus (2025) · cites this paper as [71]
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- Authors
- Bankhead, P., Loughrey, M. B., Fernández, J. A., Dombrowski, Y., McArt, D. G., Dunne, P. D., McQuaid, S., Gray, R. T., Murray, L. J., Coleman, H. G., James, J. A., Salto-Tellez, M., & Hamilton, P. W.
- Affiliations
- Queen's University Belfast (GB)
- Corresponding author
- Hamilton, Peter W.
- ORCID
- Venue
- Scientific Reports
- Published
- 2017-12-04
- Volume
- 7
- Issue
- 1
- Pages
- 16878-16878
- ISSN
- 2045-2322 (ISSN-L)
- PMC
- PMC5715110
- OpenAlex
- W2952481429
- Cited by
- 8,908
- References
- 36
- Citations by year
- 2026: 1616 · 2025: 1896 · 2024: 1681 · 2023: 1359 · 2022: 1023 · 2021: 704 · 2020: 396 · 2019: 171 · 2018: 49 · 2017: 4 · 2016: 1
- FWCI
- 99.74
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Scientific Reports (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
- Funders
- Invest Northern Ireland (RDO0712612)
- Friends of the Cancer Centre
- Cancer Research UK (20256, A15333, C37703/A15333, C11512, A20256, C11512/A20256, C50104/A17592, 15333)
- Public Health Agency (SPI/3315/06, EAT/4905/13)
- Health and Social Care Research and Development Division
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
- Keywords
- QuPath, digital pathology, whole slide image analysis, open source software, tumor detection, biomarker analysis, batch processing, scripting, tissue image analysis
- MeSH terms
- Algorithms, Colonic Neoplasms, Humans, Image Interpretation, Computer-Assisted, Biomarkers, Tumor, User-Computer Interface, Kaplan-Meier Estimate, Programmed Cell Death 1 Ligand 2 Protein
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