The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
QuPath: Open source software for digital pathology image analysis
Open accessPublished version of a preprint
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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“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]
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“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]
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“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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Citations
Cites
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
Fiji: an open-source platform for biological-image analysis
Schindelin, J., Arganda-Carreras, I., Frise, E., Kaynig, V., Longair, M., Pietzsch, T., Preibisch, S., Rueden, C., Saalfeld, S., Schmid, B., et al. (2012) · Nature Methods · doi:10.1038/nmeth.2019 · Cited by 66,890
NIH Image to ImageJ: 25 years of image analysis
Schneider, C. A., Rasband, W. S., & Eliceiri, K. W. (2012) · Nature Methods · doi:10.1038/nmeth.2089 · Cited by 64,638
PD-1 and PD-L1 Immune Checkpoint Blockade to Treat Breast Cancer
Hartkopf, A. D., Taran, F., Wallwiener, M., Walter, C. B., Krämer, B., Grischke, E., & Brucker, S. Y. (2016) · Breast Care · doi:10.1159/000453569 · Cited by 30,989
Textural Features for Image Classification
Haralick, R. M., Shanmugam, K., & Dinstein, I. (1973) · IEEE Transactions on Systems, Man, and Cybernetics · doi:10.1109/tsmc.1973.4309314 · Cited by 22,886
Adverse Renal Effects of Immune Checkpoint Inhibitors: A Narrative Review
Wanchoo, R., Karam, S., Uppal, N. N., Barta, V. S., Deray, G., Devoe, C., Launay‐Vacher, V., Jhaveri, K. D., & on behalf of Cancer and Kidney International Network Workgroup on Immune Checkpoint Inhibitors (2017) · American Journal of Nephrology · doi:10.1159/000455014 · Cited by 15,320
SLIC Superpixels Compared to State-of-the-Art Superpixel Methods
Achanta, R., Shaji, A., Smith, K., Lucchi, A., Fua, P., & Susstrunk, S. E. (2012) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2012.120 · Cited by 9,451
Type, Density, and Location of Immune Cells Within Human Colorectal Tumors Predict Clinical Outcome
Galon, J., Costes, A., Sanchez-Cabo, F., Kirilovsky, A., Mlecnik, B., Lagorce-Pagès, C., Tosolini, M., Camus, M., Berger, A., Wind, P., et al. (2006) · Science · doi:10.1126/science.1129139 · Cited by 6,516
Pembrolizumab for the Treatment of Non–Small-Cell Lung Cancer
Garon, E. B., Rizvi, N. A., Hui, R., Leighl, N., Balmanoukian, A. S., Eder, J. P., Patnaik, A., Aggarwal, C., Gubens, M., Horn, L., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1501824 · Cited by 6,198
Quantification of histochemical staining by color deconvolution.
Ruifrok, A. C. C., & Johnston, D. A. (2001) · PubMed · Cited by 2,029
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CellProfiler 4: improvements in speed, utility and usability
Stirling, D. R., Swain-Bowden, M. J., Lucas, A. M., Carpenter, A. E., Cimini, B. A., & Goodman, A. (2021) · BMC Bioinformatics · doi:10.1186/s12859-021-04344-9 · Cited by 2,109
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Ramachandran, P., Dobie, R., Wilson-Kanamori, J. R., Dora, E. F., Henderson, B. E. P., Luu, N. T., Portman, J. R., Matchett, K. P., Brice, M., Marwick, J. A., et al. (2019) · Nature · doi:10.1038/s41586-019-1631-3 · Cited by 1,784
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Graham, S., Vu, Q. D., Raza, S. E. A., Azam, A. S., Tsang, Y. W., Kwak, J. T., & Rajpoot, N. (2019) · Medical Image Analysis · doi:10.1016/j.media.2019.101563 · Cited by 1,516
Kather, J. N., Krisam, J., Charoentong, P., Luedde, T., Herpel, E., Weis, C.-A., Gaiser, T., Marx, A., Valous, N. A., Ferber, D., et al. (2019) · PLOS Medicine · doi:10.1371/journal.pmed.1002730 · Cited by 1,082
Metadata
- 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
- 37
- Citations by year
- 2026: 1616 · 2025: 1896 · 2024: 1681 · 2023: 1359 · 2022: 1023 · 2021: 704 · 2020: 396 · 2019: 171 · 2018: 49 · 2017: 4
- 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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