The DOI matches its Crossref record; 120 of the 120 references it cites were found in a registry or an index.
Introduction to Digital Image Analysis in Whole-slide Imaging: A White Paper from the Digital Pathology Association
Open accessAbstract
The advent of whole-slide imaging in digital pathology has brought about the advancement of computer-aided examination of tissue via digital image analysis. Digitized slides can now be easily annotated and analyzed via a variety of algorithms. This study reviews the fundamentals of tissue image analysis and aims to provide pathologists with basic information regarding the features, applications, and general workflow of these new tools. The review gives an overview of the basic categories of software solutions available, potential analysis strategies, technical considerations, and general algorithm readouts. Advantages and limitations of tissue image analysis are discussed, and emerging concepts, such as artificial intelligence and machine learning, are introduced. Finally, examples of how digital image analysis tools are currently being used in diagnostic laboratories, translational research, and drug development are discussed.
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Cites
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QuPath: Open source software for digital pathology image analysis
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Cited by
Digital pathology and artificial intelligence in translational medicine and clinical practice
Baxi, V., Edwards, R., Montalto, M., & Saha, S. (2022) · Modern Pathology · doi:10.1038/s41379-021-00919-2 · Cited by 592
Artificial intelligence and computational pathology
Cui, M., & Zhang, D. Y. (2021) · Laboratory Investigation · doi:10.1038/s41374-020-00514-0 · Cited by 544
Abels, E., Pantanowitz, L., Aeffner, F., Zarella, M. D., van der Laak, J., Bui, M. M., Vemuri, V. N., Parwani, A. V., Gibbs, J., Agosto‐Arroyo, E., et al. (2019) · The Journal of Pathology · doi:10.1002/path.5331 · Cited by 459
Self-citationArtificial intelligence (AI) and big data in cancer and precision oncology
Dlamini, Z., Francies, F. Z., Hull, R., & Marima, R. (2020) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2020.08.019 · Cited by 398
Whole Slide Imaging (WSI) in Pathology: Current Perspectives and Future Directions
Kumar, N., Gupta, R., & Gupta, S. (2020) · Journal of Digital Imaging · doi:10.1007/s10278-020-00351-z · Cited by 299
Metadata
- Authors
- Aeffner, F., Zarella, M. D., Buchbinder, N., Bui, M. M., Goodman, M. R., Hartman, D. J., Lujan, G. M., Molani, M. A., Parwani, A. V., Lillard, K., Turner, O. C., Vemuri, V. N. P., Yuil-Valdes, A. G., & Bowman, D.
- Venue
- Journal of Pathology Informatics
- Publisher
- Elsevier BV
- Published
- 2019-01
- Volume
- 10
- Issue
- 1
- Pages
- 9
- ISSN
- 2153-3539 (ISSN-L)
- OpenAlex
- W2921675148
- Cited by
- 403
- References
- 120
- FWCI
- 22.10
- Type
- journal article
- Language
- en
- Open access
- gold
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- Aeffner, F., Zarella, M. D., Buchbinder, N., Bui, M. M., Goodman, M. R., Hartman, D. J., Lujan, G. M., Molani, M. A., Parwani, A. V., Lillard, K., Turner, O. C., Vemuri, V. N. P., Yuil-Valdes, A. G., & Bowman, D. (2019). Introduction to Digital Image Analysis in Whole-slide Imaging: A White Paper from the Digital Pathology Association. Journal of Pathology Informatics. https://doi.org/10.4103/jpi.jpi_82_18
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
