The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Whole Slide Imaging (WSI) in Pathology: Current Perspectives and Future Directions
Open accessAbstract
Whole slide imaging (WSI), ever since its first introduction about two decades ago, has been validated for a number of applications in the field of pathology. The recent approval of US FDA to a WSI system for use in primary surgical pathology diagnosis has opened avenues for wider acceptance and application of this technology in routine practice. The ongoing technological advances in digital scanners, image visualization methods, and the integration of artificial intelligence-derived algorithms with these systems provide opportunities of its newer applications. Its benefits are innumerable such as ease of access through internet, avoidance of physical storage space, and no risk of deterioration of staining quality or breakage of slides to name a few. Various barriers such as the high cost, technical glitches, and professional hesitation to adopt a new technology have hindered its use in pathology. This review article summarizes the technical aspects of WSI, its applications in diagnostic pathology, training, and research along with future perspectives. It highlights the benefits, limitations, and challenges delaying the use of this technology in routine practice. The review is targeted at students, residents, and budding pathologists to better acquaint them with the key aspects of state-of-the-art technology and enable them to implement WSI judiciously.
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Digital Imaging in Pathology: Whole-Slide Imaging and Beyond
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Review of the current state of whole slide imaging in pathology
Pantanowitz, L., Valenstein, P. N., Evans, A. J., Kaplan, K. J., Pfeifer, J. D., Wilbur, D. C., Collins, L. C., & Colgan, T. J. (2011) · Journal of Pathology Informatics · doi:10.4103/2153-3539.83746 · Cited by 435
A Practical Guide to Whole Slide Imaging: A White Paper From the Digital Pathology Association
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Whole slide imaging in pathology: advantages, limitations, and emerging perspectives
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Pantanowitz, L., Sharma, A., Carter, A. B., Kurc, T., Sussman, A., & Saltz, J. (2018) · Journal of Pathology Informatics · doi:10.4103/jpi.jpi_69_18 · Cited by 282
Virtual microscopy in pathology education
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Cited by
Digital pathology and computational image analysis in nephropathology
Barisoni, L., Lafata, K. J., Hewitt, S. M., Madabhushi, A., & Balis, U. G. J. (2020) · Nature Reviews Nephrology · doi:10.1038/s41581-020-0321-6 · Cited by 264
Image annotation and curation in radiology: an overview for machine learning practitioners
Galbusera, F., & Cina, A. (2024) · European Radiology Experimental · doi:10.1186/s41747-023-00408-y · Cited by 62
Zehra, T., Parwani, A., Abdul-Ghafar, J., & Ahmad, Z. (2023) · Diagnostic Pathology · doi:10.1186/s13000-023-01352-6 · Cited by 43
Advancing biological understanding of cellular senescence with computational multiomics
Li, S., Agudelo Garcia, P. A., Aliferis, C., Becich, M. J., Calyeca, J., Cosgrove, B. D., Elisseeff, J., Farzad, N., Fertig, E. J., Glass, C., et al. (2025) · Nature Genetics · doi:10.1038/s41588-025-02314-y · Cited by 40
Duschner, N., Baguer, D. O., Schmidt, M., Griewank, K. G., Hadaschik, E., Hetzer, S., Wiepjes, B., Le'Clerc Arrastia, J., Jansen, P., Maass, P., et al. (2023) · JDDG: Journal der Deutschen Dermatologischen Gesellschaft · doi:10.1111/ddg.15180 · Cited by 14
Metadata
- Authors
- Kumar, N., Gupta, R., & Gupta, S.
- Venue
- Journal of Digital Imaging
- Published
- 2020-05-28
- Volume
- 33
- Issue
- 4
- Pages
- 1034-1040
- ISSN
- 0897-1889 (ISSN-L)
- 1618-727X
- OpenAlex
- W3030555654
- Cited by
- 299
- References
- 32
- FWCI
- 8.81
- Type
- journal article
- Language
- en
- Open access
- bronze
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