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Overview of telepathology, virtual microscopy, and whole slide imaging: prospects for the future
Abstract
Telepathology, the practice of pathology at a long distance, has advanced continuously since 1986. Today, fourth-generation telepathology systems, so-called virtual slide telepathology systems, are being used for education applications. Both conventional and innovative surgical pathology diagnostic services are being designed and implemented as well. The technology has been commercialized by more than 30 companies in Asia, the United States, and Europe. Early adopters of telepathology have been laboratories with special challenges in providing anatomic pathology services, ranging from the need to provide anatomic pathology services at great distances to the use of the technology to increase efficiency of services between hospitals less than a mile apart. As to what often happens in medicine, early adopters of new technologies are professionals who create model programs that are successful and then stimulate the creation of infrastructure (ie, reimbursement, telecommunications, information technologies, and so on) that forms the platforms for entry of later, mainstream, adopters. The trend at medical schools, in the United States, is to go entirely digital for their pathology courses, discarding their student light microscopes, and building virtual slide laboratories. This may create a generation of pathology trainees who prefer digital pathology imaging over the traditional hands-on light microscopy. The creation of standards for virtual slide telepathology is early in its development but accelerating. The field of telepathology has now reached a tipping point at which major corporations now investing in the technology will insist that standards be created for pathology digital imaging as a value added business proposition. A key to success in teleradiology, already a growth industry, has been the implementation of standards for digital radiology imaging. Telepathology is already the enabling technology for new, innovative laboratory services. Examples include STAT QA surgical pathology second opinions at a distance and a telehealth-enabled rapid breast care service. The innovative bundling of telemammography, telepathology, and teleoncology services may represent a new paradigm in breast care that helps address the serious issue of fragmentation of breast cancer care in the United States and elsewhere. Legal and regulatory issues in telepathology are being addressed and are regarded as a potential catalyst for the next wave of telepathology advances, applications, and implementations.
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“Management platforms enable efficient storage, retrieval, and integration of WSIs with pathology reports and facilitate teledermatopathology [42].”
From Artificial Intelligence in Dermatopathology: An Update and Review of the Current Literature (2026) · cites this paper as [42]
Citations
Cites
Krupinski, E. A., Tillack, A. A., Richter, L. C., Henderson, J. T., Bhattacharyya, A. K., Scott, K., Graham, A. R., Descour, M. R., Davis, J. R., & Weinstein, R. S. (2006) · Human Pathology · doi:10.1016/j.humpath.2006.08.024 · Cited by 283
Self-citationVirtual microscopy in pathology education
Dee, F. R. (2009) · Human Pathology · doi:10.1016/j.humpath.2009.04.010 · Cited by 211
Telepathology overview: From concept to implementation
Weinstein, R. S., Descour, M. R., Liang, C., Bhattacharyya, A. K., Graham, A. R., Davis, J. R., Scott, K., Richter, L. C., Krupinski, E. A., Szymus, J., et al. (2001) · Human Pathology · doi:10.1053/hupa.2001.29643 · Cited by 210
Self-citationWeinstein, R. S., Descour, M. R., Chen, L., Barker, G. P., Scott, K., Richter, L. C., Krupinski, E. A., Bhattacharyya, A. K., Davis, J. R., Graham, A. R., et al. (2004) · Human Pathology · doi:10.1016/j.humpath.2004.09.002 · Cited by 167
Self-citationTelepathology and the networking of pathology diagnostic services.
Rs, W., Bloom, K. J., & Ls, R. (1987) · PubMed · Cited by 162
Evans, A. J., Chetty, R., Clarke, B. A., Croul, S. E., Ghazarian, D., Kiehl, T., Perez‐Ordoñez, B., Ilaalagan, S., & Asa, S. L. (2009) · Human Pathology · doi:10.1016/j.humpath.2009.04.012 · Cited by 160
Weinstein, R. S. (1986) · Human Pathology · doi:10.1016/s0046-8177(86)80028-4 · Cited by 158
Self-citationHistory of Telemedicine: Evolution, Context, and Transformation
Ryu, S. (2010) · Healthcare Informatics Research · doi:10.4258/hir.2010.16.1.65 · Cited by 148
Telepathology: A ten-year progress report
Weinstein, R. S., Bhattacharyya, A. K., Graham, A. R., & Davis, J. R. (1997) · Human Pathology · doi:10.1016/s0046-8177(97)90270-7 · Cited by 147
Self-citationRemote frozen section service: A telepathology project in northern Norway
Nordrum, I. S., Engum, B., Rinde, E., Finnseth, A., Ericsson, H., Kearney, M., Stalsberg, H., & Eide, T. J. (1991) · Human Pathology · doi:10.1016/0046-8177(91)90226-f · Cited by 140
Research works printed but not linked: 2
- Krupinski, 1993, Progress in telepathology: system implementation and testing, Adv Pathol Lab Med, 6, 63
- Weinstein, 1995, Pathology consultation service via the Arizona-International Telemedicine Network, Arch Anat Cytol Pathol, 43, 219
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Nunes, C. L., Rocha, R. M., Buzelin, M. A., Balabram, D., Foureaux, F. D. S., Porto, S., & Gobbi, H. (2014) · Pathology - Research and Practice · doi:10.1016/j.prp.2014.06.031 · Cited by 9
Ayad, E., Soliman, A., Anis, S. E., Salem, A. B., Hu, P., & Dong, Y. (2018) · Diagnostic Pathology · doi:10.1186/s13000-018-0735-7 · Cited by 9
Telemedicine and Telehealth: The Current Update
Suresh, D., Chaudhari, S., Saxena, A., & Gupta, P. K. (2021) · Health information science · doi:10.1007/978-3-030-68723-6_4 · Cited by 9
Veterinary and Human Biobanking Practices
Hostetter, G. H., Collins, E., Varlan, P., Edewaard, E., Harbach, P. R., Hudson, E. A., Feenstra, K., Turner, L. M., Berghuis, B. D., Resau, J. H., et al. (2013) · Veterinary Pathology · doi:10.1177/0300985813510532 · Cited by 9
An Assessment of Pathology Resident Access to and Use of Technology: A Nationwide Survey
Vallangeon, B. D., Hawley, J. S., Sloane, R., & Bean, S. M. (2017) · Archives of Pathology & Laboratory Medicine · doi:10.5858/arpa.2016-0228-oa · Cited by 9
VIRMISCO – The Virtual Microscope Slide Collection
Decker, P., Christian, A., & Xylander, W. E. R. (2018) · ZooKeys · doi:10.3897/zookeys.741.22284 · Cited by 9
Research progress in digital pathology: A bibliometric and visual analysis based on Web of Science
Zhao, J., Han, Z., Ma, Y., Liu, H., & Yang, T. (2022) · Pathology - Research and Practice · doi:10.1016/j.prp.2022.154171 · Cited by 8
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Kim, J., Song, Y., Park, J., & Lee, J.-R. (2011) · Korean Journal of Family Medicine · doi:10.4082/kjfm.2011.32.6.341 · Cited by 8
Gomez-Gelvez, J. C., Kryvenko, O. N., Chabot‐Richards, D., Foucar, K. K., Inamdar, K. V., & Karner, K. H. (2015) · American Journal of Clinical Pathology · doi:10.1309/ajcp25almxqfjcqa · Cited by 8
Şenel, E., & Baş, Y. (2020) · Turkish Journal of Pathology · doi:10.5146/tjpath.2019.01484 · Cited by 8
Mapping Telemedicine Efforts: Surveying Regional Initiatives in Denmark
Kierkegaard, P. (2015) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2014.0123 · Cited by 10
Perceptual Factors in Reading Medical Images
Krupinski, E. A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781108163781.008 · Cited by 8
Self-citationRahman, M. J., Rahman, M. M., Matsuyama, R., Tsunematsu, M., Islam, R., Ahmed, A., Banu, B., Hossain, S. M., Sarker, M. H. R., Monjur, F., et al. (2022) · Journal of Family Medicine and Primary Care · doi:10.4103/jfmpc.jfmpc_1876_21 · Cited by 7
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Momenzadeh, M., Vard, A., Talebi, A., Mehridehnavi, A., & Rabbani, H. (2017) · Microscopy Research and Technique · doi:10.1002/jemt.22951 · Cited by 7
Weinstein, R. S. (2018) · Human Pathology · doi:10.1016/j.humpath.2018.08.035 · Cited by 7
Self-citationKldiashvili, E., & Schräder, T. (2010) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2010.0079 · Cited by 7
Telemedicine, Telehealth, and e-Health Technologies in Cancer Prevention
López, A. M. (2013) · Springer eBooks · doi:10.1007/978-3-642-38983-2_9 · Cited by 7
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Khan, U., Härkönen, J., Friman, M., Hakimnejad, H., Latonen, L., Kuopio, T., & Ruusuvuori, P. (2026) · Scientific Reports · doi:10.1038/s41598-026-40943-3 · Cited by 15
Design and Validation of a Low-Cost Telepathology System
Álvarez, B. F. M., Avendaño, O. F. R., Gil-Guillén, V. F., & Carratalá‐Munuera, C. (2017) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2017.0030 · Cited by 6
Nelson, D., Ziv, A., & Bandali, K. S. (2013) · Postgraduate Medical Journal · doi:10.1136/postgradmedj-2012-200665rep · Cited by 6
Dennis, E., Banks, P., Murata, L. B., Sanchez, S. A., Pennington, C., Hockersmith, L., Miller, R. M., Lambe, J., Feng, J. D., Kapadia, M. J., et al. (2016) · Human Pathology · doi:10.1016/j.humpath.2016.06.013 · Cited by 6
Alawashiz, R., & AlDossary, S. A. (2023) · Digital Health · doi:10.1177/20552076231163672 · Cited by 6
Chen, J., Yang, J., Wang, J., Zhao, Z., Wang, M., Sun, C., Song, N., & Feng, S. (2024) · Sensors · doi:10.3390/s24123803 · Cited by 5
Takeyama, S., Watanabe, T., Gong, N., Yamaguchi, M., Urata, T., Kimura, F., & Ishii, K. (2024) · Journal of medical imaging · doi:10.1117/1.jmi.12.1.017501 · Cited by 5
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Bertheau, P., Chabouis, A., Fabiani, B., Poullier, É., Daniel, C., Cucherousset, J., Bosq, J., Hénin, D., Capron, F., & Guettier, C. (2012) · médecine/sciences · doi:10.1051/medsci/20122811018 · Cited by 5
Totu, T., Buga, R. M., Dumitru, A. V., Costache, M., Sladoje, N., & Stanciu, S. G. (2018) · IEEE Access · doi:10.1109/access.2018.2868127 · Cited by 5
TC-CycleGAN: Improved CycleGAN with Texture Constraints for Virtual Staining of Pathological Images
Huang, S., Wang, H., Hao, Y., Guo, S., Wang, Y., & Wang, T. (2023) · International Conference on Bioinformatics and Intelligent Computing (BIC) · doi:10.1145/3592686.3592713 · Cited by 5
Faghani, S., Codipilly, D. C., Moassefi, M., Iyer, P. G., & Erickson, B. J. (2023) · Mayo Clinic Proceedings Digital Health · doi:10.1016/j.mcpdig.2023.06.010 · Cited by 5
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Nofech‐Mozes, S., & Jorden, T. (2014) · Diagnostic histopathology · doi:10.1016/j.mpdhp.2014.11.001 · Cited by 5
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Nap, M., Teunissen, R., & Pieters, M. (2012) · Apmis · doi:10.1111/j.1600-0463.2011.02870.x · Cited by 5
Braunhut, B. L., Graham, A. R., Lian, F., Webster, P., Krupinski, E. A., Bhattacharyya, A. K., & Weinstein, R. S. (2014) · Journal of Pathology Informatics · doi:10.4103/2153-3539.133142 · Cited by 5
Self-citationHon, J. D., Chen, W., Minerowicz, C., Thomas, S. V., Barnard, N., Gilbert, N., & Fyfe, B. S. (2018) · American Journal of Clinical Pathology · doi:10.1093/ajcp/aqy117 · Cited by 5
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Chandra, M. (2014) · Indian Journal of Dermatopathology and Diagnostic Dermatology · doi:10.4103/2349-6029.135190 · Cited by 5
Innovative Methods of Archiving, Presentation and Providing Access to Histological Sections
FILIPIAK, K., Malińska, A., Krupa, D., & Zabel, M. (2011) · Postepy Biologii Komorki · doi:10.2478/v10052-011-0003-4 · Cited by 5
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Krupinski, E. A., Bhattacharyya, A. K., & Weinstein, R. S. (2015) · Springer eBooks · doi:10.1007/978-3-319-20379-9_5 · Cited by 5
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Alheejawi, S., Berendt, R. C., Jha, N., & Mandal, M. K. (2020) · Signal & Image Processing An International Journal · doi:10.5121/sipij.2020.11401 · Cited by 5
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Lézoray, O., Gürcan, M. N., Can, A., & Olivo‐Marín, J. (2011) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2011.06.008 · Cited by 5
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Abdelgawadbirry, R. (2013) · University of Salford Institutional Repository (University of Salford) · Cited by 5
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Carbone, F., Fochi, N. P., Perna, G. D., Wagner, A., Schlegel, J., Ranieri, E., Spetzger, U., Armocida, D., Cofano, F., Garbossa, D., et al. (2025) · Diagnostics · doi:10.3390/diagnostics15040499 · Cited by 4
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Bello, I. A., & Prasad, R. (2014) · Cited by 4
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Zhang, J., Xu, T., Li, X., Zhang, Y., Chen, Y., Wang, X., Wang, S., & Wang, C. (2020) · IEEE photonics journal · doi:10.1109/jphot.2020.2977888 · Cited by 4
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Parwani, A. V. (2020) · Elsevier eBooks · doi:10.1016/b978-0-323-67538-3.00006-3 · Cited by 4
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Mohanty, S. K., & Parwani, A. V. (2021) · Springer eBooks · doi:10.1007/978-3-030-83332-9_3 · Cited by 5
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Kobayashi, N., Suzuki, H., Ishikawa, M., Obi, T., Ichimura, T., Yanagisawa, H., Tsuchida, T., & Sasaki, A. (2020) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc44109.2020.9175398 · Cited by 4
Application of virtual microscopy in consultation practice of gastrointestinal and liver pathology
Jakate, S. M. (2010) · Journal of Pathology Informatics · doi:10.4103/2153-3539.68333 · Cited by 4
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Lele, S. M. (2010) · Journal of Pathology Informatics · doi:10.4103/2153-3539.68334 · Cited by 4
Virtual slides in peer reviewed, open access medical publication
Kayser, K., Borkenfeld, S., Goldmann, T., & Kayser, G. (2011) · Diagnostic Pathology · doi:10.1186/1746-1596-6-124 · Cited by 4
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Samak, A., Wiliem, A., Hobson, P., Walsh, M. D., Ditchmen, T., Troskie, A., Barksdale, S. K., Edwards, R., Jennings, A., & Lovell, B. C. (2015) · International Conference on Digital Image Computing: Techniques and Applications (DICTA) · doi:10.1109/dicta.2015.7371230 · Cited by 4
A collaborative central reviewing platform for cancer detection in digital microscopy images
Karatzanis, I., Iliopoulos, A., Tsiknakis, M., Sakkalis, V., & Kostas Marias, A. (2014) · International Advanced Research Workshop on In Silico Oncology and Cancer Investigation (IARWISOCI) · doi:10.1109/iarwisoci.2014.7034639 · Cited by 4
Hsu, D. C., & Lee, S. (2012) · doi:10.1002/9781444398595.ch55 · Cited by 4
Ohnishi, C., Ohnishi, T., Ibrahim, K., Ntiamoah, P., Ross, D. S., Yamaguchi, M., & Yagi, Y. (2023) · Microscopy and Microanalysis · doi:10.1093/micmic/ozad136 · Cited by 3
Self-citationShi, J., Ye, M., Sun, D., He, X., Lu, Y., Wang, L., Chen, H., Wang, W., Zhao, J., & Cui, F. (2026) · Journal of Medical Internet Research · doi:10.2196/75172 · Cited by 3
Huynh, C. D. (2026) · Intelligence-Based Medicine · doi:10.1016/j.ibmed.2026.100386 · Cited by 4
Kaabi, H. H., Alsoghier, A. M., Alredah, I. A., Alqahtani, M. S., Alsanie, I., & Balto, H. A. G. (2025) · Acta Odontologica Scandinavica · doi:10.2340/aos.v84.43564 · Cited by 3
Sawai, T., Miwa, U., Miura, Y., Kamataki, A., Matsumura, T., Saito, K., Kurose, A., Osamura, Y. R., Yoshimi, N., Kanno, H., et al. (2013) · Journal of Pathology Informatics · doi:10.4103/2153-3539.119002 · Cited by 3
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Bowa, K., & Anderson, P. G. (2014) · Academic Medicine · doi:10.1097/acm.0000000000000332 · Cited by 3
Color processing in pathology image analysis system for liver biopsy
Murakami, Y., Abe, T., Yamashita, Y., Yamaguchi, M., Ishikawa, M., Hashiguchi, A., Kiyuna, T., Saito, A., & Sakamoto, M. (2014) · Color and Imaging Conference · doi:10.2352/cic.2014.22.1.art00032 · Cited by 3
Kawano, Y., Namiki, K., Miyawaki, A., & Ishikawa, T. (2017) · PLoS ONE · doi:10.1371/journal.pone.0167774 · Cited by 3
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Yamaguchi, M. (2017) · Springer eBooks · doi:10.1007/978-981-10-2945-5_4 · Cited by 3
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Hay, R. J., & Asiedu, K. B. (2019) · MDPI eBooks · doi:10.3390/books978-3-03921-254-5 · Cited by 3
TelePi: an affordable telepathology microscope camera system anyone can build and use
Youssef, A., Rosenwald, A., & Rosenfeldt, M. T. (2023) · Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin · doi:10.1007/s00428-023-03685-5 · Cited by 3
Puri, M., Lloyd, M. C., & Bui, M. M. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-801559-9.00019-3 · Cited by 3
Weinstein, R. S., Holcomb, M. J., Krupinski, E. A., & Latifi, R. (2020) · Springer eBooks · doi:10.1007/978-3-030-56917-4_1 · Cited by 3
Self-citationWeinstein, R. S., Lian, F., & Bhattacharyya, A. K. (2015) · Springer eBooks · doi:10.1007/978-1-4939-2349-6_11 · Cited by 3
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Fan, Y., Gal, Y., & Bradley, A. P. (2013) · International Conference on Digital Image Computing: Techniques and Applications (DICTA) · doi:10.1109/dicta.2013.6691511 · Cited by 3
Belhomme, P., Oger, M., Michels, J.-J., & Plancoulaine, B. (2013) · Diagnostic Pathology · doi:10.1186/1746-1596-8-s1-s9 · Cited by 3
Lega, S., Crucitti, P., Pierotti, P., Rapezzi, R., de Bianchi, P. S., Naldoni, C., & Bondi, A. (2013) · Diagnostic Pathology · doi:10.1186/1746-1596-8-s1-s18 · Cited by 3
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Meyer, J. M., & Paré, G. (2017) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2017.429 · Cited by 3
Registration accuracy between whole slide images and glass slides in eeDAP workflow
Gong, Q., Berman, B. P., Gavrielides, M. A., & Gallas, B. D. (2018) · SPIE Medical Imaging: Digital and Computational Pathology · doi:10.1117/12.2293189 · Cited by 3
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Alvarez‐Jimenez, C., Corredor, G., Giraldo, D. L., & Romero, E. (2019) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2019.8759227 · Cited by 3
Şensu, S. (2020) · Journal of Medical Science And clinical Research · doi:10.18535/jmscr/v8i11.93 · Cited by 3
Eccher, A., Girolami, I., Troncone, G., & Pantanowitz, L. (2021) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2021.684034 · Cited by 3
Clinical Laboratory Informatics
Baron, J. M., & Dighe, A. S. (2010) · Encyclopedia of Analytical Chemistry · doi:10.1002/9780470027318.a9114 · Cited by 3
Rapid Whole Slide Imaging via Learning-based Two-shot Virtual AutofocusingPreprint
Li, Q., Liu, X., Han, K., Guo, C., Ji, X., & Wu, X. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2003.06630 · Cited by 3
Allan, E. L., Price, B. W., Shchedrina, O., Dupont, S. T. K., Livermore, L., & Smith, V. (2018) · doi:10.31219/osf.io/dvmsh · Cited by 3
Kats, L., Gabet, Y., Shpunt, U., & Vered, M. (2025) · PLoS ONE · doi:10.1371/journal.pone.0335602 · Cited by 2
Micsík, T., Elmberger, G., Bergquist, A. M., & Fónyad, L. (2015) · AIMS Medical Science · doi:10.3934/medsci.2015.2.79 · Cited by 2
Sorani, M. D. (2012) · PLoS ONE · doi:10.1371/journal.pone.0030463 · Cited by 2
Huss, S., Fronhoffs, F., Büttner, R., & Heukamp, L. C. (2011) · Diagnostic Pathology · doi:10.1186/1746-1596-6-17 · Cited by 2
Braunhut, B. L., Graham, A. R., Richter, L., Webster, P., Krupinski, E. A., Bhattacharyya, A., & Weinstein, R. S. (2013) · Diagnostic Pathology · doi:10.1186/1746-1596-8-s1-s3 · Cited by 2
Self-citationIdentifying regions of interest in whole slide images of renal cell carcinoma
Benomar, M. L., Settouti, N., Debreuve, É., Descombes, X., & Ambrosetti, D. (2021) · Research on Biomedical Engineering · doi:10.1007/s42600-021-00178-9 · Cited by 2
CGS-Net:Classification-guided Segmentation Network for Improved Gland Segmentation
Tang, X., Peng, Y., Ma, Y., Chen, J., Li, S., & He, X. (2023) · IEEE Data Driven Control and Learning Systems Conference (DDCLS) · doi:10.1109/ddcls58216.2023.10166683 · Cited by 2
Lucà, S., Monti, R., Corte, C. M. D., Cantisani, A., Cozzolino, I., Clery, E., Amato, M., Marone, L., Capasso, F., Guida, G. D., et al. (2025) · Cancers · doi:10.3390/cancers17111738 · Cited by 2
Graph Convolutional Neural Networks to Classify Whole Slide Images
Konda, R., Wu, H., & Wang, M. D. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9054598 · Cited by 2
How to Prepare Neuroanatomical Image Data
O’Connor, N., Tappan, S. J., & Glaser, J. R. (2014) · Current Protocols in Neuroscience · doi:10.1002/0471142301.ns0121s69 · Cited by 2
Whole Slide Imaging In Medical and Dental Education
Kumar, N., & Chandra, M. (2013) · Cited by 2
Silverstein, L. D., Hashmi, S. F., Lang, K., Krupinski, E. A., Dallas, W. J., & Roehrig, H. (2011) · SID Symposium Digest of Technical Papers · doi:10.1889/1.3620995 · Cited by 2
Self-citationDiagnostic reproducibility on whole digital slide in cytology and histology in oncologic screenings
Lega, S., Crucitti, P., Pierotti, P., Rapezzi, R., de Bianchi, P. S., Naldoni, C., & Bondi, A. (2013) · Diagnostic Pathology · doi:10.1186/1746-1596-8-s1-s12 · Cited by 2
Tele-Cardiology in Remote O&G Premises
Panait, D., & Mika, F. (2013) · SPE European HSE Conference and Exhibition · doi:10.2118/164984-ms · Cited by 2
eeDAP: An evaluation environment for digital and analog pathology
Gallas, B. D., Cheng, W., Gavrielides, M. A., Ivansky, A., Keay, T. C., Wunderlich, A., Hipp, J., & Hewitt, S. M. (2014) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.2044443 · Cited by 2
Use of Telemedicine in Postgraduate Pathology Education
Kar, A., Kar, T., Biswal, P., Pattanaik, K., Bhuyan, P., Mallick, R., & Mohanty, B. N. (2013) · International Journal of Clinical Medicine · doi:10.4236/ijcm.2013.46053 · Cited by 2
Recent development and perspectives of virtual slides (VS) and telepathology in Europe
Kayser, K., Borkenfeld, S., & Kayser, G. (2013) · Diagnostic Pathology · doi:10.1186/1746-1596-8-s1-s2 · Cited by 2
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Metadata
- Authors
- Weinstein, R. S., Graham, A. R., Richter, L. C., Barker, G. P., Krupinski, E. A., Lopez, A. M., Erps, K. A., Bhattacharyya, A. K., Yagi, Y., & Gilbertson, J. R.
- Affiliations
- University of Arizona (US)
- Harvard University (US)
- Corresponding author
- Weinstein, Ronald S.
- ORCID
- Venue
- Human Pathology
- Publisher
- Elsevier BV
- Published
- 2009-08
- Volume
- 40
- Issue
- 8
- Pages
- 1057-1069
- ISSN
- 0046-8177 (ISSN-L)
- OpenAlex
- W2126047962
- Cited by
- 380
- References
- 52
- Citations by year
- 2026: 11 · 2025: 8 · 2024: 7 · 2023: 15 · 2022: 18 · 2021: 26 · 2020: 24 · 2019: 14 · 2018: 25 · 2017: 19 · 2016: 18 · 2015: 24 · 2014: 37 · 2013: 34 · 2012: 39
- FWCI
- 32.61
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Human Pathology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiology practices and education
- Keywords
- telepathology, virtual microscopy, whole slide imaging, digital pathology, telemammography, teleoncology, telemedicine, pathology education, legal and regulatory issues
- MeSH terms
- Computer Communication Networks, Humans, Image Processing, Computer-Assisted, Microscopy, Pathology, Surgical, User-Computer Interface, Telepathology
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