The DOI matches its Crossref record; 13 of the 15 references it cites were found in a registry or an index.
The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository
Open accessAbstract
The National Institutes of Health have placed significant emphasis on sharing of research data to support secondary research. Investigators have been encouraged to publish their clinical and imaging data as part of fulfilling their grant obligations. Realizing it was not sufficient to merely ask investigators to publish their collection of imaging and clinical data, the National Cancer Institute (NCI) created the open source National Biomedical Image Archive software package as a mechanism for centralized hosting of cancer related imaging. NCI has contracted with Washington University in Saint Louis to create The Cancer Imaging Archive (TCIA)-an open-source, open-access information resource to support research, development, and educational initiatives utilizing advanced medical imaging of cancer. In its first year of operation, TCIA accumulated 23 collections (3.3 million images). Operating and maintaining a high-availability image archive is a complex challenge involving varied archive-specific resources and driven by the needs of both image submitters and image consumers. Quality archives of any type (traditional library, PubMed, refereed journals) require management and customer service. This paper describes the management tasks and user support model for TCIA.
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“we used the recent adrenocortical carcinoma CT dataset34,42,43, where the segmentation target, adrenal tumor, was neither part of the training nor of the existing validation sets.”
From Segment anything in medical images (2024) · cites this paper as [34]
Experimental — accuracy not yet measuredIn the citing paper
“They are beginning to be solved through sharing of oncology metadata (www.oriencancer.org or the Children’s Oncology Group), and some sharing of image files has been enabled by The Cancer Imaging Archive (77).”
From Radiomics: Images Are More than Pictures, They Are Data (2016) · cites this paper as [77]
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The Human Connectome Project: A data acquisition perspective
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Self-citationHowe, D. G., Costanzo, M. C., Fey, P., Gojobori, T., Hannick, L. I., Hide, W., Hill, D. P., Kania, R., Schaeffer, M. L., Pierre, S. S., et al. (2008) · Nature · doi:10.1038/455047a · Cited by 701
Informatics and Data Mining Tools and Strategies for the Human Connectome Project
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Quantitative Imaging for Evaluation of Response to Cancer Therapy
Clarke, L. P., Croft, B. S., Nordstrom, R. J., Zhang, H., Kelloff, G. J., & Tatum, J. L. (2009) · Translational Oncology · doi:10.1593/tlo.09217 · Cited by 46
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Radiomics: Images Are More than Pictures, They Are Data
Gillies, R. J., Kinahan, P. E., & Hricak, H. (2016) · Radiology · doi:10.1148/radiol.2015151169 · Cited by 8,421
Convolutional neural networks: an overview and application in radiology
Yamashita, R., Nishio, M., Do, R. K. G., & Togashi, K. (2018) · Insights into Imaging · doi:10.1007/s13244-018-0639-9 · Cited by 4,682
“Figure 12a shows a representative example of segmentation of the uterus with a malignant tumor on MRI [24, 44, 45].”
BackgroundZwanenburg, A., Vallières, M., Abdalah, M. A., Aerts, H. J. W. L., Andrearczyk, V., Apte, A., Ashrafinia, S., Bakas, S., Beukinga, R. J., Boellaard, R., et al. (2020) · Radiology · doi:10.1148/radiol.2020191145 · Cited by 4,177
Artificial intelligence in radiology
Hosny, A., Parmar, C., Quackenbush, J., Schwartz, L. H., & Aerts, H. J. W. L. (2018) · Nature Reviews Cancer · doi:10.1038/s41568-018-0016-5 · Cited by 3,803
Review The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge
Tomczak, K. J., Czerwińska, P., & Wiznerowicz, M. (2015) · Współczesna Onkologia · doi:10.5114/wo.2014.47136 · Cited by 3,624
Metadata
- Authors
- Clark, K., Vendt, B., Smith, K., Freymann, J., Kirby, J., Koppel, P., Moore, S., Phillips, S., Maffitt, D., Pringle, M., Tarbox, L., & Prior, F.
- Affiliations
- Washington University in St. Louis (US)
- Frederick National Laboratory for Cancer Research (US)
- Corresponding author
- Clark, Kenneth
- Venue
- Journal of Digital Imaging
- Published
- 2013-07-25
- Volume
- 26
- Issue
- 6
- Pages
- 1045-1057
- ISSN
- 0897-1889 (ISSN-L)
- 1618-727X
- PMC
- PMC3824915
- OpenAlex
- W2083927153
- Cited by
- 4,599
- References
- 15
- Citations by year
- 2026: 337 · 2025: 584 · 2024: 685 · 2023: 667 · 2022: 623 · 2021: 542 · 2020: 418 · 2019: 320 · 2018: 204 · 2017: 112 · 2016: 68 · 2015: 27 · 2014: 7 · 2013: 1
- FWCI
- 101.32
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- other-oa
- www.springer.com/tdm (tdm)
- Locations
- Journal of Imaging Informatics in Medicine (publishedVersion, other-oa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- U.S. Department of Health and Human Services (HHSN261200800001E)
- Radiological Society of North America
- National Institutes of Health (Contract No. HHSN261200800001E., #HHSN261200800001E, HHSN261200800001C)
- National Cancer Institute (No. HHSN261200800001E, Contract No.,HHSN261200800001E, HHSN261200800001E))
- Topics
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Social Sciences › Sociology and Political Science › Data Analysis and Archiving
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Keywords
- The Cancer Imaging Archive, medical image repositories, tumor imaging, open source software, data sharing, secondary research, repository management, user support
- MeSH terms
- Diagnostic Imaging, Female, Humans, Male, Medical Informatics, Neoplasms, Quality Control, Radiology Information Systems, Software, United States, Program Evaluation, Information Storage and Retrieval, National Cancer Institute (U.S.), Multimodal Imaging
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