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| active | true |
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| title | Data Access |
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| Click the Download button to save a ".tcia" manifest file to your computer, which you must open with the NBIA Data Retriever. | Data Type | Download all or Query/Filter |
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| Structured Reports (SR) and Segmentations (DICOM) | |
Please contact help@cancerimagingarchive.net with any questions regarding usage. |
| Localtab |
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| title | Detailed Description |
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| Image Statistics |
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Modalities (DICOM) | Seg, SR | Number of Patients | 875 | Number of Studies | 883 | Number of Series | 13,718 | Number of Images | 13,718 | | Images Size (GB) | 2 GB |
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| Localtab |
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| title | Citations & Data Usage Policy |
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| These collections are freely available to browse, download, and use for commercial, scientific and educational purposes as outlined in the Creative Commons Attribution 3.0 Unported License. Questions may be directed to help@cancerimagingarchive.net. Please be sure to acknowledge both this data set and TCIA in publications by including the following citations in your work: | Info |
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| Andrey Fedorov A, Matthew Hancock M, David Clunie D, Mathias Brockhausen M, Jonathan Bona J, Justin Kirby J, John Freymann J, Hugo Aerts H, Ron Kikinis R, Fred Prior F. Standardized representation of the TCIA LIDC-IDRI annotations using DICOM. (2018) The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.2018.h7umfurq |
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| Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F. (2013) The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6 pp 1045-1057. DOI: 10.1007/s10278-013-9622-7 |
| Info |
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| Fedorov A, Hancock M, Clunie D, Brochhausen M, Bona J, Kirby J, Freymann J, Pieper S, Aerts H, Kikinis R, Prior F. 2018. Standardized representation of the LIDC annotations using DICOM. PeerJ Preprints 6:e27378v1 e27378v2 https://doi.org/10.7287/peerj.preprints.27378 |
In addition to the dataset citation above, please be sure to cite the following if you utilize these data in your research: | Info |
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| title | Publication Citation |
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| Armato SG III, McLennan G, Bidaut L, McNitt-Gray MF, Meyer CR, Reeves AP, Zhao B, Aberle DR, Henschke CI, Hoffman EA, Kazerooni EA, MacMahon H, van Beek EJR, Yankelevitz D, et al.: The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A completed reference database of lung nodules on CT scans. Medical Physics, 38: 915--931, 2011. DOI: 10.1118/1.3528204 |
| Info |
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| Armato III, Samuel G., McLennan, Geoffrey, Bidaut, Luc, McNitt-Gray, Michael F., Meyer, Charles R., Reeves, Anthony P., … Clarke, Laurence P. (2015). Data From LIDC-IDRI. The Cancer Imaging Archive. http://doi.org/10.7937/K9/TCIA.2015.LO9QL9SX |
TCIA maintains a list of publications that leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk. |
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| | Data Type | Download all or Query/Filter |
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| Structured Reports (SR) and Segmentations (DICOM) | |
What changed: DICOM objects curated and added to the cancerimagingarchive.net | Data Type | Download all or Query/Filter |
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| Structured Reports (SR) and Segmentations (DICOM) | |
What changed: DICOM SEG objects no longer encode empty slices to reduce object size. The coded terms used to describe the nodule annotations now use fewer non-standard (99QIICR) codes. SegmentLabel attribute is populated in the DICOM SEG objects to list nodule annotation name instead of "Nodule", to help with readability
for the user. | Data Type | Download all or Query/Filter |
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| Structured Reports (SR) and Segmentations (DICOM) | |
Note: Version 1 of this dataset is currently located in a shared Google Drive folder while undergoing verification. When testing is complete the Google Drive folder will be replaced by a different link to the final dataset. If you identify any issues with the data please report them to the TCIA Helpdesk.
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