Data Access
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 |
Structured Reports (SR) and Segmentations (DICOM) |
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Please contact help@cancerimagingarchive.net with any questions regarding usage.
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Detailed Description
Image Statistics
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Modalities (DICOM)
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Seg, SR
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Number of Patients
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875
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Number of Studies
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883
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Number of Series
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13,718
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Number of Images
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13,718
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Images Size (GB) |
2 GB |
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Citations & Data Usage Policy
Fedorov, A., Hancock, M., Clunie, D., Brockhhausen, M., Bona, J., Kirby, J., Freymann, J., Aerts, H.J.W.L., Kikinis, R., Prior, F. (2018). Standardized representation of the TCIA LIDC-IDRI annotations using DICOM. 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
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Fedorov, A., Hancock, M., Clunie, D., Brochhausen, M., Bona, J., Kirby, J.,
Freymann, J, Pieper S, Aerts H.J.W.L., Kikinis, R., Prior, F. 2018. Standardized
representation of the LIDC annotations using DICOM. PeerJ Preprints
6:e27378v2
https://doi.org/10.7287/peerj.preprints.27378
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In addition to the dataset citation above, please be sure to cite the following if you utilize these data in your research:
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
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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
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Other Publications Using This Data
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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Version 3 (Current): 2020/03/26
Data Type |
Download all or Query/Filter |
Structured Reports (SR) and Segmentations (DICOM) |
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What changed:
DICOM objects curated and added to the cancerimagingarchive.net
Version 2: 2019/05/14
Data Type |
Download all or Query/Filter |
Structured Reports (SR) and Segmentations (DICOM) |
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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.
Version 1: 2018/11/30
Data Type |
Download all or Query/Filter |
Structured Reports (SR) and Segmentations (DICOM) |
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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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