Localtab |
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active | true |
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title | Data Access |
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| Data AccessClick 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 | License |
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Structured Reports (SR) and Segmentations (DICOM) | Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/44499647/LIDC-IDRI-StandardizedRepresentation-March2020-manifest.tcia?api=v2 |
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(Download requires the NBIA Data Retriever) | | DSO Key (csv) | |
Please contact help@cancerimagingarchive.net with any questions regarding usage. |
Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/44499647/TCGA_DSO_Key.csv?api=v2 |
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Additional Resources for this DatasetThe following external resources have been made available by the data submitters. These are not hosted or supported by TCIA, but may be useful to researchers utilizing this collection. Collections Used in this Third Party AnalysisBelow is a list of the Collections used in these analyses: |
Localtab |
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title | Detailed Description |
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| Detailed DescriptionImage Image Statistics |
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Modalities (DICOM) | SegSEG, SR | Number of Patients | 875 | Number of Studies | 883 | Number of Series | 13,71813,718 GB
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Localtab |
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title | Citations & Data Usage Policy |
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| Citations & Data Usage Policy 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: Tcia limited license policy |
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Info |
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| 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 |
Info |
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title | TCIA Publication Citation |
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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. (2020) DICOM re‐encoding of volumetrically annotated Lung Imaging Database Consortium (LIDC) nodules. Medical Physics Dataset Article. https://doi.org/10.1002/mp.14445 |
Info |
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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.J.W.L., Kikinis, R., Prior, F. 2018. Standardized representation of the LIDC annotations using DICOM. PeerJ Preprints 6:e27378v2 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, 26(6), 1045–1057. https://doi.org/10.7287/peerj.preprints.273781007/s10278-013-9622-7 |
Additional Publication Resources:The Collection authors suggest the below will give context to this dataset: Info |
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| title | Publication Citation |
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| 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, The - 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: https://doi.org/10.1118/1.3528204
info | Samuel Geoffrey Luc Michael Charles , Anthony P., … Clarke, Laurence http- , A. P., Zhao, B., Aberle, D. R., Henschke, C. I., Hoffman, E. A., Kazerooni, E. A., MacMahon, H., Van Beek, E. J. R., Yankelevitz, D., Biancardi, A. M., Bland, P. H., Brown, M. S., Engelmann, R. M., Laderach, G. E., Max, D., Pais, R. C. , Qing, D. P. Y. , Roberts, R. Y., Smith, A. R., Starkey, A., Batra, P., Caligiuri, P., Farooqi, A., Gladish, G. W., Jude, C. M., Munden, R. F., Petkovska, I., Quint, L. E., Schwartz, L. H., Sundaram, B., Dodd, L. E., Fenimore, C., Gur, D., Petrick, N., Freymann, J., Kirby, J., Hughes, B., Casteele, A. V., Gupte, S., Sallam, M., Heath, M. D., Kuhn, M. H., Dharaiya, E., Burns, R., Fryd, D. S., Salganicoff, M., Anand, V., Shreter, U., Vastagh, S., Croft, B. Y., Clarke, L. P. (2015). Data From LIDC-IDRI [Data set]. The Cancer Imaging Archive.
Other Publications Using This DataTCIA maintainsmaintains a list of publications that which leverage TCIA our data. If you have a manuscript you'd like to add please contact the TCIA's Helpdesk.
Localtab |
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| Version 3 (Current): 2020/03/26
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 Version 2: 2019/05/14
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. Version 1: 2018/11/30
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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