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Comment: updated preprint citation with finished citation

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Localtab Group



Localtab
activetrue
titleData Access

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 TypeDownload all or Query/Filter
Structured Reports (SR) and Segmentations (DICOM)


Please contact help@cancerimagingarchive.net  with any questions regarding usage.




Localtab
titleDetailed Description

Detailed Description


Image Statistics


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






Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy 

Public collection license

Info
titleData Citation

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
titlePublication Citation

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
titleTCIA Citation

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
titlePreprint Citation

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


In addition to the dataset citation above, please be sure to cite the following if you utilize these data in your research:


Info
titlePublication Citation

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
titleData Citation

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


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.




Localtab
titleVersions

Version 3 (Current): 2020/03/26


Data TypeDownload all or Query/Filter
Structured Reports (SR) and Segmentations (DICOM)


What changed:

DICOM objects curated and added to the cancerimagingarchive.net

Version 2: 2019/05/14


Data TypeDownload all or Query/Filter
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 TypeDownload all or Query/Filter
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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