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Summary

This dataset (also known as the “moist run” among QIN sites) contains CT images (41 total scans) of non-small cell lung cancer from: the Reference Image Database to Evaluate Therapy Response (RIDER), the Lung Image Database Consortium (LIDC), patients from Stanford University Medical Center and the Moffitt Cancer Center, and the Columbia University/FDA Phantom. In addition, 3 academic institutions (Columbia, Stanford, Moffitt-USF) each ran their own segmentation algorithm on a total of 52 tumor volumes.  Segmentations were performed 3 different times with different initial conditions, resulting in 9 segmentations formatted as DICOM Segmentation Objects (DSOs) for each tumor volume, for a total of 468 segmentations. This collection may be useful for designing and comparing competing segmentation algorithms, for establishing acceptable ranges of variability in volume and segmentation borders, and for developing algorithms for creating cancer biomarkers from features computed from the segmented tumors and their environments.

Note: In December 2018 it was discovered that an update to NSCLC Radiogenomics mistakenly resulted in the deletion of the segmentation data from this analysis set.  As a result, the 10 affected patients and related segmentations are no longer included in the download section below.  


Localtab Group



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

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
CT Images - 31 series (DICOM)
Segmentations - 378 series (DICOM)
CT Images & Segmetations Combined - 409 series  (DICOM)
License
Segmentations (378 series, DICOM)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/20644453/QIN%20Multi-site%20Lung%20SEG%20Only%20%28minus%20Stanford%29.tcia?version=1&modificationDate=1545170222429&api=v2

Segmentations download

(Requires NBIA Data Retriever

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CT Images & Segmentations Combined  (409 series, DICOM)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/20644453/QIN%20Multi-site%20Lung%20CTs%20and%20SEG%20%28minus%20Stanford%29.tcia?api=v2

images and results

(Requires NBIA Data Retriever

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Lung Phantom Nodule Locations Documentation (xls)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/19038560/a_CU_12PhantomLocations.xls?version=1&modificationDate=1412707717723&api=v2



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QIN LUNG CT Nodule Locations Documentation (xls)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/19038560/a_moffitt%20remapping.xls?version=1&modificationDate=1412707717954&api=v2



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RIDER Lung CT Nodule Locations Documentation (xls)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/19038560/a_RIDER_locations_rev3.xls?version=1&modificationDate=1412707718311&api=v2



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LIDC-IDRI Nodule Locations Documentation (xls)


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urlhttps://wiki.cancerimagingarchive.net/download/attachments/19038560/a_lidcMoistFinal2%20remapping.xls?version=1&modificationDate=1412707717900&api=v2



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Collections Used in this Third Party Analysis

Below is a list of the Collections used in these analyses:

Source Data TypeDownloadLicense
Corresponding Original CT Images from Lung Phantom, LIDC-IDRI, QIN LUNG CT, and RIDER Lung CT - 31 series (DICOM)
Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/20644453/QIN%20Multi-site%20Lung%20CTs%20%28minus%20Stanford%29.tcia?version=1&modificationDate=1545170229923&api=v2

Source CT only download

(Requires NBIA Data Retriever

Tcia cc by 3





Localtab
titleDetailed Description

Detailed Description


To download all DICOM source CT Images & Segmentations Combined - 409 series  (DICOM) you can use this link : QIN Multi-site Lung CTs and SEG (minus Stanford).tcia(Download requires NBIA Data Retriever

Localtab
titleDetailed Description

Detailed Description

Current version spreadsheets:

Previous version spreadsheets:

For more information on versioning, please refer to the Versions tab.




Localtab
titleCitations & Data Usage Policy

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

Info
titleData Citation

Jayashree Kalpathy-Cramer, Sandy J., Napel, Dmitry Goldgof, Binsheng ZhaoS., Goldgof, D., & Zhao, B. (2015). Multi-site collection of Lung CT data with Nodule Segmentations (version 3) [Data set]. The Cancer Imaging Archive. DOI: https://doi.org/10.7937/K9k9/TCIAtcia.2015.1BUVFJR71buvfjr7 


Info
titleTCIA Publication 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: Kalpathy-Cramer, J., Zhao, B., Goldgof, D., Gu, Y., Wang, X., Yang, H., Tan, Y., Gillies, R., & Napel, S. (2016). A Comparison of Lung Nodule Segmentation Algorithms: Methods and Results from a Multi-institutional Study. In Journal of Digital Imaging (Vol. 29, Issue 4, pp. 476–487).  https://doi.org/10.1007/s10278-013016-9622-7

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

9859-z


Info
titlePublication TCIA Citation

Kalpathy-CramerClark, JK., ZhaoVendt, B., Smith, K., GoldgofFreymann, DJ., GuKirby, YJ., WangKoppel, XP., YangMoore, HS., … NapelPhillips, S. (2016, February 3). A Comparison of Lung Nodule Segmentation Algorithms: Methods and Results from a Multi-institutional Study. , Maffitt, D., Pringle, M., Tarbox, L., & Prior, F. (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. In Journal of Digital Imaging (Vol. Springer Nature. DOI: 26, Issue 6, pp. 1045–1057). Springer Science and Business Media LLC. https://doi.org/10.1007/s10278-016013-9859-z9622-7 PMCID: PMC3824915


Other Publications Using This Data

TCIA maintains a list of publications that leverage TCIA our data. If you have a manuscript you'd like to add please contact the TCIA's Helpdesk.




Image Removed

Version 1: 2015/09/15

On 9/14/2015 this DOI was updated to resolve problems with 9 of the segmentations being incorrectly labeled.  The Series Instance UIDs in the original data set which have since been deleted from TCIA are:

1.2.276.0.7230010.3.1.3.0.34323.1424694723.968333
1.2.276.0.7230010.3.1.3.0.34343.1424694769.748096
1.2.276.0.7230010.3.1.3.0.32279.1424660367.640148
1.2.276.0.7230010.3.1.3.0.3373.1415292738.832393
1.2.276.0.7230010.3.1.3.0.32259.1424660332.352116
1.2.276.0.7230010.3.1.3.0.32238.1424660298.604243
1.2.276.0.7230010.3.1.3.0.3306.1415292638.342990
1.2.276.0.7230010.3.1.3.0.3345.1415292685.22320
1.2.276.0.7230010.3.1.3.0.34303.1424694693.127541

These have been replaced with the following new segmentation series:

1.2.276.0.7230010.3.1.3.0.21757.1437749726.319319 
1.2.276.0.7230010.3.1.3.0.21734.1437749686.271681 
1.2.276.0.7230010.3.1.3.0.21713.1437749624.694944 
1.2.276.0.7230010.3.1.3.0.95052.1441388220.839236 
1.2.276.0.7230010.3.1.3.0.95027.1441388189.267094 
1.2.276.0.7230010.3.1.3.0.95003.1441388142.544126 
1.2.276.0.7230010.3.1.3.0.3233.1437599346.502866 

Previous version spreadsheets:

Version 1: 2015/09/15

Original release of dataset.

Localtab
titleVersions

Version 3 (Current): 2018/12/18


Data TypeDownload all or Query/Filter
CT Images - 31 series (DICOM)

Segmentations - 378 series (DICOM)

CT Images & Segmetations Segmentations Combined - 409 series  (DICOM)


Note: In December 2018 it was discovered that an update to NSCLC Radiogenomics mistakenly resulted in the deletion of the segmentation data for this analysis set.  We are currently investigating whether it is possible to restore the data.  In the meantime this dataset can be downloaded using the links above which exclude As a result, version 3 excludes the Stanford NSCLC Radiogenomics subset of the analyses.

Version 2: 2015/12/21

Data TypeDownload all or Query/Filter
CT Images - 31 series (DICOM)
Segmentations - 378 series (DICOM)
CT Images & Segmetations Combined - 409 series  (DICOM)