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  • Long and Short Survival in Adenocarcinoma Lung CTs (LUAD-CT-Survival)

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Localtab Group



Localtab
activetrue
titleData Access

Data Access

Click the Download  button to save the data.

Data TypeDownload all or Query/FilterLicense
Tumor Segmentations (NIfTI, ZIP, 834 KB)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/24284406/segmentations.zip?api=v2



Tcia cc by 3

Image Features and Patient Survival (CSV, 107 KB)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/24284406/FeaturesWithLabels%20%281%29.csv?api=v2



Tcia cc by 3


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


Collections Used in this Third Party Analysis

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

Data TypeDownload all or Query/Filter
Original Source Images (DICOM, 1.54 GB)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/24284406/LongShortSurvivalAdenocarcinoma-doiJNLP-qOFdxYUi.tcia?api=v2


(Download requires the NBIA Data Retriever)





Localtab
titleDetailed Description

Detailed Description

Image data is available in DICOM format. Segmentation data is available in .nii format. Labels are available in .csv format. The first column is subject identification. The second column is survival class.  Subsequent columns are computed image features which are described in the following publications.




Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy 

Tcia limited license policy

Info
titleData Citation

Goldgof D., Hall L., Hawkins S.H., Schabath M.B., Stringfield O., Garcia A., Balagurunathan Y., Kim J., Eschrich S., Berglund A.E., Gatenby R., Gillies R.J. (2017) Long and Short Survival in Adenocarcinoma Lung CTs. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2017.0tv7b9x1


Info
titlePublication Citation

Paul, R., Hawkins, S., Balagurunathan, Y., Schabath, M., Gillies, R., Hall, L., & Goldgof, D. (2016). Deep Feature Transfer Learning in Combination with Traditional Features Predicts Survival among Patients with Lung Adenocarcinoma. Tomography, 2(4), 388–395. https://doi.org/10.18383/j.tom.2016.00211


Info
titlePublication Citation

Hawkins, S. H., Korecki, J. N., Balagurunathan, Y., Yuhua Gu, Kumar, V., Basu, S., Hall, L. O., Goldgof, D. B., Gatenby, R. A., & Gillies, R. J. (2014). Predicting Outcomes of Nonsmall Cell Lung Cancer Using CT Image Features. IEEE Access, 2, 1418–1426. https://doi.org/10.1109/access.2014.2373335


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. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057. https://doi.org/10.1007/s10278-013-9622-7

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 1 (Current): 2017/08/11

Data TypeDownload all or Query/Filter
Images (DICOM)

Tumor Segmentations (NIFTI)

Image Features and Patient Survival (CSV)




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