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  • Segmentation of Pulmonary Nodules in Computed Tomography Using a Regression Neural Network Approach and its Application to the Lung Image Database Consortium and Image Database Resource Initiative Dataset

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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

Images containing the 66 testing nodules that are delineated by all four board certified radiologists (DICOM) 

Images containing the 77 LIDC testing nodules that are segmented by three or more radiologists (DICOM)

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


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:

Info
titleData Citation

Temesguen Messay, Russell C Hardie, and Timothy R Tuinstra. (2014). Segmentation of Pulmonary Nodules in Computed Tomography Using a Regression Neural Network Approach and its Application to the Lung Image Database Consortium and Image Database Resource Initiative Dataset. The Cancer Imaging Archive. http://doi.org/10.7937/K9/TCIA.2014.V7CVH1JO


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. (paper)

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

Messay, T., Hardie, R. C., & Tuinstra, T. R. (2015, May). Segmentation of pulmonary nodules in computed tomography using a regression neural network approach and its application to the Lung Image Database Consortium and Image Database Resource Initiative dataset. Medical Image Analysis. Elsevier BV. http://doi.org/10.1016/j.media.2015.02.002

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.


Supplemental Data
Localtab
titleVersions

Version 1 (Current):

2016

2015/

08

02/

02

24


Data TypeDownload all or Query/Filter
Image Data

Images containing the 66 testing nodules that are delineated by all four board certified radiologists (DICOM) 

Images containing the 77 LIDC testing nodules that are segmented by three or more radiologists (DICOM)