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The FDA anthropomorphic thorax phantom with 12 phantom lesions of different sizes (10 and 20 mm in effective diameter), shapes (spherical, elliptical, lobulated, and spiculated), and densities (−630,−10, and +100 HU) was scanned at Columbia University Medical Center on a 64-detector row scanner (LightSpeed VCT, GE Healthcare, Milwaukee, WI). The CT scanning parameters were 120 kVp, 100 mAs, 64x0.625 collimation, and pitch of 1.375. The images were reconstructed with the lung kernel using 1.25 mm slice thickness.

This data set was provided to TCIA for use in the National Cancer Institute's Quantiatitive Imaging Network (QIN) Lung CT Segmentation Challenge.  A TCIA Analysis Result dataset was created to enable easy re-use of the complete multi-site challenge data set.

About the NCI QIN

The mission of the QIN is to improve the role of quantitative imaging for clinical decision making in oncology by developing and validating data acquisition, analysis methods, and tools to tailor treatment for individual patients and predict or monitor the response to drug or radiation therapy. More information is available on the Quantitative Imaging Network Collections page. Interested investigators can apply to the QIN at: Quantitative Imaging for Evaluation of Responses to Cancer Therapies (U01).

Data Access

Click the  Download button to save a ".tcia" manifest file to your computer, which you must open with the NBIA Data Retriever . Click the Search button to open our Data Portal, where you can browse the data collection and/or download a subset of its contents.

Data TypeDownload all or Query/Filter
Images (DICOM, 127.5 MB)


DICOM Metadata Digest (CSV)

Click the Versions tab for more info about data releases.

Third Party Analyses of this Dataset

TCIA encourages the community to publish your analyses of our datasets. Below is a list of such third party analyses published using this Collection:

Detailed Description

Collection Statistics

Updated 2014/08/26



Number of Participants


Number of Studies


Number of Series


Number of Images


Image Size (MB)127.5

Supporting Documentation and Metadata

No supporting documentation is available for this collection.

Citations & Data Usage Policy 

Users of this data must abide by the TCIA Data Usage Policy and the Creative Commons Attribution 3.0 Unported License under which it has been published. Attribution should include references to the following citations:

Data Citation

Zhao, Binsheng. (2015). Data From Lung_Phantom. The Cancer Imaging Archive.

TCIA 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.

Other Publications Using This Data

TCIA maintains a list of publications that leverage our data. At this time, we are not aware of any publications based on this data.  If you have a  publication  you'd like to add, please  contact the TCIA Helpdesk .

Version 2 (Current): Updated 2020/09/25

Data TypeDownload all or Query/Filter
CT(127.5 MB)


(Requires the NBIA Data Retriever .)

DICOM Metadata Digest (CSV)

9/25/2020: Adjusted this table and *.tcia manifest files to remove segmentations built in Multi-site collection of Lung CT data with Nodule Segmentations. DOI: . Note that the "Search" will take you to both until you uncheck the "Include third party" button.

Version 1 (deprecated): Updated 2014/08/26

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