Child pages
  • Lung Phantom

Versions Compared

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.

Summary

Excerpt

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 Digital Object Identifier 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).

 

Localtab Group
Localtab
activetrue
titleData Access

Data Access

Choosing the Download option will provide you with a file to launch the TCIA Download Manager to download the entire collection. If you want to browse or filter the data to select only specific scans/studies please use the Search By Collection option.

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.

Localtab
titleDetailed Description

Detailed Description

Collection Statistics

Updated 2014/08/26

Modalities

CT

Number of Patients

1

Number of Studies

1

Number of Series

1

Number of Images

237

Image Size (MB)127.5

Supporting Documentation and Metadata

No supporting documentation is available for this collection.

Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy 

This collection is freely available to browse, download, and use for commercial, scientific and educational purposes as outlined in the Creative Commons Attribution 3.0 Unported License.  See TCIA's Data Usage Policies and Restrictions for additional details. Questions may be directed to help@cancerimagingarchive.net.

Please be sure to include the following citations in your work if you use this data set:

Info
titleData Citation

Zhao, Binsheng. (2015). Data From Lung_Phantom. The Cancer Imaging Archive. http://doi.org/10.7937/K9/TCIA.2015.08A1IXOO

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)

Info
titleQIN Challenge DOI Citation

Jayashree Kalpathy-Cramer, Sandy Napel, Dmitry Goldgof, Binsheng Zhao. (2015). Multi-site collection of Lung CT data with Nodule Segmentations. The Cancer Imaging Archive. http://doi.org/10.7937/K9/TCIA.2015.1BUVFJR7

Other Publications Using This Data

TCIA maintains a list of publications which 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.

Localtab
titleVersions

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

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

Image Modified Image Modified 

DICOM Metadata Digest (CSV)Image Added