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  • SPIE-AAPM-NCI Lung Nodule Classification Challenge Dataset (SPIE-AAPM Lung CT Challenge)

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Summary

 


Excerpt

As part of the 2015 SPIE Medical Imaging Conference, SPIE – with the support of American Association of Physicists in Medicine (AAPM) and the National Cancer Institute (NCI) – will conduct a “Grand Challenge” on quantitative image analysis methods for the diagnostic classification of malignant and benign lung nodules. The LUNGx Challenge will provide a unique opportunity for participants to compare their algorithms to those of others from academia, industry, and government in a structured, direct way using the same data sets.

 



  • Release date of calibration set cases with truth:  November 21, 2014
  • Release date of test set cases without truth:  January 9, 2015
  • Submission date for participants to submit test set classification results:  February 6, 2015
  • SPIE Medical Imaging meeting:  February 21 to 26, 2015

 For For more information please refer to: LUNGx SPIE-AAPM-NCI Lung Nodule Classification Challenge and the , the related SPIE Guest Editorial, and corresponding scientific manuscript.


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 optionC lick 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, 12.1GB)
 Image Removed
Nodule Locations/Diagnoses - Calibration Set (XLS)
Nodule Locations/Diagnoses - Test Set (XLS)

Click the Versions tab for more info about data releases.


Localtab
titleDetailed Description

Detailed Description

Collection Statistics

 


Modalities

CT

Number of

Patients

Participants

70

Number of Studies

70

Number of Series

70

Number of Images

22,489

Images Size (GB)12.1

For more information please refer to: LUNGx SPIE-AAPM-NCI Lung Nodule Classification Challenge and , the related SPIE Guest Editorial, and the follow up scientific manuscript.

Counts below reflect both the training set (10 subjects) and test set (60 subjects). The Patient IDs of the 10-subject training set begin CT-Training. The Patient IDs of the 60-subject test set begin LUNGx.

Nodule locations and diagnoses


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:
Public collection license
Info
titleSPIE-AAPM Lung CT Challenge Data Citation

Armato III, Samuel G. Armato III; ; Hadjiiski, Lubomir; Tourassi, Georgia D.; Drukker, Karen; Giger, Maryellen L.; Li, Feng; Redmond, George; Farahani, Keyvan; Kirby, Justin S.; Clarke, Laurence P. (2015): . SPIE-AAPM-NCI Lung Nodule Classification Challenge Dataset; . The Cancer Imaging Archive. httphttps://dx.doi.org/10.7937/K9/TCIA.2015.UZLSU3FL


Info
titlePublication Citation

Armato III SG, Hadjiiski LM, Tourassi GD, Drukker K, Giger ML, Li F, Redmond G, Farahani K, Kirby JS, Clarke LP.  (2015). Guest Editorial: LUNGx Challenge for computerized lung nodule classification: reflections and lessons learned. Journal of Medical Imaging. SPIE-Intl Soc Optical Eng. DOI:  10.1117/1.jmi.2.2.020103


Info
titlePublication Citation

Samuel G. Armato, III ; Karen Drukker, Feng Li, Lubomir Hadjiiski ; , Georgia D. Tourassi ; Karen Drukker ; , Roger M. Engelmann, Maryellen L. Giger ; Feng Li ; , George Redmond ; , Keyvan Farahani ; , Justin S. Kirby ; , Laurence P. Clarke. Guest Editorial: (2016)  "LUNGx Challenge for computerized lung nodule classification: reflections and lessons learned. ," J. Med. Imag. 2 3(24), 020103 (Jun 25, 2015).   http://dx.doi.org/044506. DOI:  10.1117/1.JMI.23.2.020103 (paper) 4.044506


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.  (2013) 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)DOI: 10.1007/s10278-013-9622-7

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

2 (Current): Updated 2016/09/23

Data TypeDownload all or Query/Filter
Images (DICOM, 12.1GB)

Image Added  Image Added

(Download requires the NBIA Data Retriever .)

Nodule Locations/Diagnoses - Calibration Set (XLS)
Nodule Locations/Diagnoses - Test Set (XLS)

Added diagnosis data to test set XLS.

Version 1: Updated 2014/11/21

Data TypeDownload all or Query/Filter
Images (DICOM, 12.1GB)
Nodule Locations/Diagnoses - Calibration Set (XLS)
Nodule Locations - Test Set (XLS)