The Cancer Imaging Archive (TCIA) Public Access

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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, the related SPIE Guest Editorial, and corresponding scientific manuscript.


Localtab Group


Localtab
activetrue
titleData Access
Imaging

Data

Info

You can view and download these images on The Cancer Imaging Archive by clickingImage Removed and selecting the SPIE-AAPM Lung CT Challenge collection.

 

Access

C 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 Added Image Added

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

Click the Versions tab for more info about data releases.


Localtab
titleDetailed Description

Detailed Description

Collection Statistics


Modalities

CT

Number of 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, 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

begin CT-Training.

The Patient IDs of the 60-subject test set begin

LUNGx.

Collection Statistics

(updated 11/21/2014)

Modalities

CT

Number of Patients

70

Number of Studies

70

Number of Series

70

Number of Images

22,489

Images Size (GB)12.1

If you are unsure how to download this Collection please view our quick guide on Searching by Collection or refer to our The Cancer Imaging Archive User's Guide for more detailed instructions on using the site.

Shared Lists

 LUNGx.

Nodule locations and diagnoses


Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy 

Public collection license
Info
titleData Citation

Armato III, Samuel G.; 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. https://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, Karen Drukker, Feng Li, Lubomir Hadjiiski, Georgia D. Tourassi, Roger M. Engelmann, Maryellen L. Giger, George Redmond, Keyvan Farahani, Justin S. Kirby, Laurence P. Clarke. (2016)  "LUNGx Challenge for computerized lung nodule classification," J. Med. Imag. 3(4), 044506. DOI:  10.1117/1.JMI.3.4.044506


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,  pp 1045-1057. DOI: 10.1007/s10278-013-9622-7

Other Publications Using This Data

TCIA maintains a list of publications which leverage our data. If you have a publication you'd like to add please contact the TCIA Helpdesk.


Localtab
titleVersions

Version 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)
Image Added
Nodule Locations/Diagnoses - Test Set (XLS)
Image Added

Added diagnosis data to test set XLS.

Version 1: Updated 2014/11/21

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

Image Added  Image Added

Nodule Locations/Diagnoses - Calibration Set (XLS)
Image Added
Nodule Locations - Test Set (XLS)
Image Added
Coming soon