Summary
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The Lung Image Database Consortium image collection (LIDC-IDRI) consists of diagnostic and lung cancer screening thoracic computed tomography (CT) scans with marked-up annotated lesions. It is a web-accessible international resource for development, training, and evaluation of computer-assisted diagnostic (CAD) methods for lung cancer detection and diagnosis. |
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Armato SG III, McLennan G, Bidaut L, McNitt-Gray MF, Meyer CR, Reeves AP, Zhao B, Aberle DR, Henschke CI, Hoffman EA, Kazerooni EA, MacMahon H, van Beek EJR, Yankelevitz D, et al.: The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A completed reference database of lung nodules on CT scans. Medical Physics, 38: 915--931, 2011.
Important note: There was a "pilot release" of 399 cases of the LIDC CT data via the NCI CBIIT installation of NBIA. The LIDC-IDRI collection contained on The Cancer Imaging Archive (TCIA) is the complete data set of all 1,010 patients which includes all 399 pilot CT cases plus the additional 611 patient CTs and all 290 corresponding chest x-rays.
In addition to following TCIA's Citation Guidelines, if you use this data in your research please be sure to include the following attribution in any publications or grant applications along with references to appropriate LIDC publications. A listing of these publications can be found on TCIA's Related Publications page.
LIDC-IDRI Attribution:
The authors acknowledge the support of the National Cancer Institute and the Foundation for the National Institutes of Health in the creation of the free publicly available LIDC/IDRI Database used in this study.
Additional information about using this data as well as some collection meta data can be obtained in the Supporting Documentation below.
Data Access
Collection Statistics |
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Modalities | CT (computed tomography) |
Number of Patients | 1,010 |
Number of Studies | 1,308 |
Number of Series | 1,018 CT |
Number of Images | 244,527 |
You can view and download these images on the Cancer Imaging Archive by selecting the LIDC-IDRI collection. If you are unsure how to download this Collection view our quick guide on Searching by Collection or you can refer to our The Cancer Imaging Archive User's Guide for more detailed instructions on using the site.
Supporting Documentation
More information about the Cancer Imaging Program's Program Announcement for LIDC can be found at: http://imaging.cancer.gov/programsandresources/InformationSystems/LIDC
Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process. |
Seven academic centers and eight medical imaging companies collaborated to create this data set which contains 1018 cases. Each subject includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories ("nodule > or =3 mm," "nodule <3 mm," and "non-nodule > or =3 mm"). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus.
Note : The TCIA team strongly encourages users to review pylidc and the Standardized representation of the TCIA LIDC-IDRI annotations using DICOM (DICOM-LIDC-IDRI-Nodules) of the annotations/segmentations included in this dataset before developing custom tools to analyze the XML version.
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Nodule Size List
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You can download this Diagnosis Data at: LIDC Diagnosis Data-01-08-10.xls
Note: This data has not yet been updated to match the new patient ID structure for the LIDC-IDRI data set (it currently still uses the pilot data patient ID schema).
AIM Annotation Conversion Project
As part of an effort to move towards standard formats for annotation and markup a project was undertaken to convert XML data from the LIDC Pilot project into Annotated Image Markup format (AIM). AIM is a standard which was developed out of the caBIG program. More information about this effort can be found here on the NCI CBIIT wiki: LIDC Conversion to AIM.
We hope to be able to provide the entire LIDC-IDRI set of markup in AIM format at some point in the future, along with a release of the ClearCanvas open source workstation which can view these markups. However at this time the project has been placed on hold. We will update this page if/when the status of this project changes.
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