The complete set of LIDC/IDRI images can be found at The Cancer Imaging Archive.
The Lung Image Database Consortium wiki page on TCIA contains supporting documentation for the LIDC/IDRI collection.
Preliminary clinical studies have shown that spiral CT scanning of the lungs can improve early detection of lung cancer in high-risk individuals. Image processing algorithms have the potential to assist in lesion detection on spiral CT studies, and to assess the stability or change in lesion size on serial CT studies. The use of such computer-assisted algorithms could significantly enhance the sensitivity and specificity of spiral CT lung screening, as well as lower costs by reducing physician time needed for interpretation.
The intent of the Lung Imaging Database Consortium (LIDC) initiative was is to support a consortium of institutions to develop consensus guidelines for a spiral CT lung image resource and to construct a database of spiral CT lung images. The investigators funded under this initiative have created a set of guidelines and metrics for database use and for developing a database as a test-bed and showcase for those methods. The database is available to researchers and users through the Internet and has wide utility as a research, teaching, and training resource.
Specifically, the LIDC initiative aims were are to provide:
This resource will stimulate further database development for image processing and CAD evaluation for applications that include cancer screening, diagnosis, and image-guided intervention, and treatment. Therefore, the NCI encourages investigator-initiated grant applications that utilize the database in their research. NCI also encourages investigator-initiated grant applications that provide tools or methodology that may improve or complement the mission of the LIDC.
See the Program Announcement: RFA: CA-01-001 LUNG IMAGE DATABASE RESOURCE FOR IMAGING RESEARCH for more information.