VIA Group Public Databases

Documented image databases are essential for the development of quantitative image analysis tools especially for tasks of computer-aided diagnosis (CAD). In collaboration with the I-ELCAP group we have established two public image databases that contain lung CT images in the DICOM format together with documentation of abnormalities by radiologists. Please access the links below for more details:

IN DEVELOPMENT SIMBA Framework for ECLAP Public Database

A demonstration website for the SIMBA Framework for image documetnation that is based on the ELCAP public database below. This database is still under development.

ECLAP public database of whole lung CT images

50 cases of low-dose thin-slice chest CT images with annotations for small nodules

Public Database to Address Drug Response

Over 100 cases of CT chest images illustrating the spectrum of nodule presentations together with a range of computer analysis methods.

VOLCANO'09 Nodule Change Challenge

A set of benchnmark pairs CT images of pulmonary nodules to provide a challenge for the evaluation of nodule change in size measurement methods

LIDC database size index list

Standardized nodule lists and spreadsheets for the LIDC public image database

Micro CT of Murine Lung Neoplasms

Micro-CT murin images and measurements for the following paper: M. Li, A. Jirapatnakul, M. L. Riccio, R. S. Weiss, and A. P. Reeves, "Growth pattern analysis of murine lung neoplasms by advanced semi-automated quantification of micro-ct images," PLOS ONE, 8(12):e83806, 2013

In addition to the databases shown above the VIA and ELCAP groups have made contributions to The National Cancer Institute (NCI) efforts to provide public image databases. In particular we have contributed to the following projects:

The Lung Image Database Consortium (LIDC)

The Image Database Resource Initiative (IDRI)

The Reference Image Database to Evaluate Response (RIDER)

The public databases for these projects can be accessed through the The Cancer Imaging Archive (TCIA).