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:
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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. |
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50 cases of low-dose thin-slice chest CT images with annotations for small nodules | |
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Over 100 cases of CT chest images illustrating the spectrum of nodule presentations together with a range of computer analysis methods. | |
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A set of benchnmark pairs CT images of pulmonary nodules to provide a challenge for the evaluation of nodule change in size measurement methods | |
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Standardized nodule lists and spreadsheets for the LIDC public image database | |
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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:
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The Lung Image Database Consortium (LIDC) |
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The Image Database Resource Initiative (IDRI) |
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The Reference Image Database to Evaluate Response (RIDER) |
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The public databases for these projects can be accessed through the The Cancer Imaging Archive (TCIA). |