FDA phantom CT database: a resource for the assessment of lung nodule size estimation methodologies and software development

Marios A. Gavrielides; Lisa M. Kinnard; Kyle J. Myers; Rongping Zeng; Nicholas Petrick

doi:10.1117/12.844329

9 March 2010 FDA phantom CT database: a resource for the assessment of lung nodule size estimation methodologies and software development

Marios A. Gavrielides, Lisa M. Kinnard, Kyle J. Myers, Rongping Zeng, Nicholas Petrick

Author Affiliations +

Proceedings Volume 7624, Medical Imaging 2010: Computer-Aided Diagnosis; 762417 (2010) https://doi.org/10.1117/12.844329
Event: SPIE Medical Imaging, 2010, San Diego, California, United States

Abstract

As part of a more general effort to probe the interrelated factors impacting the accuracy and precision of lung nodule size estimation, we have been conducting phantom CT studies with an anthropomorphic thoracic phantom containing a vasculature insert on which synthetic nodules were inserted or attached. The utilization of synthetic nodules with known truth regarding size and location allows for bias and variance analysis, enabled by the acquisition of repeat CT scans. Using a factorial approach to probe imaging parameters (acquisition and reconstruction) and nodule characteristics (size, density, shape, location), ten repeat scans have been collected for each protocol and nodule layout. The resulting database of CT scans is incrementally becoming available to the public via the National Biomedical Imaging Archive to facilitate the assessment of lung nodule size estimation methodologies and the development of image analysis software among other possible applications. This manuscript describes the phantom CT scan database and associated information including image acquisition and reconstruction protocols, nodule layouts and nodule truth.

Citation Download Citation

Marios A. Gavrielides, Lisa M. Kinnard, Kyle J. Myers, Rongping Zeng, and Nicholas Petrick "FDA phantom CT database: a resource for the assessment of lung nodule size estimation methodologies and software development", Proc. SPIE 7624, Medical Imaging 2010: Computer-Aided Diagnosis, 762417 (9 March 2010); https://doi.org/10.1117/12.844329

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