Please cite the following paper when using this data in your publications:

  • Bernal, J., Tajkbaksh, N., Sánchez, F.J., Matuszewski, B., Chen H., Yu, L., Angermann, Q., Romain, O., Rustad, B., Balasingham, I., Pogorelov, K., Choi, S., Debard, Q., Maier-Hein, L., Speidel, S., Stoyanov, D., Brandao, P., Cordova, H., Sánchez-Montes, C., Gurudu, S.R., Fernández-Esparrach, G., Dray, X.,  Liang, J. and Histace, A. "Comparative Validation of Polyp Detection Methods in Video Colonoscopy: Results from the MICCAI 2015 Endoscopic Vision Challenge", IEEE Transactions on Medical Imaging, 2017, Issue 99

Please refer to each database for additional citation information specific to each database.

We present in this page the different databases used within Automatic Polyp Detection challenge:

Name Representative image Purpose Brief definition
CVC-ClinicDB Training database 612 still images from 29 different sequences. Each image has its associated manually annotated ground truth covering the polyp. More details and download links here
ETIS-Larib  Testing database More details and download links here
ASU-Mayo Clinic Colonoscopy Video (c) Database Training and testing database More details here. The ASU-Mayo Clinic Colonoscopy Video (c) Database is copyrighted. If you are interested in using this database, please contact Prof. Jianming Liang at Arizona State University.