A web database for Computer-Aided Detection and Diagnosis of medical images

Building effective Computer-Aided Detectionand Diagnosis (CAD) systems involves the combination of running experiments, image markup, security, analysis, evaluation, feature extraction, and feature combination in order to capture and evaluate medical images effectively. This requires the involvement of a large community of experts across several fields. We have created a CAD development system which integrates the community together without requiring disclosure of sensitive details. The system design enables researchers to upload their feature sets and quickly compare the effectiveness of their methods against other stored feature sets. Additionally, research into the techniques used by radiologists is possible through double-blind radiologist comparisons based on their annotations and features markups. This research archive contains the essential technologies of secure transmission and storage, textual and feature searches, spatial scarches, annotation searching, filtering of result sets, feature creation, and bulk loading of features, while creating a respiratory and testbed for the community.