Building effective content-based image retrieval (CBIR) systems involves the combination of image creation, storage, security, transmission, analysis, evaluation feature extraction, and feature combination in order to store and retrieve medical images effectively. This requires the involvement of a large community of experts across several fields. We have created a CBIR system called Archimedes which integrates the community together without requiring disclosure of sensitive details. Archimedes' 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 in Archimedes through double-blind radiologist comparisons based on their annotations and feature markups. This research archive contains the essential technologies of secure transmission and storage, textual and feature searches, spatial searches, annotation searching, filtering of result sets, feature creation, and bulk loading of features, while creating a repository and testbed for the community.