| Abstract | Building effective content-based image retrieval (CBIR) systemsinvolves 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.
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