Image indexing, storage, and retrieval based on pictorial content is a feature of image database systems which is becoming of increasing importance in many application domains. Medical image database systems, which support the retrieval of images generated by different modalities based on their pictorial content, will provide added value to future generation picture archiving and communication systems (PACS), and can be used as a diagnostic decision support tools and as a tool for medical research and training. We present the architecture and features of I2C, a system for the indexing, storage, and retrieval of medical images by content. A unique design feature of this architecture is that it also serves as a platform for the implementation and performance evaluation of image description methods and retrieval strategies. I2C is a modular and extensible system, which has been developed based on object-oriented principles. It consists of a set of cooperating modules which facilitate the addition of new graphical tools, image description and matching algorithms. These can be incorporated into the system at the application level. The core concept of I2C is an image class hierarchy. Image classes encapsulate different segmentation and image content description algorithms. Medical images are assigned to image classes based on a set of user-defined attributes such as imaging modality, type of study, anatomical characteristics, etc. This class-based treatment of images in the I2C system achieves increased accuracy and efficiency of content-based retrievals, by limiting the search space and allowing specific algorithms to be fine-tuned for images acquired by different modalities or representing different parts of the anatomy.