This paper describes the Center for Imaging Systems Optimization's (CISO) initial efforts to develop a query system that will enhance medical image archive retrieval. As medical archive systems become more commonplace, it is important to examine the system architecture, associate data types, and query support required to effectively take advantage of these systems. Our implementation is a federated system of a relational database, textual database, and image server. The architecture is based on a client-server, extended relational data model. Access is possible through an X window compatible query interface. The data scheme is based on inclusive divisions of the data by patient, study, series, and images. These support patient history, study diagnosis, series protocols, and image observations. This scheme defines four tables in the relational database and four text fields. Acquired images are stored in the image archive, while associated header data is mapped into the relational tables. Dictated readings and other textual information is added and indexed to the image as it is acquired. This system supports a wide range of ad hoc queries based on any or all of the four data categories.