A framework for radiological assistant systems

Abstract

The market for health care systems supporting physicians and improving their daily routine is dynamically growing. The development of these systems makes great demands on the handling of medical knowledge, like anatomical and process knowledge. In this paper, a special approach for the radiological domain is presented. Our framework includes mechanisms to store medical knowledge in different knowledge containers, whose importance varies from application to application, and to support the execution of the processes. Three applications are introduced by way of example. We analyze these application scenarios to find the knowledge-intensive tasks that can be supported by an assistant system. The implemented solutions are integrated in the daily work of our radiological partner hospitals.