Image Data Base Archive Design Using Parallel Architectures And Expert Systems

Abstract

Data base archive system (DBAS) for picture archiving and communication systems (PACS) require very large storage systems. The storage systems must be high speed and must be very inteligent in order to handle requests for image storage and retrieval. The DBAS is interfaced to a high speed fiber optic network via ACR-NEMA interfaces. User workstations and imaging equipment represent the sinks and sources of digital image data. The image data to be stored in the DBAS may be as large as 2048 x 2048 x 12 bits, or 50 megabits per image. Image storage and retrieval requests contain a mix of image and text data. The text data represents patient information and doctor's diagnosis. User scenarios include simultaneous image generation and retrieval. Hence, the image data transfer and storage must occur at a high speed in order to achieve response times of less than two seconds per image request. The approaches used to implement a DBAS must contain parallel and intelligent processing to handle the large amount of image data in a real-time mode. In this paper characteristics, elements of image data base system, and the functional description of DBAS architecture components and intelligence are described. The use of expert systems to process the image requests and to locate the information is explored.