Knowledge Augmented Medical Image Retrieval System

We are living in an era of information explosion. Medical images are generated at an accelerating rate. A more effective information technology to deal with storage and retrieval of such huge amount of medical image data is needed. The purpose of this paper is to demonstrate by presenting a concrete example that a knowledge augmented medical image retrieval system by means of automated feature extraction is possible. It provides not only decision support in the clinical setting but an education/ research platform upon which issues regarding computer-aided diagnosis and inter-observer variations among radiologists can be addressed systematically and effectively. It inspires more productive man-computer collaboration by bringing computer intelligence to new heights through knowledge transfer to meet the challenge of information explosion.