Geographically Distributed Complementary Content-Based Image Retrieval Systems for Biomedical Image Informatics

There is a significant increase in the use of medical images in clinical medicine, disease research, and education. While the literature lists several successful systems for content-based image retrieval and image management methods, they have been unable to make significant inroads in routine medical informatics. This can be attributed to the following: (i) the challenging nature of medical images, (ii) need for specialized methods specific to each image type and detail, (iii) lack of advances in image indexing methods, and (iv) lack of a uniform data and resource exchange framework between complementary systems. Most systems tend to focus on varying degrees of the first two items, making them very versatile in a small sampling of the variety of medical images but unable to share their strengths. This paper proposes to overcome these shortcomings by defining a data and resource exchange framework using open standards and software to develop geographically distributed toolkits. As proof-of-concept, we describe the coupling of two complementary geographically separated systems: the IRMA system at Aachen University of Technology in Germany, and the SPIRS system at the U. S. National Library of Medicine in the United States of America.