In most biomedical disciplines, digital image data is rapidly expanding in quantity and heterogeneity, and there is an increasing trend towards the formation of archives adequate to support diagnostics and preventive medicine.
Exploration, exploitation, and consolidation of the immense image collections require tools to access structurally different data for research, diagnostics and teaching. Currently, image data is linked to textual descriptions, and data access
is provided only via these textual additives. There are virtually no tools available to access medical images directly by their content or to cope with their structural differences. Therefore, visual-based (i.e. content-based) indexing and retrieval
based on information contained in the pixel data of biomedical images is expected to have a great impact on biomedical image databases. However, existing systems for content-based image retrieval (CBIR) are not applicable to the biomedical imagery special needs, and novel methodologies are urgently needed.
This special issue grew from the work-shop, Content-Based Image Retrieval: Major Challenges for Medical Applications at SPIE’s International Symposium on Medical Imaging 2008 (Content-Based, 2008), which was convened to assess status of CBIR within the biomedical clinical and research worlds, and to collect
opinion from leading CBIR researchers about the most productive way forward. The workshop was structured around the concept of “gaps” (Deserno, Antani, & Long, 2008) between desired capabilities and use for medical CBIR, and what
has actually been realized.
Thomas M. Deserno, RWTH Aachen University, Germany