Tuesday, January 20, 2009

Content-Based Image Retrieval: Major Challenges for Biomedical Applications

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
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