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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.