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Partial Shape Matching for CBIR of Spine X-Ray Images
Efficient content-based image retrieval (CBIR) of biomedical images is a challenging problem. Feature representation algorithms used in indexing medical images on the pathology of interest have to address conflicting goals of reducing feature dimensionality while retaining important and often subtle biomedical features. In case of the vertebra, its shape effectively describes various pathologies identified by medical experts as being consistently and reliably found in x-rays in the image collection. A suitable shape method must enable retrieval relevant to the pathology in question. An approach to enabling pathology based retrieval is to use partial shape matching techniques. This paper describes our research in the development of such methods and initial retrieval results and related issues. The research is a part of our ongoing effort in developing CBIR for digitized images of a collection of 17,000 cervical and lumbar spine x-rays taken as a part of the second National Health and Nutrition Examination Survey (NHANES II) at the Lister Hill National Center for Biomedical Communications, an intramural Research and Development division of the U.S. National Library of Medicine.