17 January 2005 Applying vertebral boundary semantics to CBIR of digitized spine x-ray images
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In developing reliable content-based image retrieval (CBIR) techniques specialized for biomedical image retrieval, applicable feature representation and similarity algorithms have to balance conflicting goals of efficient and effective retrieval. These methods must index important and often subtle biomedical features and also incorporate their siginificance. From a collection of digitized X-rays of the spine, such as that from the second National Health and Nutrition Examination Survey (NHANES II) maintained by the U.S. National Library of Medicine, a typical user may be interested in cases where the pathology is exhibited by only a pertinent small region of the vertebral boundary: for this experiment, the Anterior Osteophyte (AO). A previous experiment in such pathology-based retrieval using partial shape matching (PSM) on a subset from the collection; 89% normal vertebrae and 45% of moderate and severe cases were correctly retrieved. Additionally, analysis of results also showed high inter-pathology-class confusion. The experiment showed that shape matching without incorporating application semantics is insufficient for correct retrieval of pathological cases. This paper describes an automatic localization algorithm that incorporates reasoning about vertebral boundary semantics equivalent to those applied by the content-expert as a step in our enhancements to PSM, and results from initial experiments.
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Sameer K. Antani, Sameer K. Antani, L. Rodney Long, L. Rodney Long, George R. Thoma, George R. Thoma, "Applying vertebral boundary semantics to CBIR of digitized spine x-ray images", Proc. SPIE 5682, Storage and Retrieval Methods and Applications for Multimedia 2005, (17 January 2005); doi: 10.1117/12.588467; https://doi.org/10.1117/12.588467

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