Content Based Image Retrieval (CBIR) in Remote Clinical Diagnosis and Healthcare

October 10, 2016 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Albany E. Herrmann, Vania Vieira Estrela arXiv ID 1610.02902 Category cs.CV: Computer Vision Citations 32 Venue arXiv.org Last Checked 6 months ago
Abstract
Content-Based Image Retrieval (CBIR) locates, retrieves and displays images alike to one given as a query, using a set of features. It demands accessible data in medical archives and from medical equipment, to infer meaning after some processing. A problem similar in some sense to the target image can aid clinicians. CBIR complements text-based retrieval and improves evidence-based diagnosis, administration, teaching, and research in healthcare. It facilitates visual/automatic diagnosis and decision-making in real-time remote consultation/screening, store-and-forward tests, home care assistance and overall patient surveillance. Metrics help comparing visual data and improve diagnostic. Specially designed architectures can benefit from the application scenario. CBIR use calls for file storage standardization, querying procedures, efficient image transmission, realistic databases, global availability, access simplicity, and Internet-based structures. This chapter recommends important and complex aspects required to handle visual content in healthcare.
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