Abstract
In this paper, we present a Case Based Reasoning (CBR) system for the retrieval of medical cases made up of a series of images with semantic information (such as the patient age, sex and medical history). Indeed, medical experts generally need varied sources of information, which might be incomplete, uncertain and conflicting, to diagnose a pathology. Consequently, we derive a retrieval framework from the Dezert- Smarandache theory, which is well suited to handle those problems. The system is designed so that a priori knowledge and heterogeneous sources of information can be integrated in the system: in particular images, indexed by their digital content, and symbolic information. The method is evaluated on a classified diabetic retinopathy database. On this database, results are promising: the retrieval precision at five reaches 81.17%, which is almost twice as good as the retrieval of single images alone.
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© 2009 Springer-Verlag Berlin Heidelberg
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Quellec, G., Lamard, M., Cazuguel, G., Cochener, B., Roux, C. (2009). Multimodal Medical Case Retrieval using Dezert-Smarandache Theory with A Priori Knowledge. In: Vander Sloten, J., Verdonck, P., Nyssen, M., Haueisen, J. (eds) 4th European Conference of the International Federation for Medical and Biological Engineering. IFMBE Proceedings, vol 22. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89208-3_171
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DOI: https://doi.org/10.1007/978-3-540-89208-3_171
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89207-6
Online ISBN: 978-3-540-89208-3
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