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Medical case-based retrieval: integrating query MeSH terms for query-adaptive multi-modal fusion

Garcia Seco De Herrera, Alba and Foncubierta-Rodríguez, Antonio and Müller, Henning (2015) Medical case-based retrieval: integrating query MeSH terms for query-adaptive multi-modal fusion. In: SPIE Medical Imaging, 2015-02-21 - 2015-02-26, Orlando, Florida, United States.

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Abstract

Advances in medical knowledge give clinicians more objective information for a diagnosis. Therefore, there is an increasing need for bibliographic search engines that can provide services helping to facilitate faster information search. The ImageCLEFmed benchmark proposes a medical case-based retrieval task. This task aims at retrieving articles from the biomedical literature that are relevant for differential diagnosis of query cases including a textual description and several images. In the context of this campaign many approaches have been investigated showing that the fusion of visual and text information can improve the precision of the retrieval. However, fusion does not always lead to better results. In this paper, a new query-adaptive fusion criterion to decide when to use multi-modal (text and visual) or only text approaches is presented. The proposed method integrates text information contained in MeSH (Medical Subject Headings) terms extracted and visual features of the images to find synonym relations between them. Given a text query, the query-adaptive fusion criterion decides when it is suitable to also use visual information for the retrieval. Results show that this approach can decide if a text or multi{modal approach should be used with 77.15% of accuracy.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: SPIE Medical Imaging
Uncontrolled Keywords: ImageCLEF, ImageCLEF benchmark, MeSH, Multimodal information retrieval and information fusion, query-adaptive fusion
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 22 Jan 2020 21:37
Last Modified: 22 Jan 2020 21:37
URI: http://repository.essex.ac.uk/id/eprint/26564

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