Semantic Representation of Neuroimaging Observations: Proof of Concept based on the VASARI Terminology
Emna Amdouni, Bernard Gibaud
2018
Abstract
The main objective of this work is to facilitate the identification, sharing and reasoning about cerebral tumors observations via the formalization of their semantic meanings in order to facilitate their exploitation in both the clinical practice and research. We have focused our analysis on the VASARI terminology as a proof of concept, but we are convinced that our work can be useful in other biomedical imaging contexts. In this paper, we propose (1) a methodology, a domain ontology and an annotation tool for providing unambiguous formal definitions of neuroimaging data, (2) an experimental work on the REMBRANDT dataset to demonstrate the added value of our work over existing methods, namely DICOM SR and the AIM model.
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in Harvard Style
Amdouni E. and Gibaud B. (2018). Semantic Representation of Neuroimaging Observations: Proof of Concept based on the VASARI Terminology. In Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - Volume 2: KEOD; ISBN 978-989-758-330-8, SciTePress, pages 63-74. DOI: 10.5220/0006931100630074
in Bibtex Style
@conference{keod18,
author={Emna Amdouni and Bernard Gibaud},
title={Semantic Representation of Neuroimaging Observations: Proof of Concept based on the VASARI Terminology},
booktitle={Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - Volume 2: KEOD},
year={2018},
pages={63-74},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006931100630074},
isbn={978-989-758-330-8},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - Volume 2: KEOD
TI - Semantic Representation of Neuroimaging Observations: Proof of Concept based on the VASARI Terminology
SN - 978-989-758-330-8
AU - Amdouni E.
AU - Gibaud B.
PY - 2018
SP - 63
EP - 74
DO - 10.5220/0006931100630074
PB - SciTePress