Semantic Gastroenterological Images Annotation and Retrieval - Reasoning with a Polyp Ontology

Yahia Chabane, Christophe Rey

Abstract

In gastroenterology, monitoring polyps is fundamental in order to detect a cancer. It may be difficult for surgeons to decide whether he should remove a polyp or not. A wrong decision may generate unjustified costs or be dangerous for the patient health. To help their diagnosis, physicians may need images of previously treated cases. For this purpose, we present in this paper a semantic image retrieval approach focused on endoscopic gastroenterological images. This approach is based on a slight extension of classical description logic reasonings, associated with a polyp ontology and a suited image annotation mechanism.

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Paper Citation


in Harvard Style

Chabane Y. and Rey C. (2013). Semantic Gastroenterological Images Annotation and Retrieval - Reasoning with a Polyp Ontology . In Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2013) ISBN 978-989-8565-81-5, pages 293-300. DOI: 10.5220/0004549202930300


in Bibtex Style

@conference{keod13,
author={Yahia Chabane and Christophe Rey},
title={Semantic Gastroenterological Images Annotation and Retrieval - Reasoning with a Polyp Ontology},
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2013)},
year={2013},
pages={293-300},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004549202930300},
isbn={978-989-8565-81-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2013)
TI - Semantic Gastroenterological Images Annotation and Retrieval - Reasoning with a Polyp Ontology
SN - 978-989-8565-81-5
AU - Chabane Y.
AU - Rey C.
PY - 2013
SP - 293
EP - 300
DO - 10.5220/0004549202930300