@conference {ICBO_2018_37,
	title = {ICBO_2018_37: Ontology-Enhanced Representations of Non-image Data in The Cancer Image Archive},
	booktitle = {International Conference on Biomedical Ontology (ICBO 2018)},
	series = {Proceedings of the International Conference on Biological Ontology (2018)},
	year = {2018},
	month = {08/06/2018},
	publisher = {International Conference on Biological Ontology},
	organization = {International Conference on Biological Ontology},
	abstract = {<p>The Cancer Image Archive (TCIA) hosts over 11 million de-identified medical images related to cancer for research reuse. These are organized around DICOM-format radiological collections that are grouped by disease type, modality, or research focus. Many collections also include diverse non-image datasets in a variety of formats without a common approach to representing the entities that the data are about. This paper describes work to make these diverse non-image data more accessible and usable by transforming them into integrated semantic representations using Open Biomedical Ontologies, highlights obstacles encountered in the data, and presents detailed representations data found in select collections.</p>
},
	keywords = {Cancer, imaging, ontology development, semantics},
	url = {http://ceur-ws.org/Vol-2285/ICBO_2018_paper_37.pdf },
	author = {Jonathan Bona and Tracy Nolan and Mathias Brochhausen}
}
