title: A medical ontology for intelligent web-based skin lesions image retrieval.
abstract: Researchers have applied increasing efforts towards providing formal computational frameworks to consolidate the plethora of concepts and relations used in the medical domain. In the domain of skin related diseases, the variability of semantic features contained within digital skin images is a major barrier to the medical understanding of the symptoms and development of early skin cancers. The desideratum of making these standards machine-readable has led to their formalization in ontologies. In this work, in an attempt to enhance an existing Core Ontology for skin lesion images, hand-coded from image features, high quality images were analyzed by an autonomous ontology creation engine. We show that by exploiting agglomerative clustering methods with distance criteria upon the existing ontological structure, the original domain model could be enhanced with new instances, attributes and even relations, thus allowing for better classification and retrieval of skin lesion categories from the web.
authors.affiliation: University of the Aegean, Samos, Greece. mmarag@aegean.gr
authors.forename: Manolis
authors.initials: M
authors.lastname: Maragoudakis
authors.forename: Ilias
authors.initials: I
authors.lastname: Maglogiannis
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D002965:Classification / Q000379:methods; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D006115:Greece; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods; D020407:Internet; D008545:Melanoma / Q000175:diagnosis* / Q000473:pathology; D012871:Skin Diseases / Q000175:diagnosis / Q000473:pathology; D009626:Terminology as Topic