A medical, description logic based, ontology for skin lesion images

Researchers have portrayed an increasing effort towards providing formal computational frameworks to consolidate the plethora of notions and relations used in the medical domain. Despite the fact that there are many reasons for this, the need for standardization of protocols and terminology is critical, not only for the provision of uniform levels of health care, but also to facilitate medical science research. In the domain of skin lesions, the variability of semantic features contained within images is major among the barriers to the medical understanding of the symptoms and development of early skin cancers. Such variability is acknowledged across specialist fields of medicine, motivating standardization of terminologies for reporting medical practice. The desideratum of making these standards machine-readable has led to their formalization in the form of ontologies. Ontologies are computational artifacts designed to provide semantic representations of a particular domain of interest. Such a representation can be encoded and reused, allowing navigation of the key concepts recorded and retrieval of information indexed against it. This fact bridges the required standardization gap by offering a set of labeling options to record observations and events encountered by medical experts. Given the twin goals of ontologies - representation and standardization - the present paper deals with the creation of an ontology for skin lesion images, encoded using Description Logic in OWL format, which can be used for decision support systems that operate on a classification basis. The declarative framework within which ontologies are encoded can transcend any specific application context and help dermatologists perform semantic inference on skin lesion images. Furthermore, extensions are easier to be accomplished and new classes can be straightforwardly incorporated.