title: Towards a semantic PACS: Using Semantic Web technology to represent imaging data.
abstract: The DICOM standard is ubiquitous within medicine. However, improved DICOM semantics would significantly enhance search operations. Furthermore, databases of current PACS systems are not flexible enough for the demands within image analysis research. In this paper, we investigated if we can use Semantic Web technology, to store and represent metadata of DICOM image files, as well as linking additional computational results to image metadata. Therefore, we developed a proof of concept containing two applications: one to store commonly used DICOM metadata in an RDF repository, and one to calculate imaging biomarkers based on DICOM images, and store the biomarker values in an RDF repository. This enabled us to search for all patients with a gross tumor volume calculated to be larger than 50 cc. We have shown that we can successfully store the DICOM metadata in an RDF repository and are refining our proof of concept with regards to volume naming, value representation, and the applications themselves.
authors.affiliation: Maastricht University Medical Centre+, Department of Radiation Oncology (MAASTRO) GROW School for Oncology and Developmental Biology, Maastricht, The Netherlands.
authors.forename: Johan
authors.initials: J
authors.lastname: Van Soest
authors.affiliation: Maastricht University Medical Centre+, Department of Radiation Oncology (MAASTRO) GROW School for Oncology and Developmental Biology, Maastricht, The Netherlands.
authors.forename: Tim
authors.initials: T
authors.lastname: Lustberg
authors.affiliation: Sohard Software GmbH, Fürth, Germany.
authors.forename: Detlef
authors.initials: D
authors.lastname: Grittner
authors.affiliation: Maastricht University Medical Centre+, Department of Radiation Oncology (MAASTRO) GROW School for Oncology and Developmental Biology, Maastricht, The Netherlands.
authors.forename: M Scott
authors.initials: MS
authors.lastname: Marshall
authors.affiliation: Maastricht University Medical Centre+, Department of Radiation Oncology (MAASTRO) GROW School for Oncology and Developmental Biology, Maastricht, The Netherlands.
authors.forename: Lucas
authors.initials: L
authors.lastname: Persoon
authors.affiliation: Maastricht University Medical Centre+, Department of Radiation Oncology (MAASTRO) GROW School for Oncology and Developmental Biology, Maastricht, The Netherlands.
authors.forename: Bas
authors.initials: B
authors.lastname: Nijsten
authors.affiliation: Sohard Software GmbH, Fürth, Germany.
authors.forename: Peter
authors.initials: P
authors.lastname: Feltens
authors.affiliation: Maastricht University Medical Centre+, Department of Radiation Oncology (MAASTRO) GROW School for Oncology and Developmental Biology, Maastricht, The Netherlands.
authors.forename: Andre
authors.initials: A
authors.lastname: Dekker
mesh_terms: D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000592:standards*; D016247:Information Storage and Retrieval / Q000592:standards*; D020407:Internet; D009323:Natural Language Processing; D009369:Neoplasms / Q000473:pathology*; D017410:Practice Guidelines as Topic; D011873:Radiology Information Systems / Q000592:standards*; D012660:Semantics; D009626:Terminology as Topic; D047368:Tumor Burden