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Seeing Is Believing - FAIR Metadata for Medical Imaging Data in the SPHN Semantic Interoperability Framework
Edwin Ter Voert1, Harald Witte2, Vasundra Touré2
1Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland.
Abstract:
Medical imaging is vital to modern healthcare, supporting diagnostics, treatment, and research. To integrate imaging data within the Swiss Personalized Health Network (SPHN), we developed an SPHN RDF Schema extension for standardized and structured imaging metadata. Built on the FAIR (Findable Accessible, Interoperable, Reusable) principles and established standards like DICOM and SNOMED CT, this extension models essential imaging information and links it to related clinical data, such as diagnoses, patient visits, and biosamples. This enhances semantic coherence and addresses interoperability gaps, thereby enabling applications in clinical research and precision medicine using the rich resources medical imaging data represents.