RDF-ization of DICOM Medical Images towards Linked Health Data Cloud

This paper proposes a novel strategy for semantifying DICOM medical images (RDF-ization) automatically. We define an architecture that involves processes for extracting, anonymizing, and serializing metadata comprised in DICOM medical images into RDF/XML. These processes allow for semantically enriching and sharing the metadata of DICOM medical files through the Linked Health Data cloud. Thereby providing enhanced query capabilities with respect to the ones offered by current PACS environments, while exploiting all advantages of the Linking Open Data (LOD) cloud and SemanticWeb technologies.

[1]  Concetto Spampinato,et al.  A Semantic-Based Platform for Medical Image Storage and Sharing Using the Grid , 2011, BIOSTEC.

[2]  Le Gruenwald,et al.  Medical data management in the SYSEO project , 2013, SGMD.

[3]  Guillermo Palma,et al.  Drug-Target Interaction Prediction Using Semantic Similarity and Edge Partitioning , 2014, SEMWEB.

[4]  Maribel Acosta,et al.  ANAPSID: An Adaptive Query Processing Engine for SPARQL Endpoints , 2011, SEMWEB.

[5]  Vitaly Shmatikov,et al.  Robust De-anonymization of Large Sparse Datasets , 2008, 2008 IEEE Symposium on Security and Privacy (sp 2008).

[6]  H K Huang,et al.  Medical image security in a HIPAA mandated PACS environment. , 2003, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[7]  H. K. Huang,et al.  PACS and Imaging Informatics: Basic Principles and Applications , 2004 .

[8]  Saikat Mukherjee,et al.  Context-Driven Ontological Annotations in DICOM Images - Towards Semantic Pacs , 2009, HEALTHINF.

[9]  Michael Brunnbauer.  DICOM metadata as RDF , 2013, GI-Jahrestagung.

[10]  G. Patel,et al.  DICOM Medical Image Management the challenges and solutions: Cloud as a Service (CaaS) , 2012, 2012 Third International Conference on Computing, Communication and Networking Technologies (ICCCNT'12).