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Living with the semantic gap - 2006


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semantic technologies used to overcome issues with semantic annotation of entities in medical information systems

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Living with the semantic gap - 2006

  1. 1. Living with the Semantic Gap Experiences and Remedies in the Context of Medical Imaging Yannis Kalfoglou, Srinandan Dasmahapatra, David Dupplaw, Bo Hu, Paul Lewis, Nigel Shadbolt  Grid based Knowledge Services  Dynamic Registration of Images (MIAS - MIAKT) domain of Triple Assessment (TA) in medical decision making (MIAKT)  Grid Reasoning Services  Ontology Services – Breast Cancer Imaging Ontology (BCIO – MIAKT) classify, cluster, retrieve images – (MIAKT)  Enrichment and Image Annotation Services using BCIO (MIAKT)  Semantic Alignment of Image Representations Ontology mapping (CROSI) MIAKT – Medical Imaging and Advanced Knowledge Technologies • 2 year EPSRC project (2002-2004), Multi-Disciplinary, Multi-Media Knowledge Decision made about patient’s treatment formed by 2 large IRCs (Advanced Knowledge Technologies (AKT), Medical Images and Signals (MIAS) Radiologist (X-ray, MRI and UltraSound Mammograms) Diagnosis correct 95% of the time • 10% of women develop breast cancer (3 million screenings per year in UK) Pathologist (Pathological Slides) But how? No explicit knowledge Clinician (Patient Records, Patient History) MIAKT provides support to this process Framework Knowledge Technologies involved • Knowledge acquisition and ontology development • Semantic annotation of images • Language generation • Annotation based clustering and classification • Grid Internet Reasoning Service and Problem Solving Environments • Issue tracking and collaborative problem solving <Mammo-Abnormality rdf:ID="ROI-0001-0001"> <has-depth rdf:resource='d epth-subareolar'/> <has-morph-feature <rdf:Description rdf:resource='shape-mammo-irregular'/> rdf:ID="ROI-0001-0001"> <rdf:type> <has-morph-feature <rdfs:Class rdf:about="#Mammo-Abnormality"/> rdf:resource='margin-mammo-spiculated'/> <rdf:Description rdf:ID="ROI-0001-0001"> </rdf:type> <is-finding rdf:resource='mass'/ > <rdf:type> </RDFNsId2:Mammo-Abnormality> <RDFNsId2:has-depth rdf:resource='d epth-subareolar' <rdfs:Class rdf:about="#Mammo-Abnormality"/> rdf:type='Depth-Descriptor'/> </rdf:type> ... ... OWL <RDFNsId2:has-depth rdf:resource='d epth-subareolar' </RDFNsId2:Mammo-Abnormality> rdf:type='Depth-Descriptor'/> ... ... DAML </RDFNsId2:Mammo-Abnormality> RDF Task Invocation Framework <miakt_fw:Instance-Handler rdf:about="MIAKT-System-Preferences_00043" miakt_fw:has-name="PatientHandler"> <miakt_fw:has-class> domain.miakt.PatientHandler </miakt_fw:has-class> <miakt_fw:has-description>Handler for instance information </miakt_fw:has-description> <miakt_fw:has-type>&domain;Patient</miakt_fw:has-type> </miakt_fw:Instance-Handler> Nature Language Generation Services • Mark up patient data and images from the ontology and store as RDF files • Generate report based on the RDF files • UMLS provides definitions for medical terms in the reports <RDFNsId2:Mammo-Abnormality rdf:about='PE-0001-0001' RDFNsId2:has-branch='false' RDFNsId2:has-size='10' RDFNsId2:graphic-region='Abnorm0'> <RDFNsId2:has-depth rdf:resource='depth-subareolar' rdf:type='Depth-Descriptor'/ > EPSRC-LSI Report The 68 years old patient is <RDFNsId2:has-morph-feature rdf:resource='shape-mammo-irregular' involved in a multi-disciplinary rdf:type='Mammo-Shape'/ > <RDFNsId2:has-morph-feature meeting procedure. The multi- rdf:resource='margin-mammo-spiculated' rdf:type='Mammo-Margin'/> disciplinary assessment procedure <RDFNsId2:is-finding rdf:resource='mass' contains a mammography exam. rdf:type='Mass'/> The mammography exam is Publishing <RDFNsId2:distri-single-obs rdf:resource='distri-xray-cluster' carried out on the patient on 22 9 rdf:type='Distribution-Mammo'/> </RDFNsId2:Mammo-Abnormality> 1995. The mammography exam produced a right CC image. The right CC image contains a Region of Interest… The ROI has a mass, a probably malignant assessment, a microlobulated margin, and a round shape … System Features Ontologies and instances • Graphical navigation • Retrieval and Annotation: • <conceptual terms, image features> • Image processing algorithms • Interface to web services using RDF triple store • Internet Reasoning Services based on declarative descriptions • Language generation – patient reports • Grid enabled image registration CROSI - Capturing Representing and Operationalising Semantic Integration • 1 year HP funded project (2004-2005) • Semantic Integration Technologies Survey • Modular architecture for Semantic Integration • Flexible, multi-matcher, multi-strategy aligner • Investigate Semantic Integration technology • Semantic Intensity Spectrum Systems • Open source, API, documented, evaluated • Focus on Ontology mapping and merging • Classify Integration Technologies • Exemplar: CMS (CROSI Mapping System) • Linguistic, Structure, Syntax, Semantics Semantic Intensity Spectrum Exemplar algorithm: structure-based CMS GUI f (name similarity, domain similarity, range similarity ) Domain Domain of P1 H of P1’ H’ C C' G G’ I’ Range Range of P1 A of P1’ A’ Modular Architecture B D’ D B’ E’ E F ’ Associated Researchers Harith Alani Yannis Kalfoglou Leslie Carr Yaozhong (David) Liang Richard Crowder Duncan McRae-Spencer Srinandan Dasmahapatra Kieron O'Hara David Dupplaw Monica Schraefel Nick Gibbins Nigel Shadbolt Hugh Glaser Paul Smart Advanced Knowledge Technologies Steve Harris Mischa Tuffield Chia-Chih Hsu Gary Wills Bo Hu