Literature DB >> 9865038

The SNOMED DICOM microglossary: controlled terminology resource for data interchange in biomedical imaging.

W D Bidgood1.   

Abstract

This paper describes an authoritative, non-proprietary information resource that provides an efficient mechanism for embedding specialized clinical knowledge into the design of healthcare telecommunications systems. The resource marries two types of data interchange standards, a message/electronic-document standard and a terminology standard. In technical terms, it is part protocol and part database. Industry, academia, professional specialty societies, and the federal government participated in its development. The development of multi-specialty content has broadly engaged biomedical domain experts to an unprecedented degree in voluntary, non-proprietary message/document-standards development. The resource is the SNOMED DICOM Microglossary (SDM), a message-terminology (or document-content) mapping resource. The message/electronic-document standard is DICOM (Digital Imaging and Communications in Medicine). The terminology standard is SNOMED, (Systematized Nomenclature of Human and Veterinary Medicine). The SDM specifies the mapping of multi-specialty imaging terminology from SNOMED to DICOM data elements. DICOM provides semantic constraints and a framework for discourse that are lacking in SNOMED. Thus the message standard and the computer-based terminology both depend upon and complete each other. The combination is synergistic. By substitution of different templates of specialty terminology from the SDM, a generic message template, such as the DICOM Visible Light (Color Diagnostic) Image or the DICOM Structured Reporting specification can be reconfigured for diverse applications. Professional societies, with technical assistance from the College of American Pathologists, contribute and maintain their portions of the terminology, and can use SDM templates and term lists in clinical practice guidelines for the structure and content of computer-based patient records.

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Year:  1998        PMID: 9865038

Source DB:  PubMed          Journal:  Methods Inf Med        ISSN: 0026-1270            Impact factor:   2.176


  9 in total

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Review 2.  Integration of haemodynamic and electrocardiographic waveform data with DICOM images.

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Journal:  Proc AMIA Symp       Date:  2001

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6.  Image acquisition context: procedure description attributes for clinically relevant indexing and selective retrieval of biomedical images.

Authors:  W D Bidgood; B Bray; N Brown; A R Mori; K A Spackman; A Golichowski; R H Jones; L Korman; B Dove; L Hildebrand; M Berg
Journal:  J Am Med Inform Assoc       Date:  1999 Jan-Feb       Impact factor: 4.497

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8.  Highdicom: a Python Library for Standardized Encoding of Image Annotations and Machine Learning Model Outputs in Pathology and Radiology.

Authors:  Christopher P Bridge; Chris Gorman; Steven Pieper; Sean W Doyle; Jochen K Lennerz; Jayashree Kalpathy-Cramer; David A Clunie; Andriy Y Fedorov; Markus D Herrmann
Journal:  J Digit Imaging       Date:  2022-08-22       Impact factor: 4.903

9.  DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research.

Authors:  Andriy Fedorov; David Clunie; Ethan Ulrich; Christian Bauer; Andreas Wahle; Bartley Brown; Michael Onken; Jörg Riesmeier; Steve Pieper; Ron Kikinis; John Buatti; Reinhard R Beichel
Journal:  PeerJ       Date:  2016-05-24       Impact factor: 2.984

  9 in total

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