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Quantitative Computed Tomography and image analysis for advanced muscle assessment

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dc.contributor Háskólinn í Reykjavík
dc.contributor Reykjavik University
dc.contributor.author Árnadóttir, Íris Dröfn
dc.contributor.author Piccione, Francesco
dc.contributor.author Gargiulo, Paolo
dc.contributor.author Edmunds, Kyle
dc.contributor.author Magnús Gíslason
dc.contributor.author Marcante, Andrea
dc.date.accessioned 2018-11-26T11:17:20Z
dc.date.available 2018-11-26T11:17:20Z
dc.date.issued 2016
dc.identifier.citation Edmunds, K. J., Gislason, M. K., Arnadottir, I. D., Marcante, A., Piccione, F., & Gargiulo, P. (2016). Quantitative Computed Tomography and image analysis for advanced muscle assessment. European Journal of Translational Myology, 26(2), 93–100
dc.identifier.issn 2037-7452
dc.identifier.issn 2037-7460 (eISSN)
dc.identifier.uri https://hdl.handle.net/20.500.11815/920
dc.description.abstract Medical imaging is of particular interest in the field of translational myology, as extant literature describes the utilization of a wide variety of techniques to non-invasively recapitulate and quantity various internal and external tissue morphologies. In the clinical context, medical imaging remains a vital tool for diagnostics and investigative assessment. This review outlines the results from several investigations on the use of computed tomography (CT) and image analysis techniques to assess muscle conditions and degenerative process due to aging or pathological conditions. Herein, we detail the acquisition of spiral CT images and the use of advanced image analysis tools to characterize muscles in 2D and 3D. Results from these studies recapitulate changes in tissue composition within muscles, as visualized by the association of tissue types to specified Hounsfield Unit (HU) values for fat, loose connective tissue or atrophic muscle, and normal muscle, including fascia and tendon. We show how results from these analyses can be presented as both average HU values and compositions with respect to total muscle volumes, demonstrating the reliability of these tools to monitor, assess and characterize muscle degeneration.
dc.description.sponsorship This research has been supported by the University Hospital Landspitali Scientific fund.
dc.format.extent 93-100
dc.language.iso en
dc.publisher Pagepress Publ, Meditgroup
dc.relation.ispartofseries European Journal of Translational Myology;26(2)
dc.rights info:eu-repo/semantics/openAccess
dc.subject Quantitative computed tomography
dc.subject Image analysis
dc.subject Advanced muscle assessment
dc.subject Sneiðmyndatökur
dc.subject Myndgreining (læknisfræði)
dc.subject Vöðvar
dc.title Quantitative Computed Tomography and image analysis for advanced muscle assessment
dc.type info:eu-repo/semantics/article
dcterms.license This article is distributed under the terms of the Creative Commons Attribution Noncommercial License (CC BY-NC 4.0) which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
dc.description.version Peer reviewed
dc.identifier.journal European Journal of Translational Myology
dc.identifier.doi 10.4081/ejtm.2016.6015
dc.contributor.department Institute of Biomedical and Neural Engineering (IBNE) (RU)
dc.contributor.school Tækni- og verkfræðideild (HR)
dc.contributor.school School of Science and Engineering (RU)


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