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dc.contributor.authorKengyelics, S.M.*
dc.contributor.authorGislason-Lee, Amber J.*
dc.contributor.authorKeeble, C.*
dc.contributor.authorMagee, D.R.*
dc.contributor.authorDavies, A.G.*
dc.date.accessioned2019-04-17T10:59:32Z
dc.date.available2019-04-17T10:59:32Z
dc.date.issued2015-09
dc.identifier.citationKengyelics SM, Gislason-Lee AJ, Keeble C et al (2015) Context sensitive cardiac x-ray imaging: a machine vision approach to x-ray dose control. Journal of Electronic Imaging. 24(5): 051002.
dc.identifier.urihttp://hdl.handle.net/10454/16975
dc.descriptionYes
dc.description.abstractModern cardiac x-ray imaging systems regulate their radiation output based on the thickness of the patient to maintain an acceptable signal at the input of the x-ray detector. This approach does not account for the context of the examination or the content of the image displayed. We have developed a machine vision algorithm that detects iodine-filled blood vessels and fits an idealized vessel model with the key parameters of contrast, diameter, and linear attenuation coefficient. The spatio-temporal distribution of the linear attenuation coefficient samples, when appropriately arranged, can be described by a simple linear relationship, despite the complexity of scene information. The algorithm was tested on static anthropomorphic chest phantom images under different radiographic factors and 60 dynamic clinical image sequences. It was found to be robust and sensitive to changes in vessel contrast resulting from variations in system parameters. The machine vision algorithm has the potential of extracting real-time context sensitive information that may be used for augmenting existing dose control strategies.
dc.description.sponsorshipProject PANORAMA, funded by grants from Belgium, Italy, France, the Netherlands, United Kingdom, and the ENIAC Joint Undertaking.
dc.language.isoenen
dc.rights(c) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited.
dc.subjectCardiac
dc.subjectX-ray
dc.subjectContrast
dc.subjectMachine vision
dc.titleContext sensitive cardiac x-ray imaging: a machine vision approach to x-ray dose control
dc.status.refereedYes
dc.date.Accepted2015-08-18
dc.date.application2015-09-21
dc.typeArticle
dc.type.versionPublished version
dc.identifier.doihttps://doi.org/10.1117/1.JEI.24.5.051002
dc.rights.licenseUnspecified
refterms.dateFOA2019-04-17T10:59:32Z
dc.openaccess.statusopenAccess


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