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    Context sensitive cardiac x-ray imaging: a machine vision approach to x-ray dose control

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    Gislason-Lee_Journal_of_Electronic_Imaging.pdf (1.237Mb)
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    Publication date
    2015-09
    Author
    Kengyelics, S.M.
    Gislason-Lee, Amber J.
    Keeble, C.
    Magee, D.R.
    Davies, A.G.
    Keyword
    Cardiac
    X-ray
    Contrast
    Machine vision
    Rights
    Copyright 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.
    Peer-Reviewed
    Yes
    
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    Abstract
    Modern 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.
    URI
    http://hdl.handle.net/10454/16975
    Version
    Published version
    Citation
    Kengyelics 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.
    Link to publisher’s version
    https://doi.org/10.1117/1.JEI.24.5.051002
    Type
    Article
    Collections
    Health Studies Publications

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