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Noise estimation in cardiac x-ray imaging: a machine vision approach
Kengyelics, S.M. Gislason-Lee, Amber J. Keeble, C. Magee, D.R. Davies, A.G.
Kengyelics, S.M.
Gislason-Lee, Amber J.
Keeble, C.
Magee, D.R.
Davies, A.G.
Publication Date
2016-12-16
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Rights
(c) 2016 IOP Publishing. This is an author-created, un-copyedited version of an article accepted for publication/published
in Biomedical Physics & Engineering Express. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at https://doi.org/10.1088/2057-1976/2/6/065014.
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Yes
Open Access status
openAccess
Accepted for publication
2016-11-28
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Abstract
We propose a method to automatically parameterize noise in cardiac x-ray image
sequences. The aim was to provide context-sensitive imaging information for
use in regulating dose control feedback systems that relates to the experience
of human observers. The algorithm locates and measures noise contained in
areas of approximately equal signal level. A single noise metric is derived from
the dominant noise components based on their magnitude and spatial location
in relation to clinically relevant structures. The output of the algorithm was
compared to noise and clinical acceptability ratings from 28 observers viewing
40 different cardiac x-ray imaging sequences. Results show good agreement and
that the algorithm has the potential to augment existing control strategies to
deliver x-ray dose to the patient on an individual basis.
Version
Accepted manuscript
Citation
Kengyelics SM, Gislason-Lee AJ, Keeble C et al (2016) Noise estimation in cardiac x-ray imaging: a machine vision approach. Biomedical Physics & Engineering Express. 2(6): 065014.
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Article