Kengyelics, SM, Gislason-Lee, AJ, Keeble, C orcid.org/0000-0003-1633-8842 et al. (2 more authors) (2016) Noise estimation in cardiac x-ray imaging: a machine vision approach. Biomedical Physics and Engineering Express, 2 (6). 065014. ISSN 2057-1976
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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 IOP Publishing Ltd. This is an author-created, un-copyedited version of an article accepted for publication in Biomedical Physics and Engineering Express. The publisher 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. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | x-ray; noise; machine vision; cardiac; imaging |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Genetics, Health and Therapeutics (LIGHT) > Division of Epidemiology & Biostatistics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 20 Dec 2016 10:55 |
Last Modified: | 16 Dec 2017 01:38 |
Published Version: | https://doi.org/10.1088/2057-1976/2/6/065014 |
Status: | Published |
Publisher: | IOP Publishing |
Identification Number: | 10.1088/2057-1976/2/6/065014 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:109693 |