Panayiotou, Maria, King, Andrew P., Bhatia, Kanwal K., Housden, R. James, Ma, YingLiang ORCID: https://orcid.org/0000-0001-5770-5843, Rinaldi, C. Aldo, Gill, Jas, Cooklin, Michael, O'Neill, Mark and Rhode, Kawal S. (2014) Extraction of cardiac and respiratory motion information from cardiac X-ray fluoroscopy images using hierarchical manifold learning. In: Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges. Lecture Notes in Computer Science . Springer, 126–134. ISBN 978-3-642-54267-1
Full text not available from this repository. (Request a copy)Abstract
We present a novel and clinically useful method to automatically determine the regions that carry cardiac and respiratory motion information directly from standard mono-plane X-ray fluoroscopy images. We demonstrate the application of our method for the purposes of retrospective cardiac and respiratory gating of X-ray images. Validation is performed on five mono-plane imaging sequences comprising a total of 284 frames from five patients undergoing radiofrequency ablation for the treatment of atrial fibrillation. We established end-inspiration, end-expiration and systolic gating with success rates of 100%, 100% and 95.3%, respectively. This technique is useful for retrospective gating of X-ray images and, unlike many previously proposed techniques, does not require specific catheters to be visible and works without any knowledge of catheter geometry.
Item Type: | Book Section |
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Faculty \ School: | Faculty of Science > School of Computing Sciences |
UEA Research Groups: | Faculty of Science > Research Groups > Norwich Epidemiology Centre Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre |
Related URLs: | |
Depositing User: | LivePure Connector |
Date Deposited: | 04 Jan 2023 17:30 |
Last Modified: | 19 May 2023 09:42 |
URI: | https://ueaeprints.uea.ac.uk/id/eprint/90385 |
DOI: | 10.1007/978-3-642-54268-8_15 |
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