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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
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 |
|---|---|
| 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 Faculty of Science > Research Groups > Data Science and AI |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 04 Jan 2023 17:30 |
| Last Modified: | 18 Jun 2026 22:11 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/90385 |
| DOI: | 10.1007/978-3-642-54268-8_15 |
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