Extraction of cardiac and respiratory motion information from cardiac X-ray fluoroscopy images using hierarchical manifold learning

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Panayiotou, Maria, King, Andrew P., Bhatia, Kanwal K., Housden, R. James, Ma, YingLiang, 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

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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:	http://www.scopus.com/inward/record.url?...
Depositing User:	LivePure Connector
Date Deposited:	04 Jan 2023 17:30
Last Modified:	06 Feb 2025 13:46
URI:	https://ueaeprints.uea.ac.uk/id/eprint/90385
DOI:	10.1007/978-3-642-54268-8_15

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