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Real-time x-ray fluoroscopy-based catheter detection and tracking for cardiac electrophysiology interventions

Ma, Yingliang; Gogin, Nicolas; Cathier, Pascal; Housden, R. James; Gijsbers, Geert; Cooklin, Michael; O'Neill, Mark; Gill, Jaswinder; Rinaldi, C. Aldo; Razavi, Reza; Rhode, Kawal S.


Yingliang Ma

Nicolas Gogin

Pascal Cathier

R. James Housden

Geert Gijsbers

Michael Cooklin

Mark O'Neill

Jaswinder Gill

C. Aldo Rinaldi

Reza Razavi

Kawal S. Rhode


Purpose: X-ray fluoroscopically guided cardiac electrophysiology (EP) procedures are commonly carried out to treat patients with arrhythmias. X-ray images have poor soft tissue contrast and, for this reason, overlay of a three-dimensional (3D) roadmap derived from preprocedural volumetric images can be used to add anatomical information. It is useful to know the position of the catheter electrodes relative to the cardiac anatomy, for example, to record ablation therapy locations during atrial fibrillation therapy. Also, the electrode positions of the coronary sinus (CS) catheter or lasso catheter can be used for road map motion correction. Methods: In this paper, the authors present a novel unified computational framework for image-based catheter detection and tracking without any user interaction. The proposed framework includes fast blob detection, shape-constrained searching and model-based detection. In addition, catheter tracking methods were designed based on the customized catheter models input from the detection method. Three real-time detection and tracking methods are derived from the computational framework to detect or track the three most common types of catheters in EP procedures: the ablation catheter, the CS catheter, and the lasso catheter. Since the proposed methods use the same blob detection method to extract key information from x-ray images, the ablation, CS, and lasso catheters can be detected and tracked simultaneously in real-time. Results: The catheter detection methods were tested on 105 different clinical fluoroscopy sequences taken from 31 clinical procedures. Two-dimensional (2D) detection errors of 0.50 ± 0.29, 0.92 ± 0.61, and 0.63 ± 0.45 mm as well as success rates of 99.4%, 97.2%, and 88.9% were achieved for the CS catheter, ablation catheter, and lasso catheter, respectively. With the tracking method, accuracies were increased to 0.45 ± 0.28, 0.64 ± 0.37, and 0.53 ± 0.38 mm and success rates increased to 100%, 99.2%, and 96.5% for the CS, ablation, and lasso catheters, respectively. Subjective clinical evaluation by three experienced electrophysiologists showed that the detection and tracking results were clinically acceptable. Conclusions: The proposed detection and tracking methods are automatic and can detect and track CS, ablation, and lasso catheters simultaneously and in real-time. The accuracy of the proposed methods is sub-mm and the methods are robust toward low-dose x-ray fluoroscopic images, which are mainly used during EP procedures to maintain low radiation dose. © 2013 © 2013 Author(s).


Ma, Y., Gogin, N., Cathier, P., Housden, R. J., Gijsbers, G., Cooklin, M., …Rhode, K. S. (2013). Real-time x-ray fluoroscopy-based catheter detection and tracking for cardiac electrophysiology interventions. Medical Physics, 40(7), 071902-1.

Journal Article Type Article
Publication Date Jan 1, 2013
Journal Medical Physics
Print ISSN 0094-2405
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 40
Issue 7
Pages 071902-1
Keywords medical imaging, computer vision, machine vision, X-ray image
Public URL
Publisher URL
Additional Information Corporate Creators : King's College London, Philips Healthcare, St. Thomas Hospital London

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