Detection of electrophysiology catheters in noisy fluoroscopy images

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Abstract

Cardiac catheter ablation is a minimally invasive medical procedure to treat patients with heart rhythm disorders. It is useful to know the positions of the catheters and electrodes during the intervention, e.g. for the automatization of cardiac mapping. Our goal is therefore to develop a robust image analysis method that can detect the catheters in X-ray fluoroscopy images. Our method uses steerable tensor voting in combination with a catheter-specific multi-step extraction algorithm. The evaluation on clinical fluoroscopy images shows that especially the extraction of the catheter tip is successful and that the use of tensor voting accounts for a large increase in performance. © Springer-Verlag Berlin Heidelberg 2006.

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Franken, E., Rongen, P., Van Almsick, M., & Ter Haar Romeny, B. (2006). Detection of electrophysiology catheters in noisy fluoroscopy images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4191 LNCS-II, pp. 25–32). Springer Verlag. https://doi.org/10.1007/11866763_4

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