Clinical cardiac electrophysiology (EP) is concerned with diagnosis and treatment of cardiac arrhythmia describing abnormality or perturbation in the normal activation sequence of the myocardium. With the recent introduction of lowest dose X-ray imaging protocol for EP procedures, interventional image enhancement has gained crucial importance for the well-being of patients as well as medical staff.
In this paper, we introduce a novel method to detect and track different EP catheter electrodes in lowest dose fluoroscopic sequences based on \(\ell _1\)-sparse coding and online robust PCA (ORPCA). Besides being able to work on real lowest dose sequences, the underlying methodology achieves simultaneous detection and tracking of three main EP catheters used during ablation procedures.
We have validated our algorithm on 16 lowest dose fluoroscopic sequences acquired during real cardiac ablation procedures. In addition to expert labels for 2 sequences, we have employed a crowdsourcing strategy to obtain ground truth labels for the remaining 14 sequences. In order to validate the effect of different training data, we have employed a leave-one-out cross-validation scheme yielding an average detection rate of \(86.9\%\).
Besides these promising quantitative results, our medical partners also expressed their high satisfaction. Being based on \(\ell _1\)-sparse coding and online robust PCA (ORPCA), our method advances previous approaches by being able to detect and track electrodes attached to multiple different catheters.
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Conflict of interest
The authors declare that they have no conflict of interest
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. For this type of study formal consent is not required. This article does not contain any studies with animals performed by any of the authors.
Informed consent was obtained from all individual participants included in the study.
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Bui, M., Bourier, F., Baur, C. et al. Robust navigation support in lowest dose image setting. Int J CARS 14, 291–300 (2019). https://doi.org/10.1007/s11548-018-1874-8
- Computer-assisted electrophysiology
- Electrode tracking
- Sparse coding
- Online robust PCA
- Online tracking