OFELIA: Optical Flow-based Electrode LocalIzAtion

Xinyi Wang, Zikang Xu, Qingsong Yao, Yiyong Sun, S Kevin Zhou

Keywords: Catheter Tracking, Video Landmark Detection, Optical Flow

Abstract:

Catheter ablation is one of the most common cardiac ablation procedures for atrial fibrillation, which is mainly based on catheters with electrodes collecting electrophysiology signals.
Catheter electrode localization facilitates intraoperative catheter positioning, surgical planning, and other applications such as 3D model reconstruction.
In this paper, we propose a novel deep network for automatic electrode localization in an X-ray sequence, which integrates spatiotemporal features between adjacent frames, aided by optical flow maps.
To improve the utility and robustness of the proposed method, we first design a saturation-based optical flow dataset construction pipeline, then finetune the optical flow estimation to obtain more realistic and contrasting optical flow maps for electrode localization.
The extensive results on clinical-challenging test sequences reveal the effectiveness of our method, with a mean radial error (MRE) of 0.95 mm for radiofrequency catheters and an MRE of 0.71 mm for coronary sinus catheters, outperforming several state-of-the-art landmark detection methods.

Submission Number: 85