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Article Dans Une Revue The International Journal of Medical Robotics and Computer Assisted Surgery Année : 2023

A multiple catheter tips tracking method in X‐ray fluoroscopy images by a new lightweight segmentation network and Bayesian filtering

Résumé

Abstract During percutaneous coronary intervention, the guiding catheter plays an important role. Tracking the catheter tip placed at the coronary ostium in the X‐ray fluoroscopy sequence can obtain image displacement information caused by the heart beating, which can help dynamic coronary roadmap overlap on X‐ray fluoroscopy images. Due to a low exposure dose, the X‐ray fluoroscopy is noisy and low contrast, which causes some difficulties in tracking. In this paper, we developed a new catheter tip tracking framework. First, a lightweight efficient catheter tip segmentation network is proposed and boosted by a self‐distillation training mechanism. Then, the Bayesian filtering post‐processing method is used to consider the sequence information to refine the single image segmentation results. By separating the segmentation results into several groups based on connectivity, our framework can track multiple catheter tips. The proposed tracking framework is validated on a clinical X‐ray sequence dataset.
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Dates et versions

hal-04190684 , version 1 (29-08-2023)

Identifiants

Citer

Hui Tang, Hao Kai Li, Chun Feng Yang, Jean‐louis Dillenseger, Gouenou Coatrieux, et al.. A multiple catheter tips tracking method in X‐ray fluoroscopy images by a new lightweight segmentation network and Bayesian filtering. The International Journal of Medical Robotics and Computer Assisted Surgery, 2023, 19 (6), pp.983-991. ⟨10.1002/rcs.2569⟩. ⟨hal-04190684⟩
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