title: Detection of electrophysiology catheters in noisy fluoroscopy images.
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.
authors.affiliation: Technische Universiteit Eindhoven, Department of Biomedical Engineering, P.O. Box 513, 5600 MB Eindhoven, The Netherlands. E.M.Franken@tue.nl
authors.forename: Erik
authors.initials: E
authors.lastname: Franken
authors.forename: Peter
authors.initials: P
authors.lastname: Rongen
authors.forename: Markus
authors.initials: M
authors.lastname: van Almsick
authors.forename: Bart
authors.initials: B
authors.lastname: ter Haar Romeny
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D006328:Cardiac Catheterization / Q000295:instrumentation* / Q000379:methods; D017115:Catheter Ablation / Q000295:instrumentation* / Q000379:methods; D022062:Electrophysiologic Techniques, Cardiac / Q000295:instrumentation* / Q000379:methods; D005471:Fluoroscopy / Q000379:methods*; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D025321:Surgery, Computer-Assisted / Q000379:methods*