Hybrid imaging systems, consisting of fluoroscopy and echocardiography, are increasingly selected for intra-operative support of minimally invasive cardiac interventions. Intracardiac Echocardiograpy (ICE) is an emerging modality with the promise of removing sedation or general anesthesia associated with Trans-esophageal Echocardiography (TEE). We introduce a novel 6 DoF pose estimation approach for catheters (equipped with radiopaque ball markers) in single Fluoroscopy projection and investigate the method's application to a prototype ICE catheter. Machine learning based catheter detection is implemented in a Bayesian hypothesis fusion framework, followed by refinement of ball marker locations through template matching. Marker correspondence and 3D pose estimation are solved building upon POSIT. The method registers the ICE catheter and volume to the C-arm coordinate system. Experiments are performed on synthetic and porcine \textitin-vivo data. Target registration error (TRE), defined at the center of echo cone is the basis of our preliminary evaluation. The method reached 8.06+-7.2~ mm TRE on 703 cases.     «

Hybrid imaging systems, consisting of fluoroscopy and echocardiography, are increasingly selected for intra-operative support of minimally invasive cardiac interventions. Intracardiac Echocardiograpy (ICE) is an emerging modality with the promise of removing sedation or general anesthesia associated with Trans-esophageal Echocardiography (TEE). We introduce a novel 6 DoF pose estimation approach for catheters (equipped with radiopaque ball markers) in single Fluoroscopy projection and investiga...     »