2020/09/12 by Youngho Kim, Jarrod A. Collins, Kim, Young-Ho +11 · 1 citation
Engineering · Medicine · #Artificial Intelligence (cs.AI) #Cardiac Valve Diseases and Treatments #FOS: Computer and information sciences #Machine Learning (cs.LG) #Robot Manipulation and Learning #Robotics (cs.RO) #Soft Robotics and Applications
paper · pdf · doi:10.48550/arxiv.2009.05859
openalex publication_date 2020/09/12 · openalex created_date 2020/09/21 · openalex updated_date 2026/07/28
Intra-cardiac Echocardiography (ICE) is a powerful imaging modality for guiding electrophysiology and structural heart interventions. ICE provides real-time observation of anatomy, catheters, and emergent complications. However, this increased reliance on intraprocedural imaging creates a high cognitive demand on physicians who can often serve as interventionalist and imager. We present a robotic manipulator for ICE catheters to assist physicians with imaging and serve as a platform for developing processes for procedural automation. Herein, we introduce two application modules towards these goals: (1) a view recovery process that allows physicians to save views during intervention and automatically return with the push of a button and (2) a data-driven approach to compensate kinematic model errors that result from non-linear behaviors in catheter bending, providing more precise control of the catheter tip. View recovery is validated by repeated catheter positioning in cardiac phantom and animal experiments with position- and image-based analysis. We present a simplified calibration approach for error compensation and verify with complex rotation of the catheter in benchtop and phantom experiments under varying realistic curvature conditions. Results support that a robotic manipulator for ICE can provide an efficient and reproducible tool, potentially reducing execution time and promoting greater utilization of ICE imaging.