Imitation Learning for Path Planning in Cardiac Percutaneous Interventions.
Journal:
IEEE transactions on bio-medical engineering
Published Date:
Aug 1, 2025
Abstract
OBJECTIVE: Mitral regurgitation is a valvular heart disease particularly affecting the aging population. Minimally invasive transcatheter procedures offer benefits over traditional open-chest surgery but require significant operator skill and hand-eye coordination, making the learning curve steeper and limiting accessibility. To address these challenges, there is growing research interest in automating these procedures, making it crucial to define safe navigable routes within anatomical structures for robotic operation. This study introduces a tailored learning-based framework for path planning in cardiac percutaneous interventions, specifically adapted to the dynamically constrained and safety-critical environment of mitral valve repair.
