Catheter Path

Catheter path research focuses on improving the accuracy, efficiency, and automation of catheter navigation during various medical procedures, primarily aiming to reduce procedure time, radiation exposure, and invasiveness. Current research employs deep learning models, including encoder-decoder networks and transformer-based architectures, along with reinforcement learning and dynamic time warping algorithms, to achieve precise catheter tracking, automated registration, and even autonomous navigation. These advancements have significant implications for minimally invasive cardiovascular interventions, improving patient outcomes and potentially transforming clinical workflows.