Towards expert-level autonomous carotid ultrasonography with large-scale learning-based robotic system.

ABSTRACT: Carotid ultrasound requires skilled operators due to small vessel dimensions and high anatomical variability, exacerbating sonographer shortages and diagnostic inconsistencies. Prior automation attempts, including rule-based approaches with manual heuristics and reinforcement learning trained in simulated environments, demonstrate limited generalizability and fail to complete real-world clinical workflows. Here, we present UltraBot, a fully learning-based autonomous carotid ultrasound robot, achieving human-expert-level performance through four innovations: (1) A unified imitation learning framework for acquiring anatomical knowledge and scanning operational skills; (2) A large-scale expert demonstration dataset (247,000 samples, 100 × scale-up), enabling embodied foundation models with st

SUBMITTER: Jiang H 

PROVIDER: S-EPMC12375115 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature