Robotic Ultrasound

Robotic ultrasound (RUS) aims to improve the accuracy, consistency, and accessibility of ultrasound imaging by automating probe manipulation and image acquisition. Current research focuses on developing advanced control algorithms (e.g., Bayesian optimization, reinforcement learning) and integrating deep learning models (e.g., GANs, UNets) for tasks such as image segmentation, registration, and autonomous navigation. This technology holds significant promise for improving diagnostic accuracy, reducing operator dependence, and expanding access to ultrasound, particularly in underserved areas or for procedures requiring high precision and repeatability.