12 citations · 18 across the 4 of their papers we have counts for
4 papers
Toward Safe Autonomous Robotic Endovascular Interventions using World Models
Harry Robertshaw, Nikola Fischer, Han-Ru Wu +6
Autonomous mechanical thrombectomy (MT) presents substantial challenges due to highly variable vascular geometries and the requirements for accurate, real-time control. While reinf…
Toward AI Autonomous Navigation for Mechanical Thrombectomy using Hierarchical Modular Multi-agent Reinforcement Learning (HM-MARL)
Harry Robertshaw, Nikola Fischer, Lennart Karstensen +6
Mechanical thrombectomy (MT) is typically the optimal treatment for acute ischemic stroke involving large vessel occlusions, but access is limited due to geographic and logistical…
World Model for AI Autonomous Navigation in Mechanical Thrombectomy
Harry Robertshaw, Han-Ru Wu, Alejandro Granados +1
Autonomous navigation for mechanical thrombectomy (MT) remains a critical challenge due to the complexity of vascular anatomy and the need for precise, real-time decision-making. R…
Reinforcement Learning for Safe Autonomous Two Device Navigation of Cerebral Vessels in Mechanical Thrombectomy
Harry Robertshaw, Benjamin Jackson, Jiaheng Wang +4
Purpose: Autonomous systems in mechanical thrombectomy (MT) hold promise for reducing procedure times, minimizing radiation exposure, and enhancing patient safety. However, current…