Christos Bergeles

PEF not only boosts navigation success rates in complex vascular environments but also adapts seamlessly to patient-specific anatomies, paving the way for improved clinical outcomes.

Eversion-based robotic navigation can reduce interaction forces by over 65%, enabling safer access to the spinal subarachnoid space without damaging delicate neural structures.

Real-time, marker-free tracking of surgical robots now achieves near-1 cm accuracy at 30 fps, outpacing traditional methods even in occluded environments.

World models can navigate blood vessels autonomously with higher success rates than standard RL, paving the way for safer robotic stroke treatments.

Standardized testbeds and effectiveness metrics could accelerate the development and validation of AI-assisted robotic thrombectomy, potentially revolutionizing stroke treatment accessibility.