Angelos Karlas
Papers
4
Total Citations
81
H-Index
3
About
Angelos Karlas is a leading researcher at the intersection of robotics, medical imaging, and artificial intelligence, with a primary focus on advancing autonomous and robot-assisted ultrasound systems. His major contributions lie in developing intelligent frameworks that bridge the gap between simulation and real-world clinical application. Notably, his most cited work, "VesNet-RL" (2022, 53 citations), pioneered the use of simulation-based reinforcement learning for autonomous ultrasound probe navigation, enabling reproducible and stable acquisition of standard examination planes. Karlas has also made significant strides in interventional robotics, including the design of virtual fixture systems for robot-assisted Deep Venous Thrombosis examinations (2024, 15 citations) and the application of Generative Adversarial Networks (GANs) for restoring thin instrument visibility during needle segmentation in robotic ultrasound (2024, 12 citations). His recent work on the Intelligent Virtual Sonographer (IVS) framework (2025) further demonstrates his commitment to enhancing physician-robot-patient communication. Through these innovations, Karlas is shaping the future of autonomous point-of-care ultrasound, improving both diagnostic accuracy and procedural safety.
Research Focus
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Top Papers
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