Stamatia Giannarou
Papers
26
Total Citations
830
H-Index
12
About
Stamatia Giannarou is a leading researcher at the intersection of computer vision, machine learning, and surgical robotics, with her work fundamentally advancing the capabilities of intelligent and autonomous surgical systems. Based at Imperial College London, her research spans surgical navigation, soft tissue tracking, robotic assistance, and AI-driven decision support in minimally invasive and robotic surgery. Giannarou's most influential contribution — a comprehensive survey on machine learning in surgical robotics (238 citations) — helped define the landscape of intelligent surgical systems for an entire generation of researchers. Her early work on affine-invariant feature detection and probabilistic tissue tracking addressed a critical challenge in surgical navigation: the unreliable behaviour of conventional computer vision techniques in dynamic, deformable surgical environments. She has also pioneered innovative medical devices, including MAMMOBOT, a miniature steerable soft robot designed for early breast cancer detection through mammary duct navigation. Her research extends into ethical dimensions of AI in surgical training, synthetic dataset generation tools like VisionBlender, and context-aware neurosurgical decision support. With over 700 cumulative citations across her most recognized works, Giannarou's contributions have meaningfully shaped how autonomous systems perceive, learn, and act within the complex realities of the operating theatre.
Research Focus
Key Achievements
Top Papers
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- 2Probabilistic Tracking of Affine-Invariant Anisotropic Regions90 citations · 2012
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- 10SurgT challenge: Benchmark of soft-tissue trackers for robotic surgery23 citations · 2023