The Cognitive Vision in Robotic Surgery Lab is developing computer vision and AI techniques for intraoperative navigation and real-time tissue characterisation.
Head of Group
Dr Stamatia (Matina) Giannarou
411 Bessemer Building
South Kensington Campus
+44 (0) 20 7594 8904
What we do
Surgery is undergoing rapid changes driven by recent technological advances and our on-going pursuit towards early intervention and personalised treatment. We are developing computer vision and Artificial Intelligence techniques for intraoperative navigation and real-time tissue characterisation during minimally invasive and robot-assisted operations to improve both the efficacy and safety of surgical procedures. Our work will revolutionize the treatment of cancers and pave the way for autonomous robot-assisted interventions.
Why it is important?
With recent advances in medical imaging, sensing, and robotics, surgical oncology is entering a new era of early intervention, personalised treatment, and faster patient recovery. The main goal is to completely remove cancerous tissue while minimising damage to surrounding areas. However, achieving this can be challenging, often leading to imprecise surgeries, high re-excision rates, and reduced quality of life due to unintended injuries. Therefore, technologies that enhance cancer detection and enable more precise surgeries may improve patient outcomes.
How can it benefit patients?
Our methods aim to ensure patients receive accurate and timely surgical treatment while reducing surgeons' mental workload, overcoming limitations, and minimizing errors. By improving tumor excision, our hybrid diagnostic and therapeutic tools will lower recurrence rates and enhance survival outcomes. More complete tumor removal will also reduce the need for repeat procedures, improving patient quality of life, life expectancy, and benefiting society and the economy.
Meet the team
Results
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Conference paperMountney P, Giannarou S, Elson D, et al., 2009,
Optical Biopsy Mapping for Minimally Invasive Cancer Screening
, Pages: 483-490 -
Conference paperGiannarou S, Stathaki T, 2007,
Object Identification in Complex Scenes using Shape Context Descriptors and Multi-Stage Clustering
, Pages: 244-247 -
Conference paperGiannarou S, Stathaki T, 2007,
Shape Signature Matching for Object Identification Invariant to Image Transformations and Occlusion
, Pages: 710-717 -
Conference paperGiannarou S, Stathaki T, 2006,
Novel Statistical Approaches to the Quantitative Combination of Multiple Edge Detectors
, Pages: 184-195 -
Conference paperGiannarou S, Stathaki T, 2005,
Edge detection using quantitative combination of multiple operators
, Pages: 359-364
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Contact Us
The Hamlyn Centre
Bessemer Building
South Kensington Campus
Imperial College
London, SW7 2AZ
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