In this section
The Cognitive Vision in Robotic Surgery Lab is developing computer vision and AI techniques for intraoperative navigation and real-time tissue characterisation.
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.
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.
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.
Dr Stamatia Giannarou
Senior Lecturer
Dr Po Wen Lo
Research Associate
Mr Alfie Roddan
Research Postgraduate
Mr Alistair G Weld
Research Postgraduate
Mr Chi Xu
Research Assistant
Mr Haozheng Xu
Research Assistant in Surgical Robot Vision
Mr Yihang Zhou
Research Assistant
@inbook{Tukra:2022:10.1007/978-3-030-64573-1_323,
author = {Tukra, S and Lidströmer, N and Ashrafian, H and Gianarrou, S},
booktitle = {Artificial Intelligence in Medicine},
doi = {10.1007/978-3-030-64573-1_323},
pages = {835--854},
title = {AI in Surgical Robotics},
url = {http://dx.doi.org/10.1007/978-3-030-64573-1_323},
year = {2022}
}
TY - CHAP
AB - The future of surgery is tightly knit with the evolution of artificial intelligence (AI) and its thorough involvement in surgical robotics. Robotics long ago became an integral part of the manufacturing industry. The area of healthcare though adds several more layers of complication. In this chapter we elaborate a broad range of issues to be dealt with when a robotic system enters the surgical theater and interacts with human surgeons - from overcoming the limitations of minimally invasive surgery to the enhancement of performance in open surgery. We present the latest from the fields of cognitive surgical robots, focusing on proprioception, intraoperative decision-making, and, ultimately, autonomy. More specifically, we discuss how AI has advanced the research field of surgical tool tracking, haptic feedback and tissue interaction sensing, advanced intraoperative visualization, robot-assisted task execution, and finally land in the crucial development of context-aware decision support.
AU - Tukra,S
AU - Lidströmer,N
AU - Ashrafian,H
AU - Gianarrou,S
DO - 10.1007/978-3-030-64573-1_323
EP - 854
PY - 2022///
SP - 835
TI - AI in Surgical Robotics
T1 - Artificial Intelligence in Medicine
UR - http://dx.doi.org/10.1007/978-3-030-64573-1_323
ER -
The Hamlyn Centre
Bessemer Building
South Kensington Campus
Imperial College
London, SW7 2AZ
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