Laparoscopic Robotic Surgery

To develop an image-guided laparoscopic robotic surgery system.
Description of the Project: 

Robotic surgery typically employs minimally invasive keyhole laparoscopic techniques. This is safer for the patient and leads to reduced recovery time.

In laparoscopic surgery surgeons have to use a camera to see what is happening and guide their actions, whilst in open surgery the surgeon has an unrestricted view of the site of the surgery. Furthermore, manipulating the surgical instruments is also undertaken in an indirect fashion. As a result there is a steep and lengthy learning curve for the surgeon in laparoscopic surgery.

Improvements in modern imaging systems, coupled with the fine motor control of robotics mean that with a system like the da Vinci robot the learning time required for the human surgeon can be substantially reduced.

This PhD research will seek to develop and image-guided laparoscopic robotic surgery system.

Project number: 
123405
First Supervisor: 
University: 
Heriot-Watt University
First supervisor university: 
Heriot-Watt University
Essential skills and knowledge: 
Image processing; Machine learning
Desirable skills and knowledge: 
Programming and ROS
References: 

[1] P. Britt, 2018, ‘How AI-Assisted Surgery Is Improving Surgical Outcomes’. Robotics Business Review. https://www.roboticsbusinessreview.com/health- medical/ai- assisted- surgery- improves-patient-outcomes/

[2] M. Kroh and S. Chalikonda. 2015, ‘Essentials of robotic surgery’. pp. 1-218. ISBN 9783319095646.

[3] D. Sarikaya, J. J. Corso, and K. A. Guru, 2017, ‘Detection and Localization of Robotic Tools in Robot-Assisted Surgery Videos Using Deep Neural Networks for Region Proposal and Detection’. IEEE Transactions on Medical Imaging, 36 (7), pp. 1542-1549.