In this section
The MIM Lab develops robotic and mechatronics surgical systems for a variety of procedures.
Twitter/X: @MIMLab_Robotics
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The Mechatronics in Medicine Laboratory develops robotic and mechatronics surgical systems for a variety of procedures including neuro, cardiovascular, orthopaedic surgeries, and colonoscopies. Examples include bio-inspired catheters that can navigate along complex paths within the brain (such as EDEN2020), soft robots to explore endoluminal anatomies (such as the colon), and virtual reality solutions to support surgeons during knee replacement surgeries.
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Mr Ayhan Aktas
Casual - Student demonstrator - lower rate
Dr Daniel Bautista Salinas
Research Associate
Dr Kaiwen Chen
Research Associate
Mr Zejian Cui
Research Postgraduate
Mr Connor Daly
Research Postgraduate
Emeritus Professor Brian L Davies FREng
Emeritus Professor
Mr Zhaoyang Jacopo Hu
Research Postgraduate
Dr Hisham M Iqbal
Research Associate
Mr Alex Ranne
Research Postgraduate
Professor Ferdinando M Rodriguez y Baena
Co-Director of Hamlyn Centre, Professor of Medical Robotics
Dr Jialei Shi
Research Associate
Mr Spyridon Souipas
Casual - Other work
Ms Emilia Zari
Research Postgraduate
@article{Hu:2021:10.1109/ACCESS.2021.3075628,
author = {Hu, X and Liu, H and Rodriguez, y Baena FM},
doi = {10.1109/ACCESS.2021.3075628},
journal = {IEEE Access},
pages = {64708--64718},
title = {Markerless navigation system for orthopaedic knee surgery: a proof of concept study},
url = {http://dx.doi.org/10.1109/ACCESS.2021.3075628},
volume = {9},
year = {2021}
}
TY - JOUR
AB - Current computer-assisted surgical navigation systems mainly rely on optical markers screwed into the bone for anatomy tracking. The insertion of these percutaneous markers increases operating complexity and causes additional harm to the patient. A markerless tracking and registration algorithm has recently been proposed to avoid anatomical markers for knee surgery. The femur points were directly segmented from the recorded RGBD scene by a neural network and then registered to a pre-scanned femur model for the real-time pose. However, in a practical setup such a method can produce unreliable registration results, especially in rotation. Furthermore, its potential application in surgical navigation has not been demonstrated. In this paper, we first improved markerless registration accuracy by adopting a bounded-ICP (BICP) technique, where an estimate of the remote hip centre, acquired also in a markerless way, was employed to constrain distal femur alignment. Then, a proof-of-concept markerless navigation system was proposed to assist in typical knee drilling tasks. Two example setups for global anchoring were proposed and tested on a phantom leg. Our BICP-based markerless tracking and registration method has better angular accuracy and stability than the original method, bringing our straightforward, less invasive markerless navigation approach one step closer to clinical application. According to user tests, our proposed optically anchored navigation system achieves comparable accuracy with the state-of-the-art (3.64± 1.49 mm in position and 2.13±0.81° in orientation). Conversely, our visually anchored, optical tracker-free setup has a lower accuracy (5.86± 1.63 mm in position and 4.18±1.44° in orientation), but is more cost-effective and flexible in the operating room.
AU - Hu,X
AU - Liu,H
AU - Rodriguez,y Baena FM
DO - 10.1109/ACCESS.2021.3075628
EP - 64718
PY - 2021///
SN - 2169-3536
SP - 64708
TI - Markerless navigation system for orthopaedic knee surgery: a proof of concept study
T2 - IEEE Access
UR - http://dx.doi.org/10.1109/ACCESS.2021.3075628
UR - https://ieeexplore.ieee.org/document/9416444
UR - http://hdl.handle.net/10044/1/89479
VL - 9
ER -
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