In this section

Mechatronics in Medicine

Head of Group

Prof Ferdinando Rodriguez y Baena

B415C Bessemer Building

South Kensington Campus

About us

The MIM Lab develops robotic and mechatronics surgical systems for a variety of procedures.

Twitter/X: @MIMLab_Robotics
Youtube: Mechatronics in Medicine Lab

What we do

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.

Why it is important?

...

How can it benefit patients?

......

Meet the team

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

Citation

BibTex format

@article{Hu:2024:10.1109/TAI.2024.3429048,
author = {Hu, X and Cutolo, F and Iqbal, H and Henckel, J and Rodriguez, y Baena F},
doi = {10.1109/TAI.2024.3429048},
journal = {IEEE Transactions on Artificial Intelligence},
title = {Artificial Intelligence-driven Framework for Augmented Reality Markerless Navigation in Knee Surgery},
url = {http://dx.doi.org/10.1109/TAI.2024.3429048},
year = {2024}
}

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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Conventional orthopaedic navigation systems depend on marker-based tracking, which may introduce additional skin incisions, increase the risk and discomfort for the patient, and entail increased workflow complexity. The guidance is conveyed via 2D monitors, which may distract the surgeon and increase the cognitive burden.</p> <p>This study presents an Artificial Intelligence (AI) - driven surgical navigation framework for knee replacement surgery. The system comprises an Augmented Reality (AR) interface that combines an occlusions-robust deep learning-based markerless bone tracking and registration algorithm with a commercial HoloLens 2 headset calibrated for the user’s perspective on both eyes. The feasibility of such a system in navigating a bone drilling task is investigated with an experienced orthopaedic surgeon on three cadaveric knees under realistic operating room conditions. After registering an implant model to computed tomography (CT) scans, the preoperative plans are determined based on the location of the fixation pins. Navigation accuracy is quantified using a highly accurate optical tracking system.</p> <p>The achieved drilling error is 7.88±2.41mm in translation and 7.36±1.77° in orientation. The results demonstrate the viability of integrating AI and AR technology to navigate knee surgery.
AU  - Hu,X
AU  - Cutolo,F
AU  - Iqbal,H
AU  - Henckel,J
AU  - Rodriguez,y Baena F
DO  - 10.1109/TAI.2024.3429048
PY  - 2024///
TI  - Artificial Intelligence-driven Framework for Augmented Reality Markerless Navigation in Knee Surgery
T2  - IEEE Transactions on Artificial Intelligence
UR  - http://dx.doi.org/10.1109/TAI.2024.3429048
ER  -

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