In this section

Mechatronics in Medicine

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

Head of Group

B415C Bessemer Building
South Kensington Campus

+44 (0)20 7594 7046

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.

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 Assistant

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{Rodriguez:2013:10.1177/0954411913500948,
author = {Rodriguez, Y Baena F and Hawke, T and Jakopec, M},
doi = {10.1177/0954411913500948},
journal = {Proc Inst Mech Eng H},
pages = {1135--1144},
title = {A bounded iterative closest point method for minimally invasive registration of the femur.},
url = {http://dx.doi.org/10.1177/0954411913500948},
volume = {227},
year = {2013}
}

Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - This article describes a novel method for image-based, minimally invasive registration of the femur, for application to computer-assisted unicompartmental knee arthroplasty. The method is adapted from the well-known iterative closest point algorithm. By utilising an estimate of the hip centre on both the preoperative model and intraoperative patient anatomy, the proposed 'bounded' iterative closest point algorithm robustly produces accurate varus-valgus and anterior-posterior femoral alignment with minimal distal access requirements. Similar to the original iterative closest point implementation, the bounded iterative closest point algorithm converges monotonically to the closest minimum, and the presented case includes a common method for global minimum identification. The bounded iterative closest point method has shown to have exceptional resistance to noise during feature acquisition through simulations and in vitro plastic bone trials, where its performance is compared to a standard form of the iterative closest point algorithm.
AU  - Rodriguez,Y Baena F
AU  - Hawke,T
AU  - Jakopec,M
DO  - 10.1177/0954411913500948
EP  - 1144
PY  - 2013///
SP  - 1135
TI  - A bounded iterative closest point method for minimally invasive registration of the femur.
T2  - Proc Inst Mech Eng H
UR  - http://dx.doi.org/10.1177/0954411913500948
UR  - http://www.ncbi.nlm.nih.gov/pubmed/23959859
UR  - http://hdl.handle.net/10044/1/14202
VL  - 227
ER  -