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{Donder:2022:10.1109/TRO.2021.3125853,
author = {Donder, A and Rodriguez, y Baena F},
doi = {10.1109/TRO.2021.3125853},
journal = {IEEE Transactions on Robotics},
pages = {2262--2275},
title = {Kalman filter-based, dynamic 3-D shape reconstruction for steerable needles with fiber bragg gratings in multi-core fibers},
url = {http://dx.doi.org/10.1109/TRO.2021.3125853},
volume = {38},
year = {2022}
}
TY - JOUR
AB - Steerable needles are a promising technology toprovide safe deployment of tools through complex anatomy inminimally invasive surgery, including tumor-related diagnosesand therapies. For the 3-D localization of these instruments in softtissue, fiber Bragg gratings (FBGs)-based reconstruction methodshave gained in popularity because of the inherent advantages ofoptical fibers in a clinical setting, such as flexibility, immunity toelectromagnetic interference, non-toxicity, the absence of line ofsight issues. However, methods proposed thus far focus on shapereconstruction of the steerable needle itself, where accuracy issusceptible to errors in interpolation and curve fitting methodsused to estimate the curvature vectors along the needle. In thisstudy, we propose reconstructing the shape of the path createdby the steerable needle tip based on the follow-the-leader natureof many of its variants. By assuming that the path made by thetip is equivalent to the shape of the needle, this novel approachpaves the way for shape reconstruction through a single set ofFBGs at the needle tip, which provides curvature informationabout every section of the path during navigation. We proposea Kalman Filter-based sensor fusion method to update thecurvature information about the sections as they are continuallyestimated during the insertion process. The proposed methodis validated through simulation, in vitro and ex vivo experimentsemploying a programmable bevel-tip steerable needle (PBN). Theresults show clinically acceptable accuracy, with 2.87 mm meanPBN tip position error, and a standard deviation of 1.63 mm fora 120 mm 3-D insertion.
AU - Donder,A
AU - Rodriguez,y Baena F
DO - 10.1109/TRO.2021.3125853
EP - 2275
PY - 2022///
SN - 1552-3098
SP - 2262
TI - Kalman filter-based, dynamic 3-D shape reconstruction for steerable needles with fiber bragg gratings in multi-core fibers
T2 - IEEE Transactions on Robotics
UR - http://dx.doi.org/10.1109/TRO.2021.3125853
UR - https://ieeexplore.ieee.org/abstract/document/9643420
UR - http://hdl.handle.net/10044/1/92605
VL - 38
ER -
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