Reference : Initialisation of Deep Brain Stimulation Parameters with Multi-objective Optimisation...

	Document type :	Parts of books : Contribution to collective works
	Discipline(s) :	Engineering, computing & technology : Multidisciplinary, general & others
	Focus Areas :	Computational Sciences
	To cite this reference:	http://hdl.handle.net/10993/52608

Title :	Initialisation of Deep Brain Stimulation Parameters with Multi-objective Optimisation Using Imaging Data
Language :	English
Author, co-author :	Baniasadi, Mehri [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Systems Control >]
	Husch, Andreas [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Interventional Neuroscience >]
	Proverbio, Daniele [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Systems Control >]
	fernandes arroteia, Isabel [Centre Hospitalier de Luxembourg]
	Hertel, Frank [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > >]
	Goncalves, Jorge [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Systems Control >]
Publication date :	5-Apr-2022
Main document title :	Bildverarbeitung für die Medizin 2022
Publisher :	Springer
Peer reviewed :	Yes
Keywords :	[en] Optimisation ; Deep Brain Stimulation ; Programming
Abstract :	[en] Following the deep brain stimulation (DBS) surgery, the stimulation parameters are manually tuned to reduce symptoms. This procedure can be timeconsuming, especially with directional leads. We propose an automated methodology to initialise contact configurations using imaging techniques. The goal is to maximise the electric field on the target while minimising the spillover, and the electric field on regions of avoidance. By superposing pre-computed electric fields, we solve the optimisation problem in less than a minute, much more efficient compared to finite element methods. Our method offers a robust and rapid solution, and it is expected to considerably reduce the time required for manual parameter tuning.
Funders :	Fonds National de la Recherche - FnR
Permalink :	http://hdl.handle.net/10993/52608
DOI :	10.1007/978-3-658-36932-3_62
Other URL :	https://doi.org/10.1007/978-3-658-36932-3_62
FnR project :	FnR ; FNR12548237 > Mehri Baniasadi > TreCoDBS > Personalised Tremor Control By Advanced Clinical Deep Brain Stimulation. > 01/11/2018 > 31/10/2022 > 2018

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