Reference : Initialisation of Deep Brain Stimulation Parameters with Multi-objective Optimisation... |
Parts of books : Contribution to collective works | |||
Engineering, computing & technology : Multidisciplinary, general & others | |||
Computational Sciences | |||
http://hdl.handle.net/10993/52608 | |||
Initialisation of Deep Brain Stimulation Parameters with Multi-objective Optimisation Using Imaging Data | |
English | |
Baniasadi, Mehri ![]() | |
Husch, Andreas ![]() | |
Proverbio, Daniele ![]() | |
fernandes arroteia, Isabel ![]() | |
Hertel, Frank ![]() | |
Goncalves, Jorge ![]() | |
5-Apr-2022 | |
Bildverarbeitung für die Medizin 2022 | |
Springer | |
Yes | |
[en] Optimisation ; Deep Brain Stimulation ; Programming | |
[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. | |
Fonds National de la Recherche - FnR | |
http://hdl.handle.net/10993/52608 | |
10.1007/978-3-658-36932-3_62 | |
https://doi.org/10.1007/978-3-658-36932-3_62 | |
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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