Brain tissue classification from stereoelectroencephalographic recordings - Modelling and Optinal Decision for Uncertain Systems Accéder directement au contenu
Article Dans Une Revue Journal of Neuroscience Methods Année : 2022

Brain tissue classification from stereoelectroencephalographic recordings

Résumé

In drug-resistant epileptic patients, direct electrical brain stimulation sessions may be needed to identify epileptic regions on the brain before surgery. In this context, the classification of the brain tissue in which the electrodes are implanted in is very important for the interpretation of observed responses. This paper presents a new method for tissue classification based on the study of the baseline data with signal processing methods and features estimated from non parametric frequency identification of transfer functions. The method is tested on actual data and compared to visual classification of contacts coregistered on magnetic resonance imaging. The results show that good separability between matters, with up to $80\%$ accuracy, can be achieved when considering the pairing of two consecutive electrodes.
Fichier principal
Vignette du fichier
Brain_tissue_classification_from_stereoelectroencephalographic_recordings_texte2.pdf (4.85 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03432757 , version 1 (15-12-2021)

Identifiants

Citer

Mariana Mulinari Pinheiro Machado, Alina Voda, Gildas Besancon, Guillaume Jean-Paul Claude Becq, Philippe Kahane, et al.. Brain tissue classification from stereoelectroencephalographic recordings. Journal of Neuroscience Methods, 2022, 365, pp.109375. ⟨10.1016/j.jneumeth.2021.109375⟩. ⟨hal-03432757⟩
81 Consultations
68 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More