An Automated Detection of Amyotrophic Lateral Sclerosis from Resting State MEG Data Using 3D Deep Convolutional Neural Network

Kaniska Samanta, Sujit Roy, Veronique Marchand-Pauvert, Shirin Dora, Stephanie Duguez, Muskaan Singh, Girijesh Prasad, Saugat Bhattacharyya

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A novel 3D deep convolutional neural network (3D-CNN) model called MEGNet3D has been proposed in the paper. MEGNet3D is designed to differentiate between amyotrophic lateral sclerosis (ALS) and healthy individuals from their resting state (eyes open and eyes closed condition) sensor-level magnetoencephalography (MEG) data. The raw MEG data is initially transformed into their time-frequency representation, which are then used as inputs to MEGNet3D. Both magnetometer and gradiometer recordings have been investigated separately. The proposed model exhibits an accuracy of over 75% for most classification conditions. Thus, MEGNet3D is capable of handling high subject variability and shows that spectral-temporal representation of resting-state MEG data yields relevant neural markers related to the existence of ALS. Furthermore, it has also been observed resting state with eyes closed yields better classification accuracy as compared to the resting state with eyes open condition.
Original languageEnglish
Title of host publication2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
Place of PublicationOahu, Hawaii, USA
PublisherIEEE
Pages3337-3342
Number of pages6
Publication statusAccepted/In press - Oct 2023
EventThe 2023 IEEE Conference on Systems, Man, and Cybernetics - Oahu, Honolulu, United States
Duration: 1 Oct 20234 Oct 2023
https://ieeesmc2023.org/

Conference

ConferenceThe 2023 IEEE Conference on Systems, Man, and Cybernetics
Country/TerritoryUnited States
CityHonolulu
Period1/10/234/10/23
Internet address

Keywords

  • Amyotrophic lateral sclerosis (ALS)
  • vision transformer
  • deep learning
  • magnetoencephalography (MEG)

Fingerprint

Dive into the research topics of 'An Automated Detection of Amyotrophic Lateral Sclerosis from Resting State MEG Data Using 3D Deep Convolutional Neural Network'. Together they form a unique fingerprint.

Cite this