Construction of human head voxel models from MR images for EEG analysis based on EM algorithm

Teruyoshi Sasayama, Tomoaki Iida, Takenori Oida, Shoji Hamada, Tetsuo Kobayashi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In order to enhance the reliability of electroencephalogram (EEG) signal source analyses, utilizing EEG lead field matrices obtained by field analyses in custom-made real head models is effective technique. Custom-made models are usually constructed from voxel models derived from magnetic resonance (MR) images using a variety of image-processing techniques. We have improved one of the techniques that select threshold levels dividing signals and noises based on the EM (expectation-maximization) algorithm. This technique contributes to rapid and high-quality voxel model acquisition. We demonstrate the following operations: (a) voxel model construction, (b) lead field calculation, and (c) simulation of EEG electrode voltage measurement induced by an equivalent current dipole (ECD), which is set in the primary motor cortex by considering application of brain-machine interfaces. The proposed technique is compared with other techniques based on the voltage differences caused by the constructed model-shape differences.

Original languageEnglish
Title of host publication2010 IEEE/ICME International Conference on Complex Medical Engineering, CME2010
Pages100-105
Number of pages6
DOIs
Publication statusPublished - Oct 15 2010
Externally publishedYes
Event2010 IEEE/ICME International Conference on Complex Medical Engineering, CME2010 - Gold Coast, QLD, Australia
Duration: Jul 13 2010Jul 15 2010

Publication series

Name2010 IEEE/ICME International Conference on Complex Medical Engineering, CME2010

Other

Other2010 IEEE/ICME International Conference on Complex Medical Engineering, CME2010
CountryAustralia
CityGold Coast, QLD
Period7/13/107/15/10

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging
  • Neuroscience(all)

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