Related Experiment Videos
The effect of layers in imaging brain function using electrical impedance tomograghy
A D Liston1, R H Bayford, D S Holder
1Middlesex University, Archway Campus, Furnival Building, Highgate, London N19 3UA, UK.
Physiological Measurement
|March 10, 2004
Summary
Improving brain imaging with electrical impedance tomography (EIT) requires advanced models. Multi-layered head models significantly enhance EIT image quality compared to simpler homogeneous models.
Area of Science:
- Medical Imaging
- Biomedical Engineering
- Electrical Engineering
Background:
- Electrical impedance tomography (EIT) shows promise for brain function imaging using scalp electrodes.
- Current human EIT imaging relies on homogeneous sphere models, limiting image quality.
Purpose of the Study:
- To assess image quality improvements by incorporating cerebro-spinal fluid (CSF), skull, and scalp layers into EIT forward models.
- To compare analytical and finite element method (FEM) approaches for EIT reconstruction.
Main Methods:
- Developed analytical and linear FEM solutions for multi-layered spherical head models.
- Validated methods with computer-simulated data and physical tank experiments.
- Tested reconstruction algorithms using homogeneous and multi-shell models.
Main Results:
- Four- or three-shell analytical models yielded best spatial accuracy (5.8 +/- 2.2 mm simulated; 14.0 +/- 5.8 mm tank).
- Homogeneous models showed 50-300% higher localization errors.
- FEM reconstructions performed poorly, similar to homogeneous analytical models, indicating a need for FEM method refinement.
Conclusions:
- Adding layers to the forward model improves EIT image quality with analytical reconstruction.
- The specific linear FEM approach used requires further development to achieve expected benefits.