18 April 2000 Characterizing subdural EEG electrode grids in a virtual realistic environment
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Proceedings Volume 3976, Medical Imaging 2000: Image Display and Visualization; (2000); doi: 10.1117/12.383045
Event: Medical Imaging 2000, 2000, San Diego, CA, United States
Abstract
When the focus of epilepsy is so deep that skin EEG electrodes do not give enough accuracy in calculating the position of the focus, it may be decided to surgically implant EEG electrodes inside the patient's head. To localize these electrodes, a high resolution CT scan is made of the patients' head. As manual tracking of the electrodes slice by slice is confusing and erroneous, a virtual reality environment has been created to give the radiologist a view from inside the patient's skull. With the help of a high quality but fast volume renderer, the radiologist can get an overview of electrode grids and can interactively characterize the grid contacts of interest;. For the localization of the contracts, we compared manual placement, center of gravity and Gaussian template matching. It appeared that the grid contacts could be characterized with an accuracy of 0.5 mm, that manual positioning and template matching with a Gaussian with flexible sizes clearly outperformed center of gravity and template matching with an isotropic Gaussian. The reason is that although the contacts are clearly visible in a CT, their small dimensions, and proximity to skull and metal wires, makes them more difficult to characterize fully automatically than commonly expected.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Herke Jan Noordmans, R. Hoekema, P. C. van Rijen, C. W. M. van Veelen, Max A. Viergever, "Characterizing subdural EEG electrode grids in a virtual realistic environment", Proc. SPIE 3976, Medical Imaging 2000: Image Display and Visualization, (18 April 2000); doi: 10.1117/12.383045; https://doi.org/10.1117/12.383045
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KEYWORDS
Electrodes

Electroencephalography

Skull

Computed tomography

Head

Epilepsy

Visualization

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