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% Last update: Fri 12/8/17 by Ally Warner
% Last update: Tuesday, September 11 by Chris Johnson

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\section{Introduction}
\label{sec:intro}

Many simulation studies in biomedicine are based on a similar sequence
of steps, starting from images, creating geometric models, assigning
tissue properties, performing numerical simulations and visualizing the
resulting computer model and simulation results—a process known as
image-based modeling, simulation, and
visualization\cite{SCI:Mac2009a,SCI:Joh2015c,SCI:Joh2012a,SCI:Joh2006a,SCI:Joh2004b}.

We describe a detailed, comprehensive pipeline to build a complete,
high-resolution head model for Electroencephalographic (EEG) Source
Imaging (ESI) and EEG Forward simulation studies.  Steps of the
pipeline include image acquisition, preprocessing and registration,
image segmentation, finite element mesh generation, simulations, and
visualization. This project includes a complete, high-resolution brain
segmentation that can be used to create three-dimensional tetrahedral
volume and surface meshes. We provide two three-dimensional
tetrahedral finite element meshes made from the segmentation of
different resolutions that serve as volume conductors to solve 
forward and inverse EEG problems. We provide simulation examples of the
EEG forward problem, with isotropic and anisotropic systems; functional
image data mapped onto a tetrahedral mesh; electroencephalography
(EEG) signals mapped onto net electrodes; and diffusion tensor data.

Along with outlining the pipeline, we have made the results of this
project available as open-source data sets to aid other scientists for use in
their EEG forward and inverse simulation studies and for help them
build new head models more efficiently. The complete head model
presented here took approximately one year to complete, in part due to
the many options in software and techniques, as well as the complexity
of the multimodal imaging data. The segmentation of the image data
took approximately 100 hours, mostly dedicated to manual
editing. Because the segmentation was high resolution, the resulting
tetrahedral meshes became extremely large, which made for very slow
simulations. Further simplification methods were developed to achieve
moderately sized geometric models.  The head model also includes
registration of diffusion tensor data, functional MR data, and high
resolution EEG recordings from 128 and 256 electrodes dense array
Philips/EGI sensor nets.  The images, data, models, and software are
available at \url{www.sci.utah.edu/SCI-Headmodel}.

