BrainK for Structural Image Processing: Creating Electrical Models of the Human Head.

Kai Li,Xenophon Papademetris,Don M Tucker

doi:10.1155/2016/1349851

Abstract

BrainK is a set of automated procedures for characterizing the tissues of the human head from MRI, CT, and photogrammetry images. The tissue segmentation and cortical surface extraction support the primary goal of modeling the propagation of electrical currents through head tissues with a finite difference model (FDM) or finite element model (FEM) created from the BrainK geometries. The electrical head model is necessary for accurate source localization of dense array electroencephalographic (dEEG) measures from head surface electrodes. It is also necessary for accurate targeting of cerebral structures with transcranial current injection from those surface electrodes. BrainK must achieve five major tasks: image segmentation, registration of the MRI, CT, and sensor photogrammetry images, cortical surface reconstruction, dipole tessellation of the cortical surface, and Talairach transformation. We describe the approach to each task, and we compare the accuracies for the key tasks of tissue segmentation and cortical surface extraction in relation to existing research tools (FreeSurfer, FSL, SPM, and BrainVisa). BrainK achieves good accuracy with minimal or no user intervention, it deals well with poor quality MR images and tissue abnormalities, and it provides improved computational efficiency over existing research packages.

Highlights

With the simple recording of the electroencephalogram (EEG), the brain’s electrical activity can be measured with millisecond temporal resolution at the head surface
We present a new segmentation method referred to as relative thresholding (RT), which uses two global relative thresholds to compare with the local intensity contrasts, thereby bringing global and local information to segment the region of interest (ROI) into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF)
BrainK provides certain algorithms, such as skull bone density (X-ray CT) image registration and cortical surface dipole tessellation, which are important to model the electrical properties of the human head

Summary

Introduction

With the simple recording of the electroencephalogram (EEG), the brain’s electrical activity can be measured with millisecond temporal resolution at the head surface. Dense array EEG (dEEG) systems allow up to 256 channels to be applied quickly with full coverage of the head, assessing the fields from the basal as well as superior cortical surface [1, 2]. The cortex, with its laminar neural organization and with locally synchronous activity stemming from its columnar organization, is the primary generator of the far fields measured by head surface EEG [3]. Cortical sources can be modeled as point dipoles, and their contribution to surface activity can be reconstructed through electrical source analysis. The source dipoles can be assumed to be oriented perpendicular to the cortical surface, consistent with the orientation of the pyramidal neurons and cortical columns

Methods

Results

Conclusion