BrainVoyager v22.2

Overview of Cortex Segmentation Steps

Achieving accurate segmentation of the cortical sheet is a very difficult task, which involves a substantial amount of work if done manually. In this section a set of tools is described with the goal to create correct segmentations of the cortical sheet of the left and right hemisphere in a largely automatic way. The better the grey / white matter contrast of the used 3D MRI data sets, the less manual work is necessary. It is recommended to use optimized structural T1-weighted MRI sequences in order to reduce manual corrections to a minimum. The automatic segmentation procedure runs through a sequence of steps including a filter enhancing tissue contrast (sigma filter), masking to remove the cerebellum and non-brain tissue, filling of ventricles and subcortical structures, intensity histogram analysis to calculate proper thresholds to separate white and grey matter, morphological operations to smooth the resulting segmentation and a "bridge removal" tool (contributed by Niko Kriegeskorte) to remove topological errors.

The automatic segmentation pipeline assumes that the input data is a (iso-voxeled) 1 mm data set in ACPC or Talairach space. If you have data that was truly acquired (without interpolation) at sub-millimeter voxel resolution, you may consider using the advanced segmentation tools. Since BrainVoyager QX 2.8 it is also possible to run the automatic segmentation pipeline using the advanced segmentation routines for 1 mm data sets by turning on the High-resolution (upsampled 0.5 mm iso voxel) option in the Automatic Cortex Segmentation and Reconstruction dialog.

Prerequisites

The following prerequisites should be considered before running the automatic segmentation tools:

The automatic segmentation routines attempt to provide high-quality results. Still it is recommended that you check the segmentation result using provided visualization tools and to improve it if necessary using provided correction ("drawing") tools.


Copyright © 2021 Rainer Goebel. All rights reserved.