Correcting Volume Conductor Segmentations

Using BESA MRI it is possible to compute EEG leadfields using individual, realistic models of a subject's head. These models are automatically created based on a T1-weighted MRI and optionally an additional T2-weighted MRI. The first step of the model creation is the segmentation of the head into the different tissues which are relevant for the EEG forward problem. This step is called the volume conductor segmentation. In BESA MRI a fully automatic, robust procedure is implemented which in general delivers very accurate segmentations.

In some rare cases, however, it might happen that the automatic segmentation result contains inaccuracies and might, thus, be considered as inadequate. Segmentation problems might occur for data sets with atypical anatomy, for example, data sets containing brain lesions. In these data sets the incorporated anatomical priors are not consistent with the anatomy of the subject or patient. This might lead to errors.

As an automatic segmentation of lesion data sets is currently not possible an alternative way of generating an adequate segmentation is to manually correct the segmentation mask, and then use the corrected segmentation mask as the basis for the FE mesh generation. This article explains how BESA MRI can be used to generate individual FEM leadfields based on a corrected volume conductor segmentation mask.

The procedure runs roughly as follows: The automatically generated segmentation mask and the associated T1 and T2 images are written to Analyze files, which can be read by many 3rd party tools. A suitable 3rd party tool can then be used to modify the segmentation mask. The modified mask is read by BESA MRI and used for the generation of the FE meshes and, thus, also for the individual FEM leadfield computation. This procedure is described in detail below.