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This paper introduces a highly adaptive and automated approach for generatingFinite Element (FE) discretization for a given realistic multi-compartmenthuman head model obtained through magnetic resonance imaging (MRI) dataset. Weaim at obtaining accurate tetrahedral FE meshes for electroencephalographicsource localization. We present recursive solid angle labeling for the surfacesegmentation of the model and then adapt it with a set of smoothing, inflation,and optimization routines to further enhance the quality of the FE mesh. Theresults show that our methodology can produce FE mesh with an accuracy greaterthan 1 millimeter, significant with respect to both their 3D structurediscretization outcome and electroencephalographic source localizationestimates. FE meshes can be achieved for the human head including complex deepbrain structures. Our algorithm has been implemented using the openMatlab-based Zeffiro Interface toolbox with it effective time-effectiveparallel computing system.

Multi-compartment human head modeling: generating adaptive tetrahedral mesh with GPU acceleration