Abstract: A method of segmentation of a medical image of a human brain including obtaining a voxelized 3D medical image of the human brain, computing at least two surface models of the human brain using a BET method, each surface model being computed for a unique fractional constant bt. For each computed surface model, determining a volume included in the computed surface model, thereby obtaining a set of sample pairs, fitting a curve to the sample pairs of the set, determining an inflection point of the curve, identifying a fractional constant bt corresponding to the determined inflection point, and computing the surface model of the human brain using the BET method that is dependent of bt.

Abstract: A computer-implemented method for voxelizing a 3D structural medical image of a human's brain. The method including obtaining a 3D structural medical image of the human's brain, including a reference frame, generating a voxelized 3D structural medical image, obtaining parameters of at least one EEG electrode sensor and, for each EEG electrode sensor: a localization in the voxelized 3D structural medical image's reference frame, and a sensor detection distance, obtaining a regular 3D grid of voxels, and for each voxel of the 3D grid, iteratively subdividing the voxel while the distance between the voxel and the localization of any electrode sensor is smaller than or equal to the sensor detection distance and while a size of the voxel is greater than a predetermined length, each subdivided voxel joining a finite number of voxels of the voxelized 3D structural medical image.