3D segmentation of SBFSEM images of neuropil by a graphical model over supervoxel boundaries

► We propose a supervoxel merging method for segmenting 3D SBFSEM images of neuropil. ► All merging decisions are coupled in a graphical model. ► Knowledge about correct segments is incorporated in higher-order potentials. ► These potentials are learned automatically from training data. ► The scope of this improvement is demonstrated on the benchmark dataset E1088.