Medical image analysis techniques require an initial localization and segmentation of the corresponding anatomical structures. As part of the VISCERAL Anatomy segmentation benchmarks, a hierarchical multi-atlas multi-structure segmentation approach guided by anatomical correlations is proposed (AnatSeg-Gspac). The method defines a global alignment of the images and renes locally the anatomical regions of interest for the smaller structures. In this paper, the method is evaluated in the VISCERAL Anatomy3 benchmark in twenty anatomical structures in both contrast-enhanced and non-enhanced computed tomography (CT) scans. AnatSeg-Gspac obtained the lowest average Hausdor distance in 19 out of the 40 possible structure scores in the test set CT scans.