The human brain undergoes fundamental structural changes between the second and the third trimester of pregnancy [1]. The most accurate non-invasive method for observing these events to date is the (ultra) fast magnetic resonance (MR) imaging technique. It allows to image a fetus at a satisfying resolution, despite its small size or varying position [2]. A problem of MR imaging is the lack of comparability and constancy of gray-values, which are mapped according to the proton (hydrogen) concentration. It differs among patients and results in varying gray-values for varying proton density [3]. This motivates to build a fetal brain atlas to use it as a standard space. Brain structures can be mapped according to marked anatomical locations, to make fetal brains comparable for studying brain development, fetal pathology locations, fetal abnormalities or anatomy. ! ! The aim of the work is to provide an atlas of the developing fetal brain, consisting of a continuous, quantifiable model of brain development derived by geodesic shooting regression [4,5] and an automated labeling procedure using a graph cut based segmentation approach [7].