1. A labeling apparatus for identifying and labeling three-dimensional structures of an object shown in a three-dimensional medical image, the labeling apparatus comprising: a computing device having a processor and a memory, together with a graphical user interface, a contour unit configured to provide three-dimensional contour images representing three-dimensional structures in the medical image, a probability map unit configured to provide a three-dimensional probability map, the probability map indicating for different labels, which are indicative of different three-dimensional structures of said object in the medical image, and for different positions in the probability map, the probability that each of said different structures, indicated by said structure's respective label is present at said structure's respective position, wherein said probability depends on the position of said structure in the probability map, a mapping unit configured to map said three-dimensional probability map to the three-dimensional medical image such that the positions of the three-dimensional structures in the probability map are assigned to positions of three-dimensional contour images in the medical image, and a label assigning unit configured to assign a label to each three-dimensional contour image based on the mapped three-dimensional probability map, wherein said label assigning unit is adapted to define positions of image elements in accordance with the provided three-dimensional contour image and a predefined definition rule, the predefined definition rule defining three-dimensional positions of image elements depending on a three-dimensional contour, determine for each label a label probability depending on the probabilities which are defined by the mapped probability map and the defined three-dimensional positions of image elements and identify the label of largest label probability for each three-dimensional contour image, and assign the label to the three-dimensional contour image for which the largest label probability has been determined, and wherein data relating to said three-dimensional contour image and said three-dimensional medical image are not divided into a series of two-dimensional image slices for determining said label probability and assigning said label.