A computer-implemented method of determining a label set of multiple labels for anatomical substructures of an anatomical structure depicted by a medical imaging dataset , the anatomical structure comprising the multiple anatomical substructures arranged in multiple sequences, the multiple sequences of the anatomical substructures being joined at bifurcation points, wherein the method comprises: - obtaining a tree-structured segmentation of the anatomical structure in the medical imaging dataset, the tree-structured segmentation comprising multiple sequences of sections associated with the sequences of substructures of the anatomical structure, - obtaining, for each section of the tree-structured segmentation, a respective predetermined list of candidate labels and associated probabilities , - obtaining a ruleset of anatomical interrelationships between the substructures of the anatomical structure based on expert knowledge, wherein the ruleset excludes certain combinations of substructures to be in direct neighborhood and/or specifies allowed combinations of substructures to be in direct neighborhood, and - determining the label set by performing a selection, for each section of the tree-structured segmentation, from the respective predetermined list of candidate labels of a respective label based on the associated probabilities and taking into account the ruleset of anatomical interrelationships, characterized in that : wherein the selections for the sections of the tree-structured segmentation are performed in accordance with a recursive walkthrough through the tree-structured segmentation, wherein the recursive walkthrough visits at least some sections of the tree-structured segmentation multiple times to determine multiple alternative solutions for the label set. - obtaining a tree-structured segmentation of the anatomical structure in the medical imaging dataset, the tree-structured segmentation comprising multiple sequences of sections associated with the sequences of substructures of the anatomical structure, - obtaining, for each section of the tree-structured segmentation, a respective predetermined list of candidate labels and associated probabilities , - obtaining a ruleset of anatomical interrelationships between the substructures of the anatomical structure based on expert knowledge, wherein the ruleset excludes certain combinations of substructures to be in direct neighborhood and/or specifies allowed combinations of substructures to be in direct neighborhood, and - determining the label set by performing a selection, for each section of the tree-structured segmentation, from the respective predetermined list of candidate labels of a respective label based on the associated probabilities and taking into account the ruleset of anatomical interrelationships, characterized in that : wherein the selections for the sections of the tree-structured segmentation are performed in accordance with a recursive walkthrough through the tree-structured segmentation, wherein the recursive walkthrough visits at least some sections of the tree-structured segmentation multiple times to determine multiple alternative solutions for the label set. wherein the selections for the sections of the tree-structured segmentation are performed in accordance with a recursive walkthrough through the tree-structured segmentation, wherein the recursive walkthrough visits at least some sections of the tree-structured segmentation multiple times to determine multiple alternative solutions for the label set. <EOS>