A computer-implemented method of training a learning algorithm for determining a relation between a label for indicating a position or type of an anatomical structure in a medical image on the one hand and the position or type of the anatomical structure in the medical image on the other hand, the learning algorithm being a convolutional neural network and the method comprising the following steps: a) patient training image data is acquired which describes digital medical images of an anatomical structure of a plurality of patients; b) atlas data is acquired which describes an image-based model of an anatomical body part including the anatomical structure, wherein the atlas data represents the result of a statistical analysis of medical image data for a plurality of human bodies, wherein the result is output as an image and contains or is comparable to medical image data; c) viewing direction data is acquired which describes the viewing direction of an imaging device towards the anatomical structure at the point in time when the imaging device was used to generate the medical image; d) anatomical vector data is determined based on the viewing direction data and the atlas data, wherein the anatomical vector data describes an anatomical vector which is a result of transforming the viewing direction into a reference system in which positions in the image-based model are defined; e) label data is acquired which describes a label describing the position or type of the anatomical structure in the image-based model; and f) anatomical indicator data is determined based on the patient training image data and the anatomical vector data and the label data, wherein the anatomical indicator data describes model parameters of the learning algorithm for establishing the relation between the position or type of the anatomical structure described by the medical image and the label, wherein the anatomical indicator data is determined by inputting the patient training image data and the label data and a subset of the atlas data into a function which is part of the learning algorithm and establishes the relation, wherein the subset of the atlas data has been determined based on the atlas data and the anatomical vector data. a) patient training image data is acquired which describes digital medical images of an anatomical structure of a plurality of patients; b) atlas data is acquired which describes an image-based model of an anatomical body part including the anatomical structure, wherein the atlas data represents the result of a statistical analysis of medical image data for a plurality of human bodies, wherein the result is output as an image and contains or is comparable to medical image data; c) viewing direction data is acquired which describes the viewing direction of an imaging device towards the anatomical structure at the point in time when the imaging device was used to generate the medical image; d) anatomical vector data is determined based on the viewing direction data and the atlas data, wherein the anatomical vector data describes an anatomical vector which is a result of transforming the viewing direction into a reference system in which positions in the image-based model are defined; e) label data is acquired which describes a label describing the position or type of the anatomical structure in the image-based model; and f) anatomical indicator data is determined based on the patient training image data and the anatomical vector data and the label data, wherein the anatomical indicator data describes model parameters of the learning algorithm for establishing the relation between the position or type of the anatomical structure described by the medical image and the label, wherein the anatomical indicator data is determined by inputting the patient training image data and the label data and a subset of the atlas data into a function which is part of the learning algorithm and establishes the relation, wherein the subset of the atlas data has been determined based on the atlas data and the anatomical vector data.