The purpose of this work is to investigate the age estimation of living individuals on the ba­sis of MRI sequences of the knee. Using a large data collective of young male subjects, a new AI-based approach is developed to automatically detect bone structures in the image and to learn the chronological age based on this information. With a mean absolute error (MAE) of 0.69 ± 0.47 years for the prediction of the age and an accuracy of 90.9% for the majority classifi­cation on the 18-year-limit, the results demonstrate the potential of this approach.weiterlesen