We implemented a processing pipeline for kidney cyst segmentation using a hierarchical patch-based stack of U-nets and applied it to abdominal MRI images of the German National Cohort (GNC) study. The training data set included 300 cases, and the final net was applied to the dataset of 11,207 MRIs. Kidney cysts could be segmented with 98% sensitivity above a lower detection threshold of 1ml. The relation of first parameters based on the cyst segmentation with age and sex are presented. This result presents an optimal starting point to identify more advanced bimarkaers and their correlates, especially with kidney function parameters.