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The UK Biobank is collecting extensive data on health-related characteristicsof over half a million volunteers. The biological samples of blood and urinecan provide valuable insight on kidney function, with important links tocardiovascular and metabolic health. Further information on kidney anatomycould be obtained by medical imaging. In contrast to the brain, heart, liver,and pancreas, no dedicated Magnetic Resonance Imaging (MRI) is planned for thekidneys. An image-based assessment is nonetheless feasible in the neck-to-kneebody MRI intended for abdominal body composition analysis, which also coversthe kidneys. In this work, a pipeline for automated segmentation of parenchymalkidney volume in UK Biobank neck-to-knee body MRI is proposed. The underlyingneural network reaches a relative error of 3.8%, with Dice score 0.956 invalidation on 64 subjects, close to the 2.6% and Dice score 0.962 for repeatedsegmentation by one human operator. The released MRI of about 40,000 subjectscan be processed within two days, yielding volume measurements of left andright kidney. Algorithmic quality ratings enabled the exclusion of outliers andpotential failure cases. The resulting measurements can be studied and sharedfor large-scale investigation of associations and longitudinal changes inparenchymal kidney volume.

Kidney segmentation in neck-to-knee body MRI of 40,000 UK Biobank participants