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