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Using 3D CNNs on high resolution medical volumes is very computationallydemanding, especially for large datasets like the UK Biobank which aims to scan100,000 subjects. Here we demonstrate that using 2D CNNs on a few 2Dprojections (representing mean and standard deviation across axial, sagittaland coronal slices) of the 3D volumes leads to reasonable test accuracy whenpredicting the age from brain volumes. Using our approach, one training epochwith 20,324 subjects takes 20 - 50 seconds using a single GPU, which two ordersof magnitude faster compared to a small 3D CNN. These results are important forresearchers who do not have access to expensive GPU hardware for 3D CNNs.

Efficient brain age prediction from 3D MRI volumes using 2D projections