  To analyse multimodal 3-dimensional medical images, interpolation is required
for resampling which - unavoidably - introduces an interpolation error. In this
work we consider three segmented 3-dimensional images resampled with three
different neuroimaging software tools for comparing undersampling and
oversampling strategies and to identify where the oversampling error lies. The
results indicate that undersampling to the lowest image size is advantageous in
terms of mean value per segment errors and that the oversampling error is
larger where the gradient is steeper, showing a Gibbs effect.
