In this part of the 2017 kaggle data science bowl preprocessing tutorial kernel, the author says the different spacing between scans "can be problematic for automatic analysis (e.g. using ConvNets)", and then demonstrates the method of "resampling the full dataset to a certain isotropic resolution".
I wonder what kind of problem will arise if we don't resample to isotropic resolution? Would anyone give a theoretic explanation?