Hey,
I did not load the whole MRI image to the data loader. The MR images I am using are of size 172x220x156 so it will exceed the memory Cuda cores can load.
For image synthesis, I created patches of 10000 per image and augmented the data. In your case of classification, it should be similar.
Then I am using regression analysis/prediction from MR image which will not work in patch-based training…so I subsampled the image to reduce the number of voxel size per image.
Then the PyTorch data loader should work fine.
Let me know if you need more help.
I would suggest you use Jupyter notebook or Pycharm IDE for coding. I find them easy to use and feasible. Use python 3.6 if possible, not all the libraries support 3.7 yet.
Since it is Pytorch help forum I would ask you to stick to it, eh…