This project is based on replication of article: BRAIN MRI SUPER RESOLUTION USING 3D DEEP DENSELY CONNECTED NEURAL NETWORKS, which utilizes deep networks to perform super resolution on 3D models from CT/MRI scans.
The training data has to be in split into two files in the data directory: (3d_lr_data.npy) containing the low resolution patches and (3d_hr_data.npy) containing their equivalent high resolution patches.
Both should have the numpy shape (N, PATCH_SIZE, PATCH_SIZE, PATCH_SIZE, 1) where N is the number of patches available.
Use the following command to check possible input arguements for training.
python dcsrn.py -h