The project 'pMRI-Net-ZF' implements the method described in "Deep Parallel MRI Reconstruction Network Without Coil Sensitivities" "https://arxiv.org/pdf/2008.01410.pdf"
Test data, learned weights and sampling mask can be downloaded in https://drive.google.com/drive/folders/1jVV0qk_4iZlY10wKadQiAEP4Sr1V6Z9N?usp=sharing
The file named 'pd_Phase5_ZF' is learned weights for 'pMRI-Net-ZF.py'.
The file named 'pd_Phase4_K_c' is learned weights for 'pMRI-CNet-K.py'.
The code was implementated on Window 10 via tensorflow-gpu 1.10.0, python 3.6.10
For training the network, simply use
python pMRI-Net-ZF.py
or
python pMRI-CNet-K.py
The reconstruction process is automatically start after training process stopped for certain epochs.
We provided the learned weights that has already trained, you can just delete the training part in the code.
The output are 15 recontructed knee images as *.mat.