CMRxRECON Challenge -- EDIPO Group

Introduction

This is the repository for the inferece code from EDIPO group for the CMRxRECON challenge. The code is based on the fastMRI with Pytorch Lightning 2.0 framework.

The file structure is as follows:

├── data
│   ├── __init__.py   
│   ├── mri_data.py                             # How to read data and arrange dataset
│   ├── transforms.py                           # Data transforms
│   └── transform_utils.py                      # Data transforms helper functions
├── inference.py                                # The main inference script
├── input                                       # Input folder
|   └── SingleCoil                              # Single coil data
|       └── Cine                                # Cine task
|           └── xSet                            # Training, Validation or TestSet                                             
|               ├── AccFactor04                 # Acceleration factor 4
|               ├── AccFactor08                 # Acceleration factor 8
|               └── AccFactor10                 # Acceleration factor 10
├── logs
│   └── Experiment1
│       └── checkpoints
│           └── epoch=x-step=xxxx.ckpt          # Checkpoint file
├── models
│   ├── cinenet.py                              # CineNet model
│   ├── datalayer.py                            # Data consistency layers
│   ├── __init__.py
│   ├── recurrent_cinenet_diffcas.py            # Recurrent CineNet model with different cascades
│   ├── recurrent_cinenet_no_weight_sharing.py  # Recurrent CineNet model without weight sharing
│   ├── recurrent_cinenet.py                    # Recurrent CineNet model
│   └── unet.py                                 # U-Net model
├── output                                      # Output folder
├── pl_modules                                  # Pytorch Lightning modules
│   ├── cinenet_module.py                       # CineNet model pl_module
│   ├── CRNN_cinenet_module.py                  # Recurrent CineNet model pl_module
│   ├── data_module.py                          # Data module
│   ├── __init__.py
│   └── mri_module.py                           # MRI module, parent of all other network pl_modules
├── README.md
├── requirements.txt                            # Need to pip install this file
├── utils                                       # Utility functions                                    
│    ├── evaluate.py                            # Evaluation functions                           
│    ├── fft.py                                 # FFT functions                                       
│    ├── __init__.py
│    ├── io.py                                  # IO functions, save reconstructions to mat                                    
│    ├── losses.py                              # Loss functions
│    └── math.py                                # Complex math functions
└── visualize_and_evaluate.py                  # Code to make some visualization of recon images and compute SSIM-NMSE-PSNR metrics

How to run

First install the requirement as follows:

pip install -r requirements.txt

Then run the inference script as follows:

python inference.py --checkpoint_path logs/Experiment1/checkpoints/epoch=x-step=xxxx.ckpt 

Note the input should be located in input folder, and the reconstructions will be saved in the output folder.

Results

References

[1].