felipesteodoro / dc-wcnn

DC-WCNN-Wavelet-based-CNN

Wavelet-based encoder decoder architecture for MRI Reconstruction

DC-WCNN: A Deep Cascade Of Wavelet based Convolutional Neural Networks For MR Image Reconstruction (ISBI 2020)

Dependencies

Packages

• PyTorch
• TensorboardX
• OpenCV
• numpy
• tqdm

An exhaustive list of packages used could be found in the requirements.txt file. Install the same using the following command:

 conda create --name <env> --file requirements.txt

Train code

sh train_kirby.sh

Test code

sh valid_kirby.sh

Evaluate PSNR / SSIM metrics

sh evaluate_kirby.sh

Display PSNR / SSIM metrics

sh report_collect_kirby.sh

Citations

If you use the DC-WCNN in your research, please consider citing:

@article{sriprabha-dc-wcnn-2020,
  title={DC-WCNN: A Deep Cascade Of Wavelet based Convolutional Neural Networks For MR Image Reconstruction},
  author={Sriprabha Ramanarayanan, Balamurali Murugesan, Keerthi Ram and Mohanasankar Sivaprakasam},
  journal={ArXiv},
  year={2020},
  volume={abs/2001.02397}
}