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Stable Deep MRI Reconstruction

Stable Deep MRI Reconstruction

This repository contains the code of Stable Deep MRI Reconstruction using Generative Priors.

Usage

The framework assumes the environment variables EXPERIMENTS_ROOT (needed for training) and DATASETS_ROOT (needed for training and evaluation) to be set. EXPERIMENTS_ROOT is the output base-directory for training can be any directory on the machine. DATASETS_ROOT should contain the fastmri dataset, i.e. the directory $DATASETS_ROOT/fastmri/multicoil_train (e.g.) should exist.

Training

To train the model, run python train.py output_dir. The first argument is the experiment output directory, i.e. checkpoints and losses etc. will be saved to $EXPERIMENTS_ROOT/output_dir/.

Evaluation

All evaluation code is found in evaluate.py. The if __name__ == '__main__': block lists evaluation functions along with annotations indicating the corresponding table or figure in the paper. Pretrained models and other data needed for evaluation can be found here.

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Code for "Stable Deep MRI Reconstruction using Generative Priors" (https://ieeexplore.ieee.org/document/10237244)

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