PHiRec

Uncertainty Estimation and Propagation in Accelerated MRI Reconstruction

Official implementation for the UNSURE@MICCAI2023 workshop paper: Uncertainty Estimation and Propagation in Accelerated MRI Reconstruction Arxiv Paper

Model overview

Results

Metric comparison

Uncertainty propagation

Installation

conda create --name phirec --file requirements.txt

Datasets

We perform all trainings and evaluations on the Stanford Knee MRI Multi-Task Evaluation (SKM-TEA) Dataset.

SKM-TEA (https://github.com/StanfordMIMI/skm-tea)

Usage

The folder examples contains training and evaluation examples for all the models that we compare against each other.

References

If you use any of the code in this repository for your research, please cite as:

  @misc{fischer2023mruq,
      title={Uncertainty Estimation and Propagation in Accelerated MRI Reconstruction}, 
      author={Fischer, Paul and Küstner, Thomas and Baumgartner, Christian F.},
      year={2023},
      eprint={2308.02631},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}