Data-Driven Regularization Parameter Selection in Dynamic MRI

@article{Hanhela2021DataDrivenRP,
  title={Data-Driven Regularization Parameter Selection in Dynamic MRI},
  author={Matti Hanhela and Olli H. J. Gr{\"o}hn and Mikko I. Kettunen and Kati Niinim{\"a}ki and Marko Vauhkonen and Ville Kolehmainen},
  journal={Journal of Imaging},
  year={2021},
  volume={7}
}
In dynamic MRI, sufficient temporal resolution can often only be obtained using imaging protocols which produce undersampled data for each image in the time series. This has led to the popularity of compressed sensing (CS) based reconstructions. One problem in CS approaches is determining the regularization parameters, which control the balance between data fidelity and regularization. We propose a data-driven approach for the total variation regularization parameter selection, where… 

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