| Abstract: |
| We present MRpro, an open-source image reconstruction package for MRI built upon PyTorch and open data formats. MRpro consists of three main areas. First, it provides unified datastructures for the processing and handling of MR datasets and their associated metadata, such as sampling trajectories in the Fourier domain. Second, it provides relevant mathematical concepts and operations required to build abstract reconstruction algorithms. Third, to enable the easy development of state-of-the-art learned reconstruction methods, MRpro includes essential building blocks such as so-called data-consistency layers, differentiable optimization layers and well-established neural network backbones.
In this talk, we showcase different components of MRpro by considering several learned and non-learned MR imaging problems using both publicly available open-source data, numerical phantoms as well as raw scanner data, demonstrating MRpro`s versatility. |
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