Keywords: Software Tools, Software Tools, NUFFT, Non-Cartesian
Motivation: Non-Cartesian imaging remains complicated to use for MRI due to the high computational cost of the Non-Uniform Fourier Transform for image reconstruction.
Goal(s): To provide a uniform interface for reconstructing magnetic resonance images from non-Cartesian k-space data and a collection of non-Cartesian sampling trajectories
Approach: We propose an open-source Python package (https://github.com/mind-inria/mri-nufft/) providing a standard interface to existing NUFFT libraries, with extended models for multi-coil imaging and static-field (B0) inhomogeneities correction.
Results: MRI-NUFFT can generate sampling trajectories, compliant with hardware constraints, as well as simple forward/adjoint operations and density compensation for use in advanced image reconstruction scenarios.
Impact: With MRI-NUFFT, non-Cartesian MRI trajectories and reconstruction algorithms become accessible, efficient, and affordable to everyone for research and education purposes.
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