openmedical/registry
← registry

mri-nufft

imported

software/mri-nufft

Doing non-Cartesian MR Imaging has never been so easy.

Machine-generated from the listed sources and not yet reviewed by a human.

record
Category
Software & Systems
Subcategory
unknown
License
BSD-3-Clause(osi)
Status
active
Maturity
deployed
Organization
mind-inria
Country
unknown
Documentation
unknown
Tags
cuda · gpu · mri · mri-reconstruction · nufft · numerical-methods · numpy · tensorflow
Regulatory
unknown
built by · 6

Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.

similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • sigpygpu · mri · nufft

    Python package for signal processing, with emphasis on iterative methods

  • tfkbnufftmri · nufft · tensorflow

    A robust, easy-to-deploy non-uniform Fast Fourier Transform in TensorFlow.

  • fastmri-reproducible-benchmarkmri · mri-reconstruction · tensorflow

    Try several methods for MRI reconstruction on the fastmri dataset. Home to the XPDNet, runner-up of the 2020 fastMRI challenge.

  • pyDHMnumerical-methods

    A Python library to numerically recover the complex wavefield information of samples from Digital Holographic Microscopy (DHM) recordings. Phase compensation, phase-shifting methods, and numerical…

  • MIRT.jlmri · nufft

    MIRT: Michigan Image Reconstruction Toolbox (Julia version)

  • torchkbnufftmri · nufft

    A high-level, easy-to-deploy non-uniform Fast Fourier Transform in PyTorch.

sources
  1. api.github.com/repos/mind-inria/mri-nufft
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2026-08-03, 125 stars, license reported as BSD-3-Clause. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/59.json→ .entries["mri-nufft"]

Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.