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DeepMRI

imported

software/deepmri-geopi1

Pytorch implementation of RAKI, k-space interpolation of MRI data

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

DeepMRI project image
GitHub preview card for geopi1/DeepMRI. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
MIT(osi)
Status
maintained
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Repository
github.com/geopi1/DeepMRI
Documentation
unknown
Tags
interpolation · kspace · kspace-deep-learning · mri · mri-reconstruction · mridata · super-resolution
Regulatory
unknown
built by · 2

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.

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  • Co-VeGANmri · mri-reconstruction

    Co-VeGAN: Complex-Valued Generative Adversarial Network for Compressive Sensing MR Image Reconstruction

  • FastTIFFmri · mri-reconstruction

    FastTIFF - the lightning-fast tiff viewer

  • GIRFReco.jlmri · mri-reconstruction

    An Open-Source End-to-End Pipeline for Spiral Magnetic Resonance Image (MRI) Reconstruction in Julia

  • grappamri · mri-reconstruction

    A repository to experiment on GRAPPA, with a TF backend. It also features some experiments on deep versions of GRAPPA

  • mri-nufftmri · mri-reconstruction

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

sources
  1. api.github.com/repos/geopi1/DeepMRI
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2025-07-08, 39 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/47.json→ .entries["deepmri-geopi1"]

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