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fastMRI_prostate

imported

data/fastmri-prostate

A large scale dataset and reconstruction script of both raw prostate MRI measurements and images

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

fastMRI_prostate project image
GitHub preview card for cai2r/fastMRI_prostate. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Data & Standards
Subcategory
unknown
License
MIT(osi)
Status
dormant
Maturity
deployed
Organization
cai2r
Country
unknown
Documentation
unknown
Tags
fastmri · fastmri-dataset · medical-image-analysis · medical-imaging · mri-reconstruction
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.

  • fastmri-reproducible-benchmarkfastmri · fastmri-dataset · mri-reconstruction

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

  • sigmanetfastmri · mri-reconstruction

    Sigmanet: Systematic Evaluation of Iterative Deep Neural Networks for Fast Parallel MR Image Reconstruction,

  • glimpse_mrifastmri · medical-imaging

    Glimpse MRI

  • M4Rawmedical-imaging · mri-reconstruction

    A multi-contrast multi-repetition multi-channel MRI k-space dataset for low-field MRI research

  • directmedical-imaging · mri-reconstruction

    Deep learning framework for MRI reconstruction

  • i-RIM applied to the fastMRI challenge data.

sources
  1. api.github.com/repos/cai2r/fastMRI_prostate
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2024-08-04, 79 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/14.json→ .entries["fastmri-prostate"]

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