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STRESS

imported

software/stress

Implementation of 'Stress: Super-Resolution for Dynamic Fetal MRI using Self-Supervised Learning'

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

STRESS project image
GitHub preview card for daviddmc/STRESS. 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
dormant
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Repository
github.com/daviddmc/STRESS
Documentation
unknown
Tags
deep-learning · mri · pytorch · self-supervised-learning · super-resolution
Regulatory
unknown
similar by tags

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    Diffusion-based super-resolution for 7T fMRI-EPI, with an MR-realistic k-space degradation operator for DDRM

  • SR-UNetmri · pytorch · super-resolution

    Customized implementation of the U-Net in PyTorch for super-resolving hyper-low-field MRI images.

  • event_super-resolutionself-supervised-learning · super-resolution

    Repo for Neuromorphic Imaging with Super-Resolution, IEEE TCSVT, 2025.

  • DeepMRImri · super-resolution

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

  • mialsuperresolutiontoolkitmri · super-resolution

    The Medical Image Analysis Laboratory Super-Resolution ToolKit (MIALSRTK) consists of a set of C++ and Python processing and workflow tools necessary to perform motion-robust super-resolution fetal…

  • superres-mrimri · super-resolution

    Portable, modular, reusable, and reproducible processing pipeline software for fetal brain MRI super-resolution

sources
  1. api.github.com/repos/daviddmc/STRESS
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2023-11-02, 17 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/37.json→ .entries["stress"]

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