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UniRes

imported

software/unires

Unified super-resolution and denoising of medical images in PyTorch

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

UniRes project image
GitHub preview card for brudfors/UniRes. 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
active
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Repository
github.com/brudfors/UniRes
Documentation
unknown
Tags
computed-tomography · denoising · magnetic-resonance-imaging · medical-imaging · super-resolution
Regulatory
unknown
built by · 4

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.

  • DenoMambacomputed-tomography · denoising · medical-imaging

    Official implementation of DenoMamba: A fused state-space model for low-dose CT denoising

  • deepinvdenoising · medical-imaging

    DeepInverse: a PyTorch library for solving imaging inverse problems using deep learning

  • OMEGAcomputed-tomography · medical-imaging

    Open-source multi-dimensional tomographic reconstruction software (OMEGA)

  • preprocessingcomputed-tomography · medical-imaging

    Preprocessing scripts: from dicom to aligned nitfy for SynthRAD2023 Grand Challenge

  • radiocomputed-tomography · medical-imaging

    RadIO is a library for data science research of computed tomography imaging

  • ccnetmagnetic-resonance-imaging · medical-imaging

    Official repository of "Towards Learning Contrast Kinetics with Multi-Condition Latent Diffusion Models"

sources
  1. api.github.com/repos/brudfors/UniRes
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2026-08-03, 94 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/45.json→ .entries["unires"]

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