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Awesome Diffusion Models In Medical Imaging

A public GitHub collection of survey material and research articles about diffusion models applied to medical imaging, organized by topic and application.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Awesome Diffusion Models In Medical Imaging — OpenViST project profile in AI Models.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use the index when mapping research areas or beginning a literature search; consult the linked papers for their methods and findings.

Who it is for

  • Researchers and students surveying diffusion methods in medical imaging.
  • Readers looking for papers on a specific imaging task or application.

Documented uses

  • Find research papers grouped by medical-imaging application.
  • Start a broader review using linked surveys and challenge reports.
  • Locate the maintainers’ survey on diffusion models in medical imaging.
Before you choose

Requirements & limits

The collection is a public GitHub repository and identifies its license as MIT.

  • The README groups papers into task headings, including segmentation, denoising, reconstruction and image generation.
  • It is an article collection, not a model, codebase for inference or medical-imaging application.
  • The README provides a citation for the maintainers’ survey paper.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Use the collection to survey medical-imaging diffusion research

Find articles by research type or application area in the curated collection.

Before you start

  • Access to the GitHub repository README.

Steps

  1. Open the repository README.

  2. Use its Contents list to select Survey Papers, Challenge Reports, or a Papers application category, such as Denoising, Segmentation, or Reconstruction.

  3. Review the entries listed under the chosen section and follow the linked papers relevant to your topic.

Expected outcome

A starting set of linked research articles organized by topic or application.

Guide limitations

  • The repository is an article collection, not a diffusion-model implementation.
  • The README identifies sections and paper links but does not describe a systematic evaluation or selection workflow.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
11 October 2026
Original website title
amirhossein-kz/Awesome-Diffusion-Models-in-Medical-Imaging · Official homepage title · retained in its source language
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