# fahadshamshad/awesome-transformers-in-medical-imaging

A collection of resources on applications of Transformers in Medical Imaging.

Repository: https://github.com/fahadshamshad/awesome-transformers-in-medical-imaging
Canonical: https://ross.abutalabs.com/products/awesome-transformers-in-medical-imaging
License Family: other
Topics: transformers, vision-transformers, medical-imaging, medical-image-analysis, clinical-report, medical-report-generate, deep-neural-networks, medical-image-segmentation, medical-image-classification, medical-image-detection, medical-image-reconstruction, medical-image-synthesis, medical-image-registration, covid-19, awesome-list, brats2021, brain-tumor-segmentation
Last push: 2026-06-21T11:56:54+00:00

## Health v2 (maintenance only)
Score: 72/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 88, release rhythm 35, longevity 100
- inputs: {"age_days": 1734, "days_push": 73, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1296, forks 195 (observed 2026-08-28T04:04:16.929449+00:00)

## What it is
A curated awesome-list of papers and open-source implementations on applications of Transformers in medical imaging, complementing the authors' survey published in Medical Image Analysis. It organizes resources chronologically across segmentation, classification, reconstruction, registration, synthesis, detection, and clinical report generation.

## Use cases
- find papers on transformers for medical image segmentation
- research vision transformers for radiology report generation
- survey deep learning methods for medical image classification
- find open-source implementations of transformer models for MRI reconstruction
- keep up with latest transformer research in medical imaging
- find resources on medical image registration and synthesis
- literature review for a medical imaging deep learning project

## When to choose
- you need a curated, regularly updated reading list of transformer papers in medical imaging
- you are writing a literature review or survey on transformer-based medical image analysis
- you want links to open-source implementations alongside papers

## When to avoid
- you need runnable software or a library rather than a paper collection
- you need non-transformer deep learning methods for medical imaging
- you need a maintained codebase with a license

## Facets
- artifact type: learning-resource
- maturity: active
- function: deep-learning, machine-learning, documentation
- domain: artificial-intelligence, deep-learning, computer-vision, healthcare, awesome-lists, tutorials
- platform: cross-platform
- tags: awesome-list, transformers, vision-transformers, medical-imaging, medical-image-segmentation, medical-image-classification, medical-image-reconstruction, medical-image-registration, medical-image-synthesis, clinical-report-generation, survey-paper, covid-19, brain-tumor-segmentation

## Member repositories
- fahadshamshad/awesome-transformers-in-medical-imaging (main) score 72

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:16.929449+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:53:57.358540+00:00, confidence not recorded.
  - readme: https://github.com/fahadshamshad/awesome-transformers-in-medical-imaging (fetched 2026-08-28T04:04:16.929449+00:00, sha 3f21eb275039)
- Data as of 2026-08-30T08:39:29.467469+00:00.