# JunMa11/SOTA-MedSeg

SOTA medical image segmentation methods based on various challenges

Repository: https://github.com/JunMa11/SOTA-MedSeg
Canonical: https://ross.abutalabs.com/products/sota-medseg
License Family: other
Topics: medical, image, segmentation
Last push: 2023-12-12T02:58:36+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3406, "days_push": 995, "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 1676, forks 205 (observed 2026-08-28T04:05:20.684949+00:00)

## What it is
A curated list of state-of-the-art medical image segmentation methods organized by MICCAI and other segmentation challenges. It summarizes each challenge's segmentation target, image modality, dataset size, and the winning network architecture.

## Use cases
- find state-of-the-art methods for brain tumor segmentation
- compare winning architectures across medical segmentation challenges
- research baseline models for CT and MRI organ segmentation
- find datasets for cardiac MRI segmentation
- survey U-Net variants used in medical imaging competitions
- pick a starting model for abdominal organ segmentation

## When to choose
- you need a survey of top-performing medical segmentation models
- you are choosing a baseline architecture for a medical imaging task
- you want links to challenge datasets and leaderboards

## When to avoid
- you need runnable code or a maintained library rather than a reference list
- you need non-medical image segmentation resources
- you need methods newer than the list's last update

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: image-processing, machine-learning, deep-learning
- domain: healthcare, computer-vision, machine-learning, awesome-lists
- platform: cross-platform
- tags: medical-imaging, segmentation, curated-list, challenges, miccai, research

## Member repositories
- JunMa11/SOTA-MedSeg (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:20.684949+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 2026-08-30T03:41:38.900136+00:00, confidence not recorded.
  - readme: https://github.com/JunMa11/SOTA-MedSeg (fetched 2026-08-28T04:05:20.684949+00:00, sha b35762fb0e0e)
- Data as of 2026-08-30T08:39:29.467469+00:00.