# YichiZhang98/SAM4MIS

Segment Anything Model for Medical Image Segmentation:  Open-Source Project Summary

Repository: https://github.com/YichiZhang98/SAM4MIS
Canonical: https://ross.abutalabs.com/products/sam4mis
License Family: other
Last push: 2026-04-30T07:11:08+00:00

## Health v2 (maintenance only)
Score: 66/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 80, release rhythm 35, longevity 87
- inputs: {"age_days": 1225, "days_push": 125, "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 1122, forks 80 (observed 2026-08-28T04:03:40.053412+00:00)

## What it is
A curated research repository tracking papers, surveys, and datasets on applying the Segment Anything Model (SAM/SAM2/SAM3) and other foundation models to medical image segmentation. It includes literature reviews, benchmarking surveys, and links to CVPR workshops.

## Use cases
- find papers on SAM for medical image segmentation
- survey foundation models for biomedical image analysis
- find datasets for medical segmentation model development
- research promptable segmentation in healthcare
- keep up with SAM2 and SAM3 medical applications

## When to choose
- you need an up-to-date literature map of SAM-based medical segmentation research
- you are writing a survey or literature review on foundation models in medical imaging
- you want curated datasets and workshop resources for biomedical segmentation

## When to avoid
- you need ready-to-run segmentation code or a production library
- you want a general-purpose image segmentation tool rather than research references
- you need clinical-grade, validated medical software

## Facets
- artifact type: learning-resource
- maturity: active
- function: image-processing, computer-vision, machine-learning
- domain: healthcare, computer-vision, deep-learning, tutorials
- platform: python, cross-platform
- tags: segment-anything, medical-imaging, survey, paper-collection, sam, segmentation, gpu

## Member repositories
- YichiZhang98/SAM4MIS (main) score 66

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:40.053412+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 2026-08-30T06:40:55.144928+00:00, confidence not recorded.
  - readme: https://github.com/YichiZhang98/SAM4MIS (fetched 2026-08-28T04:03:40.053412+00:00, sha 2f313a8bf2a6)
- Data as of 2026-08-30T08:39:29.467469+00:00.