# JunMa11/MICCAI-OpenSourcePapers

MICCAI 2019-2023 Open Source Papers

Repository: https://github.com/JunMa11/MICCAI-OpenSourcePapers
Canonical: https://ross.abutalabs.com/products/miccai-opensourcepapers
License: Apache-2.0
License Family: permissive
Topics: deep-learning, medical-imaging
Last push: 2023-11-01T20:25:08+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2519, "days_push": 1036, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1293, forks 224 (observed 2026-08-28T04:04:16.161821+00:00)

## What it is
A curated list of MICCAI conference papers (2019-2023) that have open-source code, with links to each paper's repository. It serves as a reference index for researchers in deep learning-based medical image analysis.

## Use cases
- find open-source implementations of MICCAI medical imaging papers
- discover deep learning papers for medical image segmentation
- survey recent medical image analysis research with code
- find baselines for medical imaging research
- keep up with MICCAI conference papers

## When to choose
- you need open-source code from MICCAI papers for medical imaging
- you're doing a literature review of medical image analysis
- you want reproducible deep learning research in healthcare

## When to avoid
- you need a runnable tool or library rather than a paper index
- you're looking for papers from venues other than MICCAI

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: deep-learning, documentation
- domain: deep-learning, healthcare, tutorials
- platform: cross-platform
- tags: awesome-list, medical-imaging, miccai, papers, curated-list

## Member repositories
- JunMa11/MICCAI-OpenSourcePapers (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:16.161821+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 2026-08-30T04:54:07.765825+00:00, confidence not recorded.
  - readme: https://github.com/JunMa11/MICCAI-OpenSourcePapers (fetched 2026-08-28T04:04:16.161821+00:00, sha cba015d5ad3b)
- Data as of 2026-08-30T08:39:29.467469+00:00.