RRepoGEO

REPOGEO REPORT · LITE

OpenGVLab/SAM-Med2D

Default branch main · commit bfd2b93b · scanned 6/29/2026, 12:23:14 PM

GitHub: 1,125 stars · 110 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
59 /100
Needs work
Category recall
1 / 2
Avg rank #4.0 when recommended
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface OpenGVLab/SAM-Med2D, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • hightopics#1
    Add relevant topics for medical image segmentation

    Why:

    COPY-PASTE FIX
    medical-imaging, image-segmentation, sam, segment-anything-model, deep-learning, computer-vision, medical-ai, foundation-model
  • mediumreadme#2
    Add a concise, descriptive opening sentence to the README

    Why:

    CURRENT
    The README starts with `# SAM-Med2D [Paper]` followed by badges.
    COPY-PASTE FIX
    SAM-Med2D is the official implementation of a specialized Segment Anything Model (SAM) for highly accurate 2D medical image segmentation, trained on the largest curated medical image dataset to date.
  • lowhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://openxlab.org.cn/apps/detail/GMAI/SAM-Med2D

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
1 / 2
50% of queries surface OpenGVLab/SAM-Med2D
Avg rank
#4.0
Lower is better. #1 = top recommendation.
Share of voice
5%
Of all named tools, what % are you?
Top rival
MONAI
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. MONAI · recommended 2×
  2. nnU-Net · recommended 1×
  3. DeepMind's AlphaFold · recommended 1×
  4. TransUNet · recommended 1×
  5. Swin-UNet · recommended 1×
  • CATEGORY QUERY
    How can I achieve highly accurate segmentation across a vast range of medical imaging data?
    you: not recommended
    AI recommended (in order):
    1. MONAI
    2. nnU-Net
    3. DeepMind's AlphaFold
    4. TransUNet
    5. Swin-UNet
    6. PyTorch
    7. Albumentations
    8. TorchIO
    9. TensorFlow/Keras
    10. imgaug
    11. 3D Slicer
    12. DeepInfer Extension
    13. ITK-SNAP

    AI recommended 13 alternatives but never named OpenGVLab/SAM-Med2D. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best pre-trained foundation models for medical image analysis and segmentation tasks?
    you: #4
    AI recommended (in order):
    1. MONAI
    2. Segment Anything Model (SAM)
    3. MedSAM
    4. SAM-Med2D ← you
    5. UNETR
    6. Swin UNETR
    7. DynUNet
    8. nnUNet
    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of OpenGVLab/SAM-Med2D?
    pass
    AI named OpenGVLab/SAM-Med2D explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts OpenGVLab/SAM-Med2D in production, what risks or prerequisites should they evaluate first?
    pass
    AI named OpenGVLab/SAM-Med2D explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo OpenGVLab/SAM-Med2D solve, and who is the primary audience?
    pass
    AI named OpenGVLab/SAM-Med2D explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of OpenGVLab/SAM-Med2D. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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HTML
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OpenGVLab/SAM-Med2D — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite