pith:MPL5JT5L
S4M: 4-points to Segment Anything
S4M augments SAM to treat four points as relational shape cues rather than isolated clicks for more accurate medical segmentation.
arxiv:2503.05534 v3 · 2025-03-07 · cs.CV
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Claims
Across eight datasets in ultrasound and surgical endoscopy, S4M improves segmentation by +3.42 mIoU over a strong SAM baseline at equal prompt budget. An annotation study with three clinicians further shows that major/minor prompts enable faster annotation.
That major/minor axis endpoints can be identified consistently and with low inter-annotator variability by clinicians across diverse medical images without introducing new sources of error or requiring extra training.
S4M augments SAM with role-specific embeddings for 4-point prompts and a canvas pretext task, yielding +3.42 mIoU gains on eight medical datasets and faster clinician annotation.
Receipt and verification
| First computed | 2026-05-25T02:01:02.696037Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/MPL5JT5L6K6ZVKN5C52TMYHPDK \
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# expect: 63d7d4cfabf2bd9aa9bd17753660ef1aa66a530b492bbb679398f013e77bb138
Canonical record JSON
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