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pith:C6KLUDR5

pith:2026:C6KLUDR5CO4OM6F3PLQ5II7R7N
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MedCore: Boundary-Preserving Medical Core Pruning for MedSAM

Cenwei Zhang, Lei You, Suncheng Xiang

MedCore prunes MedSAM parameters by 60 percent while preserving boundary fidelity through dual-intervention scoring and logit-level boundary leverage.

arxiv:2605.13688 v1 · 2026-05-13 · cs.CV · cs.LG

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Claims

C1strongest claim

On polyp segmentation benchmarks, MedCore reduces parameters by 60.0% and FLOPs by 58.4% while achieving Dice 0.9549, Boundary F1 0.6388, and HD95 5.14 after recovery fine-tuning. It also reaches 86.6% parameter reduction with strong boundary quality.

C2weakest assumption

That the dual-intervention score and boundary-aware Fisher estimation correctly identify preservable structures without hidden degradation, and that the boundary leverage principle accurately predicts and controls compression-induced boundary displacement in practice.

C3one line summary

MedCore achieves 60% parameter and 58.4% FLOP reduction on MedSAM with Dice 0.9549 and preserved boundary metrics via dual-intervention pruning and a new boundary leverage principle.

References

51 extracted · 51 resolved · 5 Pith anchors

[1] Segment Anything 2023 · arXiv:2304.02643
[2] Segment anything in medical images.Nature Communications, 15:654, 2024 2024
[3] An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale 2021 · arXiv:2010.11929
[4] An image is worth 16x16 words: Transformers for image recognition at scale 2021
[5] Customized segment anything model for medical image segmentation, 2023 2023
Receipt and verification
First computed 2026-05-18T02:44:16.975916Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

1794ba0e3d13b8e678bb7ae1d423f1fb4309624c885f1f2f9ee0f5349e22a4b4

Aliases

arxiv: 2605.13688 · arxiv_version: 2605.13688v1 · doi: 10.48550/arxiv.2605.13688 · pith_short_12: C6KLUDR5CO4O · pith_short_16: C6KLUDR5CO4OM6F3 · pith_short_8: C6KLUDR5
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/C6KLUDR5CO4OM6F3PLQ5II7R7N \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 1794ba0e3d13b8e678bb7ae1d423f1fb4309624c885f1f2f9ee0f5349e22a4b4
Canonical record JSON
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    "submitted_at": "2026-05-13T15:42:39Z",
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