Pith Number

pith:K3FPPPQW

pith:2026:K3FPPPQWRTXH34KHOZBD4T5BBQ

not attested not anchored not stored refs resolved

CoGE: Sim-to-Real Online Geometric Estimation for Monocular Colonoscopy

Beilei Cui, Hongliang Ren, Liangjing Shao

A model trained only on simulated colonoscopy images reaches state-of-the-art depth and 3D reconstruction accuracy on real patient data.

arxiv:2605.13038 v1 · 2026-05-13 · cs.CV · cs.AI

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\pithnumber{K3FPPPQWRTXH34KHOZBD4T5BBQ}

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

the proposed model solely trained on simulated data achieves state-of-the-art performance in geometric estimation for both simulated and realistic scenes

C2weakest assumption

That the illumination-aware supervision module based on Retinex theory and the structure-aware perception module based on wavelet decomposition are sufficient to bridge the large feature gap caused by artifacts and illumination differences between simulated and real colonoscopy data.

C3one line summary

CoGE achieves state-of-the-art monocular geometric estimation in colonoscopy by training solely on simulated data via an illumination-aware Retinex-based module and a wavelet-based structure-aware module.

References

18 extracted · 18 resolved · 1 Pith anchors

[1] Medical image analysis90, 102956 (2023) 2023

[2] In: International Conference on Medical Image Computing and Computer-Assisted Intervention 2024

[3] arXiv preprint arXiv:2506.24074 (2025) 2025

[4] In: International Conference on Medical Image Computing and Computer-Assisted Intervention 2025

[5] Medical image analysis70, 101990 (2021) 2021

Formal links

1 machine-checked theorem link

Receipt and verification

First computed	2026-05-18T03:08:59.593157Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

56caf7be168cee7df14776423e4fa10c1f21048b672ef7e6212df606898e4f41

Aliases

arxiv: 2605.13038 · arxiv_version: 2605.13038v1 · doi: 10.48550/arxiv.2605.13038 · pith_short_12: K3FPPPQWRTXH · pith_short_16: K3FPPPQWRTXH34KH · pith_short_8: K3FPPPQW

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Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/K3FPPPQWRTXH34KHOZBD4T5BBQ \
  | 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: 56caf7be168cee7df14776423e4fa10c1f21048b672ef7e6212df606898e4f41

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "5ccf32e9e7e58e351e4b94b43c65cffc4123c74ca66b86ab8c2185494ae85ee0",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-13T05:46:39Z",
    "title_canon_sha256": "affdbaec32533d47d1a42b53fdd925417acea69f9005f53e73ff663e5fce8e9b"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13038",
    "kind": "arxiv",
    "version": 1
  }
}