Pith Number

pith:HMM5C53J

pith:2026:HMM5C53JGQESFSQDJ6BRDS7TZA

not attested not anchored not stored refs resolved

CineMesh4D: Personalized 4D Whole Heart Reconstruction from Sparse Cine MRI

Ching-Hui Sia, Lei Li, Mark Y Chan, Xiaohan Yuan, Xiaoyue Liu

CineMesh4D reconstructs personalized 4D whole-heart meshes directly from sparse multi-view 2D cine MRI.

arxiv:2605.13994 v1 · 2026-05-13 · cs.CV · cs.AI

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\usepackage{pith}
\pithnumber{HMM5C53JGQESFSQDJ6BRDS7TZA}

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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

✓ Portable graph bundle live · download bundle · merged state

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

In quantitative and qualitative evaluations, CineMesh4D outperforms existing approaches in terms of reconstruction quality and motion consistency, providing a practical pathway for personalized real-time cardiac assessment.

C2weakest assumption

The differentiable rendering loss can reliably supervise accurate 3D+t whole-heart meshes from sparse multi-view 2D contours, and the dual-context temporal block sufficiently captures high-dimensional sequential cardiac patterns without additional constraints or data.

C3one line summary

CineMesh4D reconstructs personalized 4D whole-heart meshes directly from multi-view 2D cine MRI via cross-domain mapping with differentiable rendering and dual-context temporal blocks.

References

27 extracted · 27 resolved · 0 Pith anchors

[1] Medical image analysis74, 102228 (2021) 2021

[2] In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition 2019

[3] In: Interna- tional Conference on Functional Imaging and Modeling of the Heart 2025

[4] Medical Image Analysis104, 103630 (2025) 2025

[5] arXiv preprint arXiv:1912.00367 (2019) 1912

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-17T23:39:13.219119Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

3b19d17769340922ca034f8311cbf3c82ce5441f5ef12d5e725d55b081324e6f

Aliases

arxiv: 2605.13994 · arxiv_version: 2605.13994v1 · doi: 10.48550/arxiv.2605.13994 · pith_short_12: HMM5C53JGQES · pith_short_16: HMM5C53JGQESFSQD · pith_short_8: HMM5C53J

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/HMM5C53JGQESFSQDJ6BRDS7TZA \
  | 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: 3b19d17769340922ca034f8311cbf3c82ce5441f5ef12d5e725d55b081324e6f

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "d53e5a43fe55139fe3c3bbbb8722ffeba7c6b107e4d0bff9b9f2cb736f6a21c2",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-13T18:05:08Z",
    "title_canon_sha256": "17d59f814b6a12f99747b6024d5a1541599317e5c4f0e76156ac0de87814024f"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13994",
    "kind": "arxiv",
    "version": 1
  }
}