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pith:IJNFNYZO

pith:2026:IJNFNYZOO25MTWOUIPBQ2TNXCW
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Region-Grounded Report Generation for 3D Medical Imaging: A Fine-Grained Dataset and Graph-Enhanced Framework

Aditya Narayan Sankaran, Cong Huy Nguyen, Guanlin Li, Mai Hong Son, Mai Huy Thong, Noel Crespi, Phi Le Nguyen, Reza Farahbakhsh, Son Dinh Nguyen, Thanh Trung Nguyen, Tuan Dung Nguyen

Graph-based framework with region annotations generates more reliable reports from 3D PET/CT scans.

arxiv:2604.18145 v2 · 2026-04-20 · cs.CV · cs.AI

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Claims

C1strongest claim

Our framework achieves SOTA performance, surpassing existing models by 19.7% in BLEU and 4.7% in ROUGE-L, while achieving a remarkable 45.8% improvement in clinical metrics, indicating enhanced clinical reliability and reduced hallucination.

C2weakest assumption

The assumption that graph-based relational modules accurately capture clinically meaningful dependencies between RoI attributes and that LLM-based extraction for RoI Coverage and RoI Quality Index provides an unbiased measure of report fidelity.

C3one line summary

Introduces the first large-scale 3D PET/CT dataset with fine-grained RoI annotations for Vietnamese and a graph-enhanced HiRRA framework that achieves SOTA report generation by modeling RoI dependencies.

References

3 extracted · 3 resolved · 0 Pith anchors

[1] Sergios Gatidis, Tobias Hepp, Marcel Früh, Christian La Fougère, Konstantin Nikolaou, Christina Pfannen- berg, Bernhard Schölkopf, Thomas Küstner, Clemens Cyran, and Daniel Rubin 2022
[2] arXiv preprint arXiv:2508.04062 , year= 2024
[3] extraction_text 2025

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First computed 2026-05-20T00:01:41.513560Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

425a56e32e76bac9d9d443c30d4db715b2e799655b28e7d78bf7ff177338386f

Aliases

arxiv: 2604.18145 · arxiv_version: 2604.18145v2 · doi: 10.48550/arxiv.2604.18145 · pith_short_12: IJNFNYZOO25M · pith_short_16: IJNFNYZOO25MTWOU · pith_short_8: IJNFNYZO
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/IJNFNYZOO25MTWOUIPBQ2TNXCW \
  | 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: 425a56e32e76bac9d9d443c30d4db715b2e799655b28e7d78bf7ff177338386f
Canonical record JSON
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    "submitted_at": "2026-04-20T12:08:21Z",
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