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pith:2026:YYUIGAWD5DUCOLO2OMF4JLBBCT
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Warm-Started Reinforcement Learning for Iterative 3D/2D Liver Registration

Abdolrahim Kadkhodamohammadi, Brian R. Davidson, Danail Stoyanov, Evangelos B. Mazomenos, Hanyuan Zhang, Lucas He, Matthew.J Clarkson, Zijie Cheng

A warm-started RL policy performs iterative 6-DoF CT-to-video liver registration and learns its own stopping criterion, reaching 15.70 mm TRE without extra optimization.

arxiv:2604.10245 v2 · 2026-04-11 · cs.CV · physics.med-ph

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Claims

C1strongest claim

Experiments on a public laparoscopic dataset demonstrated that our method achieved an average target registration error (TRE) of 15.70 mm, comparable to supervised approaches with optimization, while achieving faster convergence.

C2weakest assumption

The warm-started RL policy can reliably learn effective 6-DoF rigid transformations and a stopping criterion from the shared encoder features without post-hoc tuning or overfitting to the specific dataset.

C3one line summary

A warm-started discrete-action RL framework for CT-to-video liver registration achieves 15.70 mm average TRE with faster convergence than supervised methods plus optimization.

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First computed 2026-05-21T01:05:18.811077Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

c6288302c3e8e8272dda730bc4ac2114de83365a693a9db42a4f48310bbb6515

Aliases

arxiv: 2604.10245 · arxiv_version: 2604.10245v2 · doi: 10.48550/arxiv.2604.10245 · pith_short_12: YYUIGAWD5DUC · pith_short_16: YYUIGAWD5DUCOLO2 · pith_short_8: YYUIGAWD
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/YYUIGAWD5DUCOLO2OMF4JLBBCT \
  | 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: c6288302c3e8e8272dda730bc4ac2114de83365a693a9db42a4f48310bbb6515
Canonical record JSON
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    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-04-11T14:58:45Z",
    "title_canon_sha256": "00f63f46f2c6f3dc2d0f9c3de92dd1faa4b4a7f651a1b1dd32af409a123169a7"
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