pith:NJX472PK
A Plug-and-Play Method for Guided Multi-contrast MRI Reconstruction based on Content/Style Modeling
A content/style model enables plug-and-play guided reconstruction of undersampled MRI by replacing aliased content from a reference contrast scan.
arxiv:2409.13477 v9 · 2024-09-20 · eess.IV · cs.CV · physics.med-ph
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Claims
PnP-CoSMo enabled up to 32.6% greater acceleration over non-guided reconstruction at given SSIM on two in-house multi-coil datasets, showing equivalent or superior quality and greater generalizability compared to end-to-end methods.
The content/style disentanglement learned from partially paired image-domain datasets accurately separates contrast-independent and contrast-specific factors such that direct replacement of aliased content with reference content, combined with data consistency, yields stable high-quality reconstructions without paired k-space training data.
PnP-CoSMo is a modular plug-and-play iterative reconstruction technique that disentangles content and style in multi-contrast MR images to guide reconstruction from reference scans without k-space training data.
Receipt and verification
| First computed | 2026-06-08T01:04:59.598135Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
6a6fcfe9ea288870c2a36bd55cf607adf671ac2c60535ef306ea59af01cb65b2
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/NJX472PKFCEHBQVDNPKVZ5QHVX \
| 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: 6a6fcfe9ea288870c2a36bd55cf607adf671ac2c60535ef306ea59af01cb65b2
Canonical record JSON
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