pith:JJQ2ZVBE
Energy-based Tissue Manifolds for Longitudinal Multiparametric MRI Analysis
A fixed energy function learned from one baseline multiparametric MRI scan tracks how voxel intensity vectors shift in sequence space during follow-up imaging.
arxiv:2604.07180 v2 · 2026-04-08 · cs.CV · cs.AI
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\pithnumber{JJQ2ZVBEDZMH7CXLR3BHXQ3NUX}
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Claims
In a paediatric case with later recurrence, follow-up scans show progressive deviation in energy and directional displacement in sequence space toward the baseline tumour-associated regime before clear radiological reappearance.
The baseline energy manifold learned from the initial scan accurately represents stable tissue regimes that persist and can be used to detect meaningful changes in subsequent scans without being affected by imaging variations or normal tissue evolution.
A patient-specific energy manifold learned from baseline multiparametric MRI provides a geometric reference system for tracking longitudinal tissue changes through energy and displacement analysis in sequence space.
Formal links
Receipt and verification
| First computed | 2026-05-22T01:04:01.759810Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
4a61acd4241e587f8aeb8ec27bc36da5f1379b04fad05095a92668144b84d009
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/JJQ2ZVBEDZMH7CXLR3BHXQ3NUX \
| 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: 4a61acd4241e587f8aeb8ec27bc36da5f1379b04fad05095a92668144b84d009
Canonical record JSON
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