Self-Supervised Implicit CEST Reconstruction via Physics-Informed Lorentz Encoding
Multi-Pool Chemical Exchange Saturation Transfer (CEST) MRI provides valuable metabolic information but is clinically limited by long acquisition times. Although sparse sampling reduces scanning time, reconstructing high-resolution Z-spectra from limited data remains an ill-posed inverse problem. Conventional interpolation and generic Implicit Neural Rep-resentations (INRs) often lack physical constraints, leading to spectral artifacts and physically invalid signals. To address this, we propose Lorentz Encoding (LE), a physics-informed framework that formulates CEST reconstruction as a self-su
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 51%Multi-resolution enhancement for full-spectrum neural representations →
- LinkedLinked via arxiv author · 85%Dexuan Li →
“Self-Supervised Implicit CEST Reconstruction via Physics-Informed Lorentz Encoding”
- LinkedLinked via arxiv author · 85%Yupeng Wu →
“Self-Supervised Implicit CEST Reconstruction via Physics-Informed Lorentz Encoding”
- LinkedLinked via arxiv author · 85%Chenglong Wang →
“Self-Supervised Implicit CEST Reconstruction via Physics-Informed Lorentz Encoding”
- LinkedLinked via arxiv author · 85%Hanlin Liu →
“Self-Supervised Implicit CEST Reconstruction via Physics-Informed Lorentz Encoding”
- LinkedLinked via arxiv author · 85%Hui Zheng →
“Self-Supervised Implicit CEST Reconstruction via Physics-Informed Lorentz Encoding”
- LinkedLinked via arxiv author · 85%Jianqi Li →
“Self-Supervised Implicit CEST Reconstruction via Physics-Informed Lorentz Encoding”
- LinkedLinked via arxiv author · 85%Guang Yang →
“Self-Supervised Implicit CEST Reconstruction via Physics-Informed Lorentz Encoding”