波谱学杂志2026，Vol.43Issue(3)：321-338,18.DOI:10.11938/cjmr20263215
物理先验引导的多对比度磁共振重建扩散模型
Physics Guided Multi-contrast Magnetic Resonance Reconstruction Diffusion Model
摘要
Abstract
Multi-contrast MRI allows for the simultaneous acquisition of multiple weighted images,which improves imaging efficiency and provides rich quantitative information.However,reconstructing these images under high undersampling while ensuring anatomical consistency and physical plausibility remains a significant challenge.Existing methods often rely on scarce fully-sampled data or suffer from performance degradation due to domain shift.To address this,we propose a physics-prior-guided diffusion model that encodes MR signal evolution via Bloch equations into a dictionary-matching constraint.This constraint is directly coupled into the reverse sampling process,enabling physical correction of data-driven priors without retraining.Experimental results demonstrate superior generalization performance over supervised and self-supervised approaches,while the estimated parameter maps validate its high quantitative accuracy,highlighting its potential for clinical multi-contrast imaging.关键词
磁共振成像/多对比度成像/扩散模型/无监督学习/物理先验Key words
magnetic resonance imaging(MRI)/multi-contrast imaging/diffusion models/unsupervised learning/physics priors分类
数理科学引用本文复制引用
苏奕霖,刘元元,崔卓须,梁栋..物理先验引导的多对比度磁共振重建扩散模型[J].波谱学杂志,2026,43(3):321-338,18.基金项目
国家自然科学基金(62125111,62476268,62206273) （62125111,62476268,62206273）
广东省多模态无创脑机接口理论与技术重点实验室(2024B1212010010) （2024B1212010010）
深圳市科技计划项目(JCYJ20240813155840052). （JCYJ20240813155840052）
