用隐式神经表示联合重建多回波胎儿T2图，提升低场强下的成像质量。
Physics-Informed Joint Multi-TE Super-Resolution with Implicit Neural Representation for Robust Fetal T2 Mapping
- 通过隐式神经表示联合多回波数据，实现运动伪影抑制
- 在0.55T下首次实现活体胎儿T2映射，精度达当前最优
- 适用于低场强胎儿脑成像，可减少扫描层数
胎儿脑MRI中的T2映射有助于表征发育中的大脑，尤其在中低场强（0.55T）下，因T2衰减较慢更具优势。然而，胎儿MRI依赖多个运动伪影严重的厚层堆叠采集，需进行层到体积重建（SVR）以获得高分辨率3D图像。传统T2映射需在每个回波时间（TE）重复采集堆叠，导致扫描时间长且对运动敏感。本文提出一种联合跨回波重建的方法，结合隐式神经表示与物理信息正则化（建模T2衰减），实现多回波间信息共享，同时保持解剖结构与定量T2准确性。在模拟胎儿脑及体内成人数据集（含胎儿样运动）上表现优于现有方法，并首次展示0.55T下的活体胎儿T2映射结果。研究证明可通过利用解剖冗余，减少每回波时间的采集层数。
原文摘要 · Abstract (English)
T2 mapping in fetal brain MRI has the potential to improve characterization of the developing brain, especially at mid-field (0.55T), where T2 decay is slower. However, this is challenging as fetal MRI acquisition relies on multiple motion-corrupted stacks of thick slices, requiring slice-to-volume reconstruction (SVR) to estimate a high-resolution (HR) 3D volume. Currently, T2 mapping involves repeated acquisitions of these stacks at each echo time (TE), leading to long scan times and high sensitivity to motion. We tackle this challenge with a method that jointly reconstructs data across TEs, addressing severe motion. Our approach combines implicit neural representations with a physics-informed regularization that models T2 decay, enabling information sharing across TEs while preserving anatomical and quantitative T2 fidelity. We demonstrate state-of-the-art performance on simulated fetal brain and in vivo adult datasets with fetal-like motion. We also present the first in vivo fetal T2 mapping results at 0.55T. Our study shows potential for reducing the number of stacks per TE in T2 mapping by leveraging anatomical redundancy.
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