直接从欠采样k-space重建低场MRI超分辨图像，提升质量并缩短扫描时间。
Direct low-field MRI super-resolution using undersampled k-space
- 在k空间域直接处理实虚部，恢复缺失频率信息
- 重建图像质量接近全采样结果，优于传统空间域方法
- 首个直接从欠采样k空间实现低场MRI超分辨率的工作
低场磁共振成像（MRI）虽具成本优势，但存在扫描时间长、图像质量差的问题。通过欠采样k空间可加速成像，但超分辨率（SR）与图像质量迁移（IQT）通常依赖空间域后处理。本文提出一种新框架，直接从欠采样低场k空间重建高场类图像。采用k空间双通道U-Net，分别处理欠采样k空间的实部和虚部，以恢复缺失的频率内容。在低场脑部MRI数据上的实验表明，该方法在重构质量上持续优于空间域方法；且欠采样重建结果达到与全采样采集相当的图像质量。据我们所知，这是首个直接从欠采样k空间实现低场MRI SR/IQT的研究。
原文摘要 · Abstract (English)
Low-field magnetic resonance imaging (MRI) provides affordable access to diagnostic imaging but suffers from prolonged acquisition and limited image quality. Accelerated imaging can be achieved with k-space undersampling, while super-resolution (SR) and image quality transfer (IQT) methods typically rely on spatial-domain post-processing. In this work, we propose a novel framework for reconstructing high-field MR like images directly from undersampled low-field k-space. Our approach employs a k-space dual channel U-Net that processes the real and imaginary components of undersampled k-space to restore missing frequency content. Experiments on low-field brain MRI demonstrate that our k-space-driven image enhancement consistently outperforms the counterpart spatial-domain method. Furthermore, reconstructions from undersampled k-space achieve image quality comparable to full k-space acquisitions. To the best of our knowledge, this is the first work that investigates low-field MRI SR/IQT directly from undersampled k-space.
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