Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, School of Electronic Science and Engineering, Xiamen University, Xiamen 361005, China.
Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China.
J Magn Reson. 2020 Mar;312:106690. doi: 10.1016/j.jmr.2020.106690. Epub 2020 Jan 30.
Diffusion weighted imaging (DWI) is a unique examining method in tumor diagnosis, acute stroke evaluation. Single-shot echo planar imaging is currently conventional method for DWI. However, single-shot DWI suffers from image distortion, blurring and low spatial resolution. Although multi-shot DWI improves image resolution, it brings phase variations among different shots at the same time. In this paper, we introduce a smooth phase constraint of each shot image into multi-shot navigator-free DWI reconstruction by imposing the low-rankness of Hankel matrix constructed from the k-space data. Furthermore, we exploit the partial sum minimization of singular values to constrain the low-rankness of Hankel matrix. Results on brain imaging data show that the proposed method outperforms the state-of-the-art methods in terms of artifacts removal and our method potentially has the ability to reconstruct high number of shot of DWI.
扩散加权成像（DWI）是肿瘤诊断、急性中风评估中的一种独特检查方法。单次激发回波平面成像目前是 DWI 的常规方法。然而，单次激发 DWI 存在图像变形、模糊和空间分辨率低的问题。虽然多shot DWI 提高了图像分辨率，但它同时会在不同的激发中产生相位变化。在本文中，我们通过对从 k 空间数据构建的 Hankel 矩阵施加低秩性，将每幅图像的平滑相位约束引入到无导航多 shot DWI 重建中。此外，我们利用奇异值的部分和最小化来约束 Hankel 矩阵的低秩性。脑部成像数据的实验结果表明，该方法在去除伪影方面优于现有方法，并且该方法有可能重建更多的 DWI 激发次数。
