IEEE Trans Biomed Eng. 2023 Dec;70(12):3425-3435. doi: 10.1109/TBME.2023.3288031. Epub 2023 Nov 21.
Multi-shot interleaved echo planer imaging (Ms-iEPI) can obtain diffusion-weighted images (DWI) with high spatial resolution and low distortion, but suffers from ghost artifacts introduced by phase variations between shots. In this work, we aim at solving the ms-iEPI DWI reconstructions under inter-shot motions and ultra-high b-values.
An iteratively joint estimation model with paired phase and magnitude priors is proposed to regularize the reconstruction (PAIR). The former prior is low-rankness in the k-space domain. The latter explores similar edges among multi-b-value and multi-direction DWI with weighted total variation in the image domain. The weighted total variation transfers edge information from the high SNR images (b-value = 0) to DWI reconstructions, achieving simultaneously noise suppression and image edges preservation.
Results on simulated and in vivo data show that PAIR can remove inter-shot motion artifacts very well (8 shots) and suppress the noise under the ultra-high b-value (4000 s/mm) significantly.
The joint estimation model PAIR with complementary priors has a good performance on challenging reconstructions under inter-shot motions and a low signal-to-noise ratio.
PAIR has potential in advanced clinical DWI applications and microstructure research.
多回合交错回波平面成像（Ms-iEPI）可获取具有高空间分辨率和低失真的扩散加权图像（DWI），但会受到回合间相位变化引起的鬼影伪影的影响。在这项工作中，我们旨在解决回合间运动和超高 b 值下的 ms-iEPI DWI 重建问题。
提出了一种具有相位和幅度先验配对的迭代联合估计模型来对重建进行正则化（PAIR）。前者的先验条件是 k 空间域中的低秩性。后者通过图像域中的加权全变分，探索多 b 值和多方向 DWI 之间的相似边缘。加权全变分将来自高 SNR 图像（b 值=0）的边缘信息传递到 DWI 重建中，从而同时实现噪声抑制和图像边缘保留。
模拟和体内数据的结果表明，PAIR 可以很好地去除回合间运动伪影（8 回合），并在超高 b 值（4000 s/mm）下显著抑制噪声。
具有互补先验的联合估计模型 PAIR 在回合间运动和低信噪比下的挑战性重建中表现良好。
PAIR 具有在高级临床 DWI 应用和微观结构研究中的潜力。
