Super-resolved enhancing and edge deghosting (SEED) for spatiotemporally encoded single-shot MRI
Super-resolved enhancing and edge deghosting (SEED) for spatiotemporally encoded single-shot MRI
复制标题
用于时空编码单次 MRI 的超分辨增强和边缘去幻影 (SEED)
DOI：
10.1016/j.media.2015.03.004
复制
发表时间：
2015-07-01
影响因子：
10.9
通讯作者：
Chen, Zhong
中科院分区：
文献类型：
--
作者：
Chen, Lin;Li, Jing;Chen, Zhong
时空编码（SPEN）单次激发磁共振成像是近年来提出的一种超快磁共振成像技术，它利用二次相位轮廓而不是线性相位轮廓来提取空间信息。与回波平面成像（EPI）相比，该技术在抗场不均匀性和化学位移效应方面具有很大的优势。超分辨重建（SR）被用来补偿SPEN图像固有的低分辨率。由于采样率不足，SR图像受到混叠伪影和边缘重影的挑战。现有的超分辨率算法通常会在空间分辨率上做出妥协，以抑制这些不希望出现的伪影。本文提出了一种新的超分辨增强和边缘去重影算法（SEED）。与伪影抑制方法不同，该算法旨在利用混叠伪影与真实的信号之间的关系。基于这种关系，可以在不损失空间分辨率的情况下消除混叠伪影。根据边缘鬼点的特点，采用有限差分和高通滤波的方法提取边缘鬼点的先验知识。该算法将先验知识与压缩感知相结合，有效地消除了边缘重影。在各种情况下的实验证明了种子的鲁棒性。结果表明，与SPEN MRI中最先进的SR重建算法相比，SEED可以提供更好的空间分辨率。理论分析和实验结果也表明，在相同的实验条件下，与传统的k空间编码方法相比，SEED重建的SR图像具有更好的空间分辨率。(C)2015 Elsevier B.V.版权所有。
Spatiotemporally encoded (SPEN) single-shot MRI is an ultrafast MRI technique proposed recently, which utilizes quadratic rather than linear phase profile to extract the spatial information. Compared to the echo planar imaging (EPI), this technique has great advantages in resisting field inhomogeneity and chemical shift effects. Super-resolved (SR) reconstruction is adopted to compensate the inherent low resolution of SPEN images. Due to insufficient sampling rate, the SR image is challenged by aliasing artifacts and edge ghosts. The existing SR algorithms always compromise in spatial resolution to suppress these undesirable artifacts. In this paper, we proposed a novel SR algorithm termed super-resolved enhancing and edge deghosting (SEED). Different from artifacts suppression methods, our algorithm aims at exploiting the relationship between aliasing artifacts and real signal. Based on this relationship, the aliasing artifacts can be eliminated without spatial resolution loss. According to the trait of edge ghosts, finite differences and high-pass filter are employed to extract the prior knowledge of edge ghosts. By combining the prior knowledge with compressed sensing, our algorithm can efficiently reduce the edge ghosts. The robustness of SEED is demonstrated by experiments under various situations. The results indicate that the SEED can provide better spatial resolution compared to state-of-the-art SR reconstruction algorithms in SPEN MRI. Theoretical analysis and experimental results also show that the SR images reconstructed by SEED have better spatial resolution than the images obtained with conventional k-space encoding methods under similar experimental condition. (C) 2015 Elsevier B.V. All rights reserved.