Compressed sensing of spatial electron paramagnetic resonance imaging.
Compressed sensing of spatial electron paramagnetic resonance imaging.
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DOI：
10.1002/mrm.24966
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发表时间：
2014-09
影响因子：
3.3
通讯作者：
Zweier, Jay L.
中科院分区：
文献类型：
--
作者：
Johnson, David H.;Ahmad, Rizwan;He, Guanglong;Samouilov, Alexandre;Zweier, Jay L.
关键词：
为了提高空间电子顺磁共振成像(EPRI)的图像质量和降低数据需求，提出了一种新的基于压缩传感(CS)的重建方法。提出了一种由图像本身的ℓ-1范数和图像的全变差组成的具有稀疏性提升惩罚项的正则化最小二乘法求解的优化问题。为了便于稀疏信号的恢复，采用了伪随机采样。将这种重建与传统的过滤反投影重建进行比较，以模拟、幻影、分离的大鼠心脏和用顺磁探针标记的小鼠胃肠道。伪随机采样和CS的结合能够在高加速率下生成高保真的EPR图像。对于3D模型成像，基于CS的EPRI在9倍加速时几乎没有视觉退化。在大鼠心脏数据集上，基于CS的EPRI生成高质量图像，速度提高8倍。高分辨率小鼠胃肠道重建显示出空间分辨率的视觉改善和信噪比翻倍。提出了一种新的基于压缩感知的三维EPRI重建方法，该方法具有较高的信噪比，并能减少高度欠采样数据中的伪影。
To improve image quality and reduce data requirements for spatial electron paramagnetic resonance imaging (EPRI) by developing a novel reconstruction approach using compressed sensing (CS). EPRI is posed as an optimization problem, which is solved using regularized least-squares with sparsity promoting penalty terms, consisting of the ℓ1 norms of the image itself and the Total Variation of the image. Pseudo-random sampling was employed to facilitate recovery of the sparse signal. The reconstruction was compared to the traditional Filtered Back-Projection reconstruction for simulations, phantoms, isolated rat hearts, and mouse GI tracts labeled with paramagnetic probes. A combination of pseudo-random sampling and CS was able to generate high-fidelity EPR images at high acceleration rates. For 3D phantom imaging, CS-based EPRI showed little visual degradation at 9-fold acceleration. In rat heart datasets, CS-based EPRI produced high quality images with 8-fold acceleration. A high resolution mouse GI tract reconstruction demonstrated a visual improvement in spatial resolution and a doubling in SNR. A novel 3D EPRI reconstruction utilizing compressed sensing was developed and offers superior SNR and reduced artifacts from highly undersampled data.
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影响因子：
10.2
作者：
HANSEN, PC
通讯作者：
HANSEN, PC
影响因子：
7.4
作者：
Liu, Yangping;Song, Yuguang;De Pascali, Francesco;Liu, Xiaoping;Villamena, Frederick A.;Zweier, Jay L.
通讯作者：
Zweier, Jay L.
影响因子：
2.1
作者：
Beck, Amir;Teboulle, Marc
通讯作者：
Teboulle, Marc
影响因子：
4.8
作者：
Johnson, CA;McGarry, D;Krishna, MC
通讯作者：
Krishna, MC
影响因子：
14.9
作者：
Lustig, Michael;Donoho, David L.;Pauly, John M.
通讯作者：
Pauly, John M.