High-dimensional fast convolutional framework (HICU) for calibrationless MRI.

High-dimensional fast convolutional framework (HICU) for calibrationless MRI.
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DOI:
10.1002/mrm.28721
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发表时间:
2021-09
影响因子:
3.3
通讯作者:
Ahmad R
Ahmad R
中科院分区:
医学3区
文献类型:
--
作者:
Zhao S;Potter LC;Ahmad R

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提出一种用于加速、无校准磁共振图像 (Cl-MRI) 重建的计算程序,该程序快速、内存高效且可扩展到高维成像。 Cl-MRI 方法可以实现高加速率和灵活的采样模式,但其临床应用受到计算复杂性和大内存占用的限制。所提出的计算过程,高维快速卷积框架(HICU),提供了未采样 k 空间点的快速、内存高效恢复。为了进行演示,HICU 应用于 6 个 2D T2 加权大脑、7 个 2D 心脏电影、5 个 3D 膝关节和 1 个多镜头扩散加权成像 (MSDWI) 数据集。 2D 成像结果表明,与其他 Cl-MRI 方法相比,HICU 可以在不牺牲成像质量的情况下提供一到两个数量级的计算加速。 2D 电影和 3D 成像结果表明,HICU 中包含的计算加速技术的计算时间与基于 SENSE 的压缩感知方法相当,信号误差比提高了 3 dB,感知质量更好。 MSDWI 结果证明了 HICU 对于具有挑战性的多镜头回波平面成像应用的可行性。所提出的方法 HICU 提供了高效的计算和可扩展性以及对各种 MRI 应用的可扩展性。
To present a computational procedure for accelerated, calibrationless magnetic resonance image (Cl-MRI) reconstruction that is fast, memory efficient, and scales to high-dimensional imaging. Cl-MRI methods can enable high acceleration rates and flexible sampling patterns, but their clinical application is limited by computational complexity and large memory footprint. The proposed computational procedure, HIgh-dimensional fast ConvolUtional framework (HICU), provides fast, memory-efficient recovery of unsampled k-space points. For demonstration, HICU is applied to six 2D T2-weighted brain, seven 2D cardiac cine, five 3D knee, and one multi-shot diffusion weighted imaging (MSDWI) datasets. The 2D imaging results show that HICU can offer one to two orders of magnitude computation speedup compared to other Cl-MRI methods without sacrificing imaging quality. The 2D cine and 3D imaging results show that the computational acceleration techniques included in HICU yield computing time on par with SENSE-based compressed sensing methods with up to 3 dB improvement in signal-to-error ratio and better perceptual quality. The MSDWI results demonstrate the feasibility of HICU for a challenging multi-shot echo-planar imaging application. The presented method, HICU, offers efficient computation and scalability as well as extendibility to a wide variety of MRI applications.
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