使用部分可分离函数和加权空间平滑正则化的高分辨率心脏磁共振成像。
High-resolution cardiac MRI using partially separable functions and weighted spatial smoothness regularization.
作者信息
Christodoulou Anthony G, Brinegar Cornelius, Haldar Justin P, Zhang Haosen, Wu Yi-Jen L, Foley Lesley M, Hitchens T, Ye Qing, Ho Chien, Liang Zhi-Pei
机构信息
Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, 1406 West Green Street, Urbana, IL 61801, USA.
出版信息
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:871-4. doi: 10.1109/IEMBS.2010.5627889.
Imaging of cardiac morphology and functions in high spatiotemporal resolution using MRI is a challenging problem due to limited imaging speed and the inherent tradeoff between spatial resolution, temporal resolution, and signal-to-noise ratio (SNR). The partially separable function (PSF) model has been shown to achieve high spatiotemporal resolution but can lead to noisy reconstructions. This paper proposes a method to improve the SNR and reduce artifacts in PSF-based reconstructions through the use of anatomical constraints. These anatomical constraints are obtained from a high-SNR image of composite (k, t)-space data (summed along the time axis) and used to regularize the PSF reconstruction. The method has been evaluated on experimental data of rat hearts to achieve 390 εm in-plane resolution and 15 ms temporal resolution.
由于成像速度有限以及空间分辨率、时间分辨率和信噪比（SNR）之间固有的权衡，使用磁共振成像（MRI）以高时空分辨率对心脏形态和功能进行成像一直是一个具有挑战性的问题。部分可分离函数（PSF）模型已被证明可以实现高时空分辨率，但可能会导致重建图像出现噪声。本文提出了一种方法，通过使用解剖学约束来提高基于PSF重建的SNR并减少伪影。这些解剖学约束是从复合（k，t）空间数据（沿时间轴求和）的高SNR图像中获得的，并用于对PSF重建进行正则化。该方法已在大鼠心脏的实验数据上进行评估，以实现390 εm的平面分辨率和15 ms的时间分辨率。
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