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基于线调频激励的单次激发 MRI 的部分傅里叶变换重建。

Partial Fourier transform reconstruction for single-shot MRI with linear frequency-swept excitation.

机构信息

Department of Electronics Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, State Key Laboratory for Physical Chemistry of Solid Surfaces, Xiamen University, Xiamen, China.

出版信息

Magn Reson Med. 2013 May;69(5):1326-36. doi: 10.1002/mrm.24366. Epub 2012 Jun 15.

Abstract

A novel image encoding approach based on linear frequency-swept excitation has been recently proposed to overcome artifacts induced by various field perturbations in single-shot echo planar imaging. In this article, we develop a new super-resolved reconstruction method for it using the concepts of local k-space and partial Fourier transform. This method is superior to the originally developed conjugate gradient algorithm in convenience, image quality, and stability of solution. Reduced field-of-view is applied to the phase encoding direction to further enhance the spatial resolution and field perturbation immunity of the image obtained. Effectiveness of this new combined reconstruction method is demonstrated with a series of experiments on biological samples. Two single-shot sequences with different encoding features are tested. The results show that this reconstruction method maintains excellent field perturbation immunity and improves fidelity of the images. In vivo experiments on rat indicate that this solution is favorable for ultrafast imaging applications in which severe susceptibility heterogeneities around the tissue-air or tissue-bone interfaces, motion and oblique plane effects usually compromise the echo planar imaging image quality.

摘要

最近提出了一种基于线性扫频激励的新型图像编码方法,以克服单次回波平面成像中各种场干扰引起的伪影。在本文中,我们使用局部 k 空间和部分傅里叶变换的概念为其开发了一种新的超分辨率重建方法。与最初开发的共轭梯度算法相比,该方法在便利性、图像质量和解决方案稳定性方面具有优势。在相位编码方向上应用较小的视野进一步提高了所获得图像的空间分辨率和场干扰免疫力。通过对生物样本的一系列实验验证了这种新的组合重建方法的有效性。测试了两种具有不同编码特征的单次拍摄序列。结果表明,该重建方法保持了出色的场干扰免疫力,并提高了图像的保真度。在大鼠的体内实验表明,该解决方案有利于超快成像应用,其中组织-空气或组织-骨界面周围的严重磁化率各向异性、运动和倾斜平面效应通常会影响回波平面成像的图像质量。

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