Noise behavior in gridding reconstruction

C. Mosquera, Pablo Irarrazabal, D. Nishimura
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引用次数: 4

Abstract

The paper addresses the properties of the noise in gridding reconstruction, an algorithm for reconstruction from nonuniform samples. Sequences with time-varying gradients, such as spiral or projection reconstruction (PR) techniques, are being increasingly used in magnetic resonance imaging (MRI). Since these techniques sample k-space nonuniformly, some kind of algorithm is needed to map the data onto a Cartesian frame to allow an inverse Fourier transform through an FFT. The authors present an analytical characterization of the image noise after gridding and inverse Fourier transform for the most popular sampling techniques used in MRI.
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网格重建中的噪声行为
本文讨论了非均匀样本重构算法网格重构中噪声的性质。具有时变梯度的序列,如螺旋或投影重建(PR)技术,在磁共振成像(MRI)中得到越来越多的应用。由于这些技术对k空间的采样是非均匀的,因此需要某种算法将数据映射到笛卡尔坐标系上,以便通过FFT进行傅里叶反变换。作者提出了一个分析表征后的图像噪声网格和傅里叶反变换最流行的采样技术在MRI中使用。
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