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Asymptotic SNR-performance of some image combination techniques for phased-array MRI

机译:相控阵MRI的一些图像组合技术的渐近SNR性能

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Phased-array magnetic resonance imaging technology is currently flourishing with the promise of obtaining a profitable trade-off between image quality and image acquisition speed. The image quality is generally measured in terms of the signal-to-noise ratio (SNR), which is often calculated using samples taken from the reconstructed image. In this paper, we derive analytical expressions for the asymptotic SNR in the final image for three different phased-array image combination methods, namely: (1) sum-of-squares, (2) singular value decomposition, and (3) normalized coil averaging. The SNR expressions are expressed in terms of the statistics of the noise in the measurements, as well as the coil sensitivity coefficients. Our results can facilitate a better understanding for the phased-array image combination problem, as well as provide a tool for the optimal design of coils.
机译:相控阵磁共振成像技术目前正在蓬勃发展,并有望在图像质量和图像采集速度之间取得有利的平衡。通常根据信噪比(SNR)来测量图像质量,通常使用从重建图像中获取的样本来计算信噪比(SNR)。在本文中,我们针对三种不同的相控阵图像组合方法得出了最终图像中渐近SNR的解析表达式,即:(1)平方和,(2)奇异值分解和(3)归一化线圈平均。 SNR表达式以测量中的噪声统计信息以及线圈灵敏度系数表示。我们的结果可以帮助您更好地理解相控阵图像组合问题,并为线圈的最佳设计提供工具。

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