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Multiple-Input–Multiple-Output (MIMO) MRI: Combining Parallel Excitation and Parallel Reception for Enhanced Imaging

机译:多输入多输出(MIMO)MRI:结合并行激励和并行接收以增强成像

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Magnetic resonance imaging (MRI) plays a critical role in visualizing the structure and functions of the human body. In order to accelerate imaging time and improve the image quality, radio-frequency (RF) coil receive arrays which are commonly employed to acquire the magnetic resonance signal. Similarly, multiple transmit coils have been shown to accelerate and refine the RF excitation. In this paper, we investigate the optimization of the total imaging time and image accuracy when considering both the transmit and receive coil arrays; we term this strategy as multiple-input-multiple-output (MIMO) MRI. Our RF pulse design method is modeled by minimizing the excitation errors while simultaneously maximizing the signal-to-noise ratio (SNR) of the reconstructed MR image. It further allows a key tradeoff between the two optimizers. Additionally, multiple acceleration factors, varying numbers of receive coils used, maximum excitation error tolerance, and different excitation patterns are simulated and analyzed in this model. For a given excitation pattern, our method is shown to improve the SNR by 18-130% under certain acceleration schemes, as compared to conventional parallel transmission methods, while simultaneously controlling the excitation error within a desired scope (NRMSE <= 0.12).
机译:磁共振成像(MRI)在可视化人体的结构和功能中起着至关重要的作用。为了加速成像时间并改善图像质量,射频(RF)线圈接收阵列通常用于采集磁共振信号。类似地,已显示多个发射线圈可加速和改善RF激励。在本文中,我们同时考虑发送和接收线圈阵列时,研究了总成像时间和图像精度的优化;我们将此策略称为多输入多输出(MIMO)MRI。我们的RF脉冲设计方法是通过最小化激励误差,同时最大化重构MR图像的信噪比(SNR)来建模的。它还允许在两个优化器之间进行关键的权衡。此外,在此模型中模拟并分析了多个加速因子,使用的接收线圈数量不同,最大激励误差容限以及不同的激励模式。对于给定的激励模式,与传统的并行传输方法相比,我们的方法在某些加速方案下显示出将SNR提高18-130%,同时将激励误差控制在所需范围内(NRMSE <= 0.12)。

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