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首页> 外文期刊>Quantitative Imaging in Medicine and Surgery >Body coil reference for inverse reconstructions of multi-coil data—the case for real-time MRI
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Body coil reference for inverse reconstructions of multi-coil data—the case for real-time MRI

机译:体线圈参考,用于多线圈数据的逆重建 - 实时MRI的情况

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Real-time magnetic resonance imaging (MRI) or model-based MRI reconstructions of parametric maps require the solution of an ill-posed nonlinear inverse problem. Respective algorithms, e.g., the iteratively regularized Gauss-Newton method, implicitly combine datasets from multiple receive coils. Because these local coils may exhibit complex sensitivity profiles with rather different phase offsets, the numerical optimization may lead to phase singularities which in turn cause “black holes” in magnitude images. The purpose of this work is to develop a method for inverse reconstructions of multi-coil MRI data which avoids the generation of such spatially selective phase singularities. It is proposed to use volumetric body coil data and start the iterative reconstruction of multi-coil data with a reference image which offers proper phase information. In more detail, inverse reconstructions of multi-coil data are initialized with a complex “seed” image which is obtained by a Fast Fourier Transform (FFT) reconstruction of data from a single body coil element. This is accomplished at no additional cost as only very few body coil scans with identical conditions as the multi-coil acquisitions are needed as part of the regular prep scan period. The method is evaluated for anatomical real-time MRI and model-based phase-contrast flow MRI in real-time at 3 T. The proposed method overcomes phase singularities in all cases for arbitrary sets of receive coils. In conclusion, the automatic use of a single body coil reference image is simple, robust, and further improves the reliability of advanced MRI reconstructions from multi-coil data.
机译:参数图的实时磁共振成像(MRI)或基于模型的MRI重建需要解决不良非线性逆问题的解。各种算法,例如迭代正则化高斯 - 牛顿方法,隐含地组合来自多个接收线圈的数据集。因为这些局部线圈可以表现出具有相当不同的相位偏移的复杂敏感性曲线,所以数值优化可能导致相奇点,其又导致幅度图像中的“黑洞”。本作作品的目的是开发一种用于逆重建的多线圈MRI数据的方法,其避免了这种空间选择性相位奇异的产生。建议使用体积体线圈数据并利用提供适当的相位信息的参考图像开始迭代重建的多线圈数据。更详细地,用复杂的“种子”图像初始化多线圈数据的逆重建,该复杂的“种子”图像是通过来自单个体线圈元件的数据的快速傅里叶变换(FFT)重建而获得的复杂的“种子”图像。这是在没有额外的成本下完成的,因为只有在常规预备扫描周期的一部分需要多线圈采集时,只有具有相同条件的体线圈扫描。该方法在3T中实时地评估基于解剖实时MRI和模型的相位对比度流动MRI。该方法在所有情况下克服了任意组接收线圈的所有情况的相奇异。总之,单个主线线圈参考图像的自动使用简单,稳健,并且进一步提高了来自多线圈数据的高级MRI重建的可靠性。

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