论文标题

SMS重建的超参数的优化

Optimization of hyperparameters for SMS reconstruction

论文作者

Muftuler, L. Tugan, Arpinar, Volkan Emre, Koch, Kevin, Bhave, Sampada, Yang, Baolian, Kaushik, Sivaram, Banerjee, Suchandrima, Nencka, Andrew

论文摘要

同时多板(SMS)成像通过同时激发多个图像切片来加速MRI数据采集。然后使用数学模型分离重叠的切片。 SMS重建中使用的几个参数会影响最终图像的质量。因此,找到一组最佳的重建参数集对于确保SMS加速度不会显着降低产生的图像质量至关重要。 梯度回声回声平面成像(EPI)数据是通过志愿者的一系列SMS加速因子获取的。使用两个头圈(一个48通道阵列和一个较小的32通道阵列)收集图像。这些线圈的数据使用一系列线圈压缩因子和重建内核参数对离线进行了重建。图像重建使用了混合空间(KY-X),外部校准的线圈片片的固定方法。将所得的SMS图像与没有SMS获取的相同的EPI数据进行了比较。还进行了功能性MRI(fMRI)实验,并比较了具有不同线圈压缩水平的数据集之间的组分析结果。 在我们的实验中,具有较小尺寸的32通道线圈的表现优于较大的48通道线圈。通常,较大的校准区域和沿ky方向的小内核大小提高了图像质量。在内核拟合过程中使用正则化具有显着影响。通过最佳选择混合空间中的其他超参数,SMS不敏化算法,线圈压缩导致SMS加速图像的质量降低。同样,fMRI结果的小组分析并未显示线圈压缩对产生图像质量的显着影响。 一旦确定了诸如RF接收线圈和SMS因子之类的实验因素,就需要对SMS重建中使用的超参数进行微调。

Simultaneous multi-slice (SMS) imaging accelerates MRI data acquisition by exciting multiple image slices simultaneously. Overlapping slices are then separated using a mathematical model. Several parameters used in SMS reconstruction impact the quality of final images. Therefore, finding an optimal set of reconstruction parameters is critical to ensure that SMS acceleration does not significantly degrade resulting image quality. Gradient-echo echo planar imaging (EPI) data were acquired with a range of SMS acceleration factors from volunteers. Images were collected using two head coils (a 48-channel array and a smaller 32-channel array). Data from these coils were reconstructed offline using a range of coil compression factors and reconstruction kernel parameters. A hybrid space (ky-x), externally-calibrated coil-by-coil slice unaliasing approach was used for image reconstruction. The resulting SMS images were compared with identical EPI data acquired without SMS. A functional MRI (fMRI) experiment was also performed and group analysis results were compared between data sets reconstructed with different coil compression levels. The 32-channel coil with smaller dimensions outperformed the larger 48-channel coil in our experiments. Generally, a large calibration region and small kernel sizes in ky direction improved image quality. Use of regularization in the kernel fitting procedure had a notable impact. With optimal selection of other hyperparameters in the hybrid space SMS unaliasing algorithm, coil compression caused small reduction in quality in SMS accelerated images. Similarly, group analysis of fMRI results did not show a significant influence of coil compression on resulting image quality. Hyperparameters used in SMS reconstruction need to be fine-tuned once the experimental factors such as the RF receive coil and SMS factor have been determined.

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