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Compressed sensing based MR image reconstruction from multiple partial K-space scans

机译:多部分k空间扫描的压缩检测基于MR图像重建

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In Magnetic Resonance Imaging (MRI), signal averaging is an established technique for reducing white Gaussian noise or motion artifacts. Acquiring multiple scans for signal averaging is time consuming. To reduce the data acquisition time, Compressed Sensing (CS) based techniques advocate partial scanning of the K-space only. Instead of using averaging techniques in conjunction with CS based reconstruction, this work proposes a novel formulation that produces extremely accurate reconstruction results. Our method gives the same reconstruction accuracy at 50% K-space sampling as does the conventional signal averaging of the full K-space.
机译:在磁共振成像(MRI)中,信号平均是用于减少白高斯噪声或运动伪影的建立技术。获取多个扫描用于信号平均是耗时的。为了减少数据采集时间,基于压缩的感测(CS)技术仅倡导仅扫描k空间。该工作提出了一种新的制剂,而不是使用基于CS的重建结合使用的平均技术,而不是使用基于CS的重建。我们的方法在50%K空间采样中提供了相同的重建精度,如全k空间的传统信号平均一样。

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