Vemuri Prashanthi, Kholmovski Eugene G, Parker Dennis L, Chapman Brian E
UCAIR, Department of Radiology, University of Utah, SLC, USA.
Inf Process Med Imaging. 2005;19:603-14. doi: 10.1007/11505730_50.
Magnetic resonance (MR) images can be acquired by multiple receiver coil systems to improve signal-to-noise ratio (SNR) and to decrease acquisition time. The optimal SNR images can be reconstructed from the coil data when the coil sensitivities are known. In typical MR imaging studies, the information about coil sensitivity profiles is not available. In such cases the sum-of-squares (SoS) reconstruction algorithm is usually applied. The intensity of the SoS reconstructed image is modulated by a spatially variable function due to the non-uniformity of coil sensitivities. Additionally, the SoS images also have sub-optimal SNR and bias in image intensity. All these effects might introduce errors when quantitative analysis and/or tissue segmentation are performed on the SoS reconstructed images. In this paper, we present an iterative algorithm for coil sensitivity estimation and demonstrate its applicability for optimal SNR reconstruction and intensity inhomogeneity correction in phased array MR imaging.
磁共振（MR）图像可以通过多个接收线圈系统采集，以提高信噪比（SNR）并减少采集时间。当线圈灵敏度已知时，可以从线圈数据重建最佳SNR图像。在典型的MR成像研究中，关于线圈灵敏度分布的信息是不可用的。在这种情况下，通常应用平方和（SoS）重建算法。由于线圈灵敏度的不均匀性，SoS重建图像的强度由空间可变函数调制。此外，SoS图像在图像强度方面也具有次优SNR和偏差。当对SoS重建图像进行定量分析和/或组织分割时，所有这些影响都可能引入误差。在本文中，我们提出了一种用于线圈灵敏度估计的迭代算法，并证明了其在相控阵MR成像中进行最佳SNR重建和强度不均匀性校正的适用性。
