Parasoglou P, Malioutov D, Sederman A J, Rasburn J, Powell H, Gladden L F, Blake A, Johns M L
Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge CB2 3RA, UK.
J Magn Reson. 2009 Nov;201(1):72-80. doi: 10.1016/j.jmr.2009.08.003. Epub 2009 Aug 14.
A novel approach with respect to single point imaging (SPI), compressed sensing, is presented here that is shown to significantly reduce the loss of accuracy of reconstructed images from under-sampled acquisition data. SPI complements compressed sensing extremely well as it allows unconstrained selection of sampling trajectories. Dynamic processes featuring short T2* NMR signal can thus be more rapidly imaged, in our case the absorption of moisture by a cereal-based wafer material, with minimal loss of image quantification. The absolute moisture content distribution is recovered via a series of images acquired with variable phase encoding times allowing extrapolation to time zero for each image pixel and the effective removal of T2* contrast.
本文提出了一种关于单点成像（SPI）的新颖方法——压缩感知，该方法能显著减少从欠采样采集数据重建图像时的精度损失。SPI与压缩感知配合得非常好，因为它允许无约束地选择采样轨迹。具有短T2核磁共振信号的动态过程因此可以更快地成像，在我们的案例中是基于谷物的薄饼材料对水分的吸收，图像量化损失最小。通过一系列在可变相位编码时间下采集的图像恢复绝对水分含量分布，允许对每个图像像素外推到时间零，并有效去除T2对比度。
