Wen Yan, Zhou Dong, Liu Tian, Spincemaille Pascal, Wang Yi
Radiology, Weill Medical College of Cornell University, New York, NY, USA; State University of New York at Stony Brook, Stony Brook, New York, USA.
Magn Reson Med. 2014 Oct;72(4):1065-71. doi: 10.1002/mrm.24998. Epub 2013 Nov 19.
The sophisticated harmonic artifact reduction for phase data (SHARP) method has been proposed for the removal of background field in MRI phase data. It relies on the spherical mean value (SMV) property of harmonic functions, and its accuracy depends on the radius of the sphere used for computing the SMV and truncation threshold needed for deconvolution. The goal of this study was to develop an alternative SMV-based background field removal method with reduced dependences on these parameters.
The proposed background field removal method, termed iterative SMV (iSMV), consists of applying the SMV operation repeatedly on the field map. It was validated in a phantom and in vivo brain data of five healthy volunteers.
The iSMV method demonstrates accurate background field removal in the phantom. Compared with SHARP, the iSMV method shows a significantly reduced dependence on the SMV radius both in phantom and in human data. Because a smaller radius can be chosen, the iSMV method allows retaining a larger part of the region of interest compared with SHARP.
The iSMV method is an effective background field removal method with a reduced dependence on method parameters. Magn Reson Med 72:1065-1071, 2014. © 2013 Wiley Periodicals, Inc.
已提出用于去除MRI相位数据中背景场的复杂谐波伪影减少相位数据(SHARP)方法。它依赖于谐波函数的球均值(SMV)特性,其准确性取决于用于计算SMV的球体半径和解卷积所需的截断阈值。本研究的目的是开发一种基于SMV的背景场去除方法,减少对这些参数的依赖。
所提出的背景场去除方法,称为迭代SMV(iSMV),包括在磁场图上反复应用SMV操作。它在一个模型以及五名健康志愿者的体内脑数据中得到了验证。
iSMV方法在模型中显示出准确的背景场去除效果。与SHARP相比,iSMV方法在模型和人体数据中对SMV半径的依赖性都显著降低。由于可以选择较小的半径,与SHARP相比,iSMV方法允许保留更大的感兴趣区域。
iSMV方法是一种有效的背景场去除方法,对方法参数的依赖性降低。《磁共振医学》72:1065 - 1071,2014年。©2013威利期刊公司。