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基于超拉普拉斯分布的磁化率重建算法
Magnetic Susceptibility Reconstruction Algorithm Using Hyper-Laplacian Priors
【摘要】 定量磁化率成像由于能够定量分析组织内部的顺磁性物质而受到越来越多的关注。然而由局部场反演出磁化率分布的过程是一个病态反问题,在反演过程中,引入合理的先验信息可以提高结果的准确性。为此,提出基于超拉普拉斯分布的磁化率重建算法,实际人脑实验验证该方法在提高结果准确性方面的优越性。
【Abstract】 There is a growing interest in quantitative susceptibility mapping because it is being used for quantifying tissue susceptibility in magnetic resonance imaging. However, the estimation of magnetic susceptibility from phase is an ill-posed problem. Introduce a more accurate prior information in order to improve the accuracy of experimental results. Proposes a magnetic susceptibility reconstruction algorithm based on Hyper-Laplacian priors. The numerical phantom experiment and vivo experiment both confirm that the proposed method can accurately measure susceptibility.
【关键词】 定量磁化率成像;
病态反问题;
超拉普拉斯分布;
【Key words】 Quantitative Susceptibility Mapping; Ill-posed Problem; Hyper-Laplacian Priors;
【Key words】 Quantitative Susceptibility Mapping; Ill-posed Problem; Hyper-Laplacian Priors;
- 【文献出处】 现代计算机(专业版) ,Modern Computer , 编辑部邮箱 ,2016年11期
- 【分类号】TP391.41
- 【下载频次】46