基于奇异谱分析的校正磁共振图像非均匀场的新方法

提出一种基于奇异函数分析数学模型的校正磁共振图像非均匀场的新方法.首先将受非均匀场污染的图像低频分量移去,然后由较高频率的不受非均匀场污染的频率分量重构被移去的低频分量,进而重构无非均匀场的磁共振图像,最后估计非均匀场.该方法不需要组织密度参数模型,不用事先对图像进行预处理,完全不需要用户的参与.

A New Approach for Correcting Bias Field in MR Images Using Singularity Spectrum Analysis

Bias field correction may benefit many quantitative analysis applications of MR image.This paper proposed a fundamentally different approach for correcting bias field in MR images.The method is based on the use of the mathematical model of singularity function analysis,which represents a discrete signal or its spectrum as a weighted sum of singularity functions.Through this model,an MR image's low spatial frequency components corrupted by a smoothly varying bias field are first removed,and then reconstructed from its higher spatial frequency components not polluted by bias field.The thus reconstructed image is then used to estimate bias field for final image correction.This correction method does not need any initialization or a prior models,nor image preprocessing such as brain masking or presegmentation.It is fully automatic without any user interaction.