波谱学杂志Issue(1)：41-50,10.DOI:10.11938/cjmr20150105
基于稀疏重建的磁共振图像尖峰噪声消除方法
Spike Noise Removal for Magnetic Resonance Imaging Based on Sparse Reconstruction
摘要
Abstract
It is well-known that, in magnetic resonance imaging (MRI), the presence of spike noise in the K-space will degrade the quality of reconstructed images. In this work, we proposed a method to remove spike noises based on the non-linear conjugate gradient (NLCG) reconstruction algorithm of compressed sensing (CS). The traditional CG algorithm reconstructs images in the wave-domain, making it difficult to remove spike noises. The proposed algorithm is a partial K-space reconstruction algorithm. Using image sparsity as a restrain, the algorithm reconstructs only the data which is covered by spike noises. Compared with the interpolation and NLCG algorithm, the proposed algorithm was shown to yield better images with less artifacts without the need to know the accurate localization of the spike noises.关键词
磁共振成像(MRI)/压缩感知/非线性共轭梯度法/K空间重建/尖峰噪声Key words
MRI/compressed sensing/non-linear conjugate gradient/K-space reconstruction/spike noise分类
数理科学引用本文复制引用
李智敏,谢海滨,周敏雄,张成秀,奚伟,姜小平,杨光..基于稀疏重建的磁共振图像尖峰噪声消除方法[J].波谱学杂志,2015,(1):41-50,10.基金项目
上海市科委资助项目(08DZ1900700) （08DZ1900700）
