CAJ | 학술논문

磁共振图像K空间中的尖峰噪声会严重影响图像质量。该文在磁共振图像压缩感知的共轭梯度重建法的基础上，提出一种新的利用磁共振图像稀疏性进行尖峰噪声修复的方法。传统的共轭梯度重建是通过小波域迭代进行的，对于K空间的尖峰噪声的消除不是最适合。首先提出压缩感知的K空间重建算法，该算法与小波域重建等效。在此基础上，提出可以较好地修复尖峰噪声的K空间部分重建算法。即在迭代过程中，以图像的稀疏性作为约束条件，仅修改尖峰噪声所遮盖区域的数据，其他位置的数据保持不变。该算法与传统的插值算法及共轭梯度算法相比，能够更好地修复K空间尖峰噪声点，减少图像伪影，同时降低了对尖峰噪声定位准确性的要求。
자공진도상K공간중적첨봉조성회엄중영향도상질량。해문재자공진도상압축감지적공액제도중건법적기출상，제출일충신적이용자공진도상희소성진행첨봉조성수복적방법。전통적공액제도중건시통과소파역질대진행적，대우K공간적첨봉조성적소제불시최괄합。수선제출압축감지적K공간중건산법，해산법여소파역중건등효。재차기출상，제출가이교호지수복첨봉조성적K공간부분중건산법。즉재질대과정중，이도상적희소성작위약속조건，부수개첨봉조성소차개구역적수거，기타위치적수거보지불변。해산법여전통적삽치산법급공액제도산법상비，능구경호지수복K공간첨봉조성점，감소도상위영，동시강저료대첨봉조성정위준학성적요구。
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.