最大熵磁共振成象理论

Maximum Entropy Magnetic Resonance Imaging Theory

由于在实际磁共振成象系统中 ,只能得到有限的频谱数据 ,利用传统的FFT方法重建磁共振图象 ,将导致截断伪影和低的分辨率。本文提出了一种基于AR模型的最大熵磁共振成象算法 ,利用AR模型外推未知频谱数据 ,替代了FFT方法的填零法重建 ,并利用了BURG算法中的AR模型参数计算的有效性 ,不仅消除了截断伪影、抑制噪声、提高了分辨率 ,而且使重建时间与FFT方法相当 。

This paper presents an AR model based maximum entropy method for magnetic resonance imaging.Since it has computedly effecient and better quality of reconstructed image,it will be an alternative method to conventional use of the fast Fourier Transform algorithm in the reconstruction of magnetic resonance images.It is acquired by computing the respective AR coefficients and linerar prediction error sequence.In practical uses,the application FFT leads to artifacts and lower resolution in the image due to the truncated spectral data sets,but our reconstruction algorithm is superior both in enhancing resolution and in removing truncation artifacts.