Weierstrass Institute for Applied Analysis and Stochastics, Berlin, Germany.
Citigroup Biomedical Imaging Center, Weill Cornell Medical College, New York, USA.
Med Image Anal. 2015 Feb;20(1):76-86. doi: 10.1016/j.media.2014.10.008. Epub 2014 Nov 4.
We present a method for local estimation of the signal-dependent noise level in magnetic resonance images. The procedure uses a multi-scale approach to adaptively infer on local neighborhoods with similar data distribution. It exploits a maximum-likelihood estimator for the local noise level. The validity of the method was evaluated on repeated diffusion data of a phantom and simulated data using T1-data corrupted with artificial noise. Simulation results were compared with a recently proposed estimate. The method was also applied to a high-resolution diffusion dataset to obtain improved diffusion model estimation results and to demonstrate its usefulness in methods for enhancing diffusion data.
我们提出了一种用于磁共振图像中信号相关噪声水平的局部估计方法。该方法使用多尺度方法自适应地推断具有相似数据分布的局部邻域。它利用最大似然估计器来估计局部噪声水平。该方法的有效性通过对重复的幻影扩散数据和使用 T1 数据污染的人工噪声模拟数据进行了评估。模拟结果与最近提出的一种估计方法进行了比较。该方法还应用于高分辨率扩散数据集，以获得改进的扩散模型估计结果，并证明其在增强扩散数据的方法中的有用性。
