Dietrich O, Heiland S, Sartor K
Department of Neuroradiology, University of Heidelberg Medical School, Heidelberg, Germany.
Magn Reson Med. 2001 Mar;45(3):448-53. doi: 10.1002/1522-2594(200103)45:3<448::aid-mrm1059>3.0.co;2-w.
Noise in MR image data increases the mean signal intensity of image regions due to the usually performed magnitude reconstruction. Diffusion-weighted imaging (DWI) is especially affected by high noise levels for several reasons, and a decreasing SNR at increasing diffusion weighting causes systematic errors when calculating apparent diffusion coefficients (ADCs). Two different methods are presented to correct biased signal intensities due to the presence of complex noise: 1) with Gaussian intensity distribution, and 2) with arbitrary intensity distribution. The performance of the correction schemes is demonstrated by numerical simulations and DWI measurements on two different MR systems with different noise characteristics. These experiments show that noise significantly influences the determination of ADCs. Applying the proposed correction schemes reduced the bias of the determined ADC to less than 10% of the bias without correction. Magn Reson Med 45:448-453, 2001.
由于通常进行的幅度重建,磁共振(MR)图像数据中的噪声会增加图像区域的平均信号强度。扩散加权成像(DWI)由于多种原因特别容易受到高噪声水平的影响,并且在扩散加权增加时信噪比(SNR)降低会在计算表观扩散系数(ADC)时导致系统误差。本文提出了两种不同的方法来校正由于存在复杂噪声而产生的信号强度偏差:1)具有高斯强度分布,以及2)具有任意强度分布。通过在具有不同噪声特性的两种不同MR系统上进行数值模拟和DWI测量,证明了校正方案的性能。这些实验表明,噪声会显著影响ADC的测定。应用所提出的校正方案可将测定的ADC偏差降低至未校正时偏差的10%以下。《磁共振医学》45:448 - 453,2001年。