Feng Yanqiu, He Taigang, Feng Meiyan, Carpenter John-Paul, Greiser Andreas, Xin Xuegang, Chen Wufan, Pennell Dudley J, Yang Guang-Zhong, Firmin David N
School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
Magn Reson Med. 2014 Jul;72(1):260-8. doi: 10.1002/mrm.24914. Epub 2013 Aug 20.
To investigate the feasibility of improving MRI R2* mapping by filtering the images before curve-fitting.
Pixel-by-pixel curve-fitting for the quantification of MRI relaxometry remains a challenge for low signal-to-noise ratio images. By computing the weighted mean of spatially adjacent pixels, the low-pass Gaussian (LPG) filter can suppress the noise but at the expense of blurring. By assigning high weights to pixels with similar neighborhood patches, the nonlocal means (NLM) algorithm can reduce noise while retaining intrinsic signals, however, its potential has not been explored in pixel-by-pixel MRI relaxometry, and in this study, we aimed to investigate the impact of the LPG and the NLM filtering on decay signals and MRI R2* mapping. These two filtering methods were compared on both simulated and in vivo data.
Both LPG and NLM algorithms produces R2* maps with decreased root-mean-square-errors. The LPG filter blurs edges of R2* maps while the NLM algorithm preserves details well. The NLM consistently yields R2* mapping with smaller errors than the LPG filtering in all cases.
Pixel-by-pixel fitting can skew MRI relaxometry. The NLM outperforms the conventional LPG filter and has the potential to provide more accurate pixel-by-pixel MRI relaxometry for improved tissue characterization.
通过在曲线拟合前对图像进行滤波来研究改善MRI R2* 映射的可行性。
对MRI弛豫测量进行逐像素曲线拟合以实现定量分析，对于低信噪比图像而言仍是一项挑战。通过计算空间相邻像素的加权平均值，低通高斯（LPG）滤波器可以抑制噪声，但代价是图像模糊。通过为具有相似邻域块的像素赋予高权重，非局部均值（NLM）算法可以在保留固有信号的同时降低噪声，然而，其在逐像素MRI弛豫测量中的潜力尚未得到探索。在本研究中，我们旨在研究LPG和NLM滤波对衰减信号和MRI R2* 映射的影响。在模拟数据和体内数据上对这两种滤波方法进行了比较。
LPG和NLM算法均生成了均方根误差降低的R2* 图。LPG滤波器会模糊R2* 图的边缘，而NLM算法能很好地保留细节。在所有情况下，NLM始终能产生比LPG滤波误差更小的R2* 映射。
逐像素拟合会使MRI弛豫测量产生偏差。NLM优于传统的LPG滤波器，有潜力为改善组织特征提供更准确的逐像素MRI弛豫测量。
