Quantitative evaluation of noise reduction strategies in dual-energy imaging
Quantitative evaluation of noise reduction strategies in dual-energy imaging
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DOI：
10.1118/1.1538232
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发表时间：
2003-02-01
期刊：
影响因子：
3.8
通讯作者：
Dobbins, JT
中科院分区：
文献类型：
--
作者：
Warp, RJ;Dobbins, JT
在本文中，我们描述了对三种双能降噪算法性能的定量评估：Kalender 相关降噪（KCNR）、噪声剪切（NOC）和边缘预测自适应平滑（EPAS）。使用 a-Si TFT 平板 X 射线探测器采集的双能图像中残余噪声的方差和噪声功率谱测量，将这些算法与简单的平滑滤波器方法进行比较。通过从整体平均图像中减去单个图像，通过具有亚像素精度的新方法来估计真实噪声。结果表明，在组织图像的肺部区域，所有三种算法在高空间频率（KCNR = 88％，NOC = 88％，EPAS = 84％，NOC / KCNR = 88％）下以相似的百分比减少噪声，而在低空间频率（KCNR = 45％，NOC = 54％，EPAS = 52％，NOC / KCNR = 55％）下稍微减少噪声。在低频下，KCNR 边缘伪影的存在使性能变差，因此 NOC 或 NOC 与 KCNR 组合的性能最佳。在高频下，KCNR 在骨骼图像中表现最佳，而 NOC 在组织图像中表现最佳。双能成像中的降噪策略可能是有效的，并且应侧重于根据解剖位置混合各种算法。 (C) 2003 年美国医学物理学家协会。
In this paper we describe a quantitative evaluation of the performance of three dual-energy noise reduction algorithms: Kalender's correlated noise reduction (KCNR), noise clipping (NOC), and edge-predictive adaptive smoothing (EPAS). These algorithms were compared to a simple smoothing filter approach, using the variance and noise power spectrum measurements of the residual noise in dual-energy images acquired with an a-Si TFT flat-panel x-ray detector. An estimate of the true noise was made through a new method with subpixel accuracy by subtracting an individual image from an ensemble average image. The results indicate that in the lung regions of the tissue image, all three algorithms reduced the noise by similar percentages at high spatial frequencies (KCNR=88%,NOC=88%,EPAS=84%,NOC/KCNR=88%) and somewhat less at low spatial frequencies (KCNR=45%,NOC=54%,EPAS=52%,NOC/KCNR=55%). At low frequencies, the presence of edge artifacts from KCNR made the performance worse, thus NOC or NOC combined with KCNR performed best. At high frequencies, KCNR performed best in the bone image, yet NOC performed best in the tissue image. Noise reduction strategies in dual-energy imaging can be effective and should focus on blending various algorithms depending on anatomical locations. (C) 2003 American Association of Physicists in Medicine.