Noise Suppression for Dual-Energy CT Through Entropy Minimization.
Noise Suppression for Dual-Energy CT Through Entropy Minimization.
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DOI：
10.1109/tmi.2015.2429000
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发表时间：
2015-11
影响因子：
10.6
通讯作者：
Zhu L
中科院分区：
文献类型：
--
作者：
Petrongolo M;Zhu L
在双能量CT（DECT）中，信号分解过程中的噪声放大严重限制了基底材料图像的实用性。由于临床相关的对象通常包含有限数量的不同材料，我们提出了一种图像域分解方法，通过熵最小化（IDEM）的噪声抑制DECT。分解图像的像素首先被线性变换成数据点的2D簇，由于强信号相关性，这些数据点是高度不对称的。通过数值搜索在2D空间中识别最佳轴，使得数据聚类到轴上的投影具有最小熵。通过沿着垂直于投影轴的方向估计每个数据簇的质心值，对每个图像像素执行噪声抑制。IDEM方法与其他噪声抑制技术的不同之处在于，它不通过减少相邻像素之间的空间变化来抑制像素噪声。通过对Catphan©600和拟人头部模型的研究，该特征赋予我们的算法以独特的能力，将DECT分解图像上的噪声标准差降低约一个数量级，同时保持空间分辨率和图像噪声功率谱（SNR）。与滤波方法和最近发展的迭代方法相比，在相同的噪声抑制水平下，IDEM算法获得了高分辨率图像，具有较少的伪影。它还保持电子密度测量的精度，偏差误差小于2%。IDEM方法有效地抑制了定量使用的DECT的噪声，具有吸引人的功能，保持图像的空间分辨率和分辨率。
In dual energy CT (DECT), noise amplification during signal decomposition significantly limits the utility of basis material images. Since clinically relevant objects typically contain a limited number of different materials, we propose an Image-domain Decomposition method through Entropy Minimization (IDEM) for noise suppression in DECT. Pixels of decomposed images are first linearly transformed into 2D clusters of data points, which are highly asymmetric due to strong signal correlation. An optimal axis is identified in the 2D space via numerical search such that the projection of data clusters onto the axis has minimum entropy. Noise suppression is performed on each image pixel by estimating the center-of-mass value of each data cluster along the direction perpendicular to the projection axis. The IDEM method is distinct from other noise suppression techniques in that it does not suppress pixel noise by reducing spatial variation between neighboring pixels. As supported by studies on Catphan©600 and anthropomorphic head phantoms, this feature endows our algorithm with a unique capability of reducing noise standard deviation on DECT decomposed images by approximately one order of magnitude while preserving spatial resolution and image noise power spectra (NPS). Compared with a filtering method and recently developed iterative method at the same level of noise suppression, the IDEM algorithm obtains high-resolution images with less artifacts. It also maintains accuracy of electron density measurements with less than 2% bias error. The IDEM method effectively suppresses noise of DECT for quantitative use, with appealing features on preservation of image spatial resolution and NPS.