Cane beam volume CT image artifacts caused by defective cells in x-ray flat panel imagers and the artifact removal using a wavelet-analysis-based algorithm
Cane beam volume CT image artifacts caused by defective cells in x-ray flat panel imagers and the artifact removal using a wavelet-analysis-based algorithm
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DOI：
10.1118/1.1368878
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发表时间：
2001-05-01
期刊：
影响因子：
3.8
通讯作者：
Conover, D
中科院分区：
文献类型：
--
作者：
Tang, XY;Ning, R;Conover, D
X射线平板成像器（FPI）在锥形束容积CT（CBVCT）中的应用越来越受到关注。然而，由于有缺陷的半导体阵列制造工艺，缺陷单元必然存在于X射线FPI中。这些缺陷细胞导致投影图像中它们对应的图像像素在信号灰度级上表现异常，并且导致从投影图像重建的CBVCT图像中的严重条纹和环形伪影。由于CBVCT涉及三维（3-D）反投影，因此条纹和环形伪影的形成不同于二维（2-D）扇束CT。本文对三维反投影中的异常传播进行了几何分析，并通过计算机模拟和体模研究，研究了由异常传播引起的条纹和环形伪影的形态。为了校正这些伪影，提出了一种基于二维小波分析的统计方法来校正异常像素。该方法包括三个步骤：（1）对平场图像进行二维小波分析，识别出X射线FPI中位置不变的缺陷细胞，得到完整的缺陷细胞模板;（2）基于模板，- 对应于所述位置的投影图像像素的异常信号灰度级;不变的缺陷单元用它们的正常相邻像素的插值来替换;（3）使用窄窗中值滤波器来校正对应于孤立的位置变化缺陷单元的像素。一个CT低对比度体模的CBVCT图像被用来评估所提出的方法，表明条纹和环形伪影可以可靠地消除。该方法的新奇和优点是结合了小波分析，其内在的多分辨率分析和局部化能力使识别算法在变量下具有鲁棒性：X射线曝光水平在X射线FPI的动态范围的30%和70%之间。(C)2001年美国医学物理学家协会。
The application of x-ray flat panel imagers (FPIs) in cone beam volume CT (CBVCT) has attracted increasing attention. However, due to a deficient semiconductor array manufacturing process, defective cells unavoidably exist in x-ray FPIs. These defective cells cause their corresponding image pixels in a projection image to behave abnormally in signal gray level, and result in severe streak and ring artifacts in a CBVCT image reconstructed from the projection images. Since a three-dimensional (3-D) back-projection is involved in CBVCT, the formation of the streak and ring artifacts is different from that in the two-dimensional (2-D) fan beam CT. In this paper, a geometric analysis of the abnormality propagation in the 3D back-projection is presented, and the morphology of the streak and ring artifacts caused by the abnormality propagation is investigated through both computer simulation and phantom studies. In order to calibrate those artifacts, a 2D wavelet-analysis-based statistical approach to correct the abnormal pixels is proposed. The approach consists of three steps: (1) the location-invariant defective cells in an x-ray FPI are recognized by applying 2-D wavelet analysis on flat-field images, and a comprehensive defective cell template is acquired; (2) based upon the template, the abnormal signal gray level of the projection image pixels corresponding to the location-invariant defective cells is replaced with the interpolation of that of their normal neighbor pixels; (3) that corresponding to the isolated location-variant defective cells are corrected using a narrow-windowed median filter. The CBVCT images of a CT low-contrast phantom are employed to evaluate this proposed approach, showing that the streak and ring artifacts can be reliably eliminated. The novelty and merit of the approach are the incorporation of the wavelet analysis whose intrinsic multi-resolution analysis and localizability make the recognition algorithm robust under variable: x-ray exposure levels between 30% and 70% of the dynamic range of an x-ray FPI. (C) 2001 American Association of Physicists in Medicine.