Affine adaptive filtering of CT data
Affine adaptive filtering of CT data
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DOI：
10.1016/s1361-8415(00)00011-6
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发表时间：
2000-06
影响因子：
10.9
通讯作者：
C. Westin;J. Richolt;V. Moharir;R. Kikinis
中科院分区：
文献类型：
--
作者：
C. Westin;J. Richolt;V. Moharir;R. Kikinis
提出了一种使用多维自适应滤波器重新采样和增强图像数据的新方法。本文解决的根本问题是尺寸接近体素几何形状的图像结构的分割。自适应滤波用于通过将数据重新采样到具有更高样本密度的点阵来减少部分体积平均的影响，并降低图像噪声水平。重采样是通过构建相对于原始采样点阵具有子像素偏移的滤波器组来实现的。滤波器还针对各向异性体素尺寸进行频率校正。位移和体素维度通过仿射变换来描述，并提供用于调整滤波器频率函数的模型。该方法已在 CT 数据上进行了评估，其中体素通常是非立方体。 CT 图像体积中的面内分辨率通常比平面分辨率高 3-10 倍。该方法清楚地表明了对三次样条插值和正弦插值等传统重采样技术的改进。
A novel method for resampling and enhancing image data using multidimensional adaptive filters is presented. The underlying issue that this paper addresses is segmentation of image structures that are close in size to the voxel geometry. Adaptive filtering is used to reduce both the effects of partial volume averaging by resampling the data to a lattice with higher sample density and to reduce the image noise level. Resampling is achieved by constructing filter sets that have subpixel offsets relative to the original sampling lattice. The filters are also frequency corrected for ansisotropic voxel dimensions. The shift and the voxel dimensions are described by an affine transform and provides a model for tuning the filter frequency functions. The method has been evaluated on CT data where the voxels are in general non cubic. The in-plane resolution in CT image volumes is often higher by a factor of 3–10 than the through-plane resolution. The method clearly shows an improvement over conventional resampling techniques such as cubic spline interpolation and sinc interpolation.