混叠
迭代重建
投影(关系代数)
采样(信号处理)
算法
基础(线性代数)
迭代法
梁(结构)
重建算法
图像分辨率
图像质量
数学
计算机科学
光学
计算机视觉
几何学
物理
滤波器(信号处理)
图像(数学)
作者
Andy Ziegler,Thomas Köhler,Tim Tolker‐Nielsen,Roland Proksa
摘要
In cone‐beam transmission tomography the measurements are performed with a divergent beam of x‐rays. The reconstruction with iterative methods is an approach that offers the possibility to reconstruct the corresponding images directly from these measurements. Another approach based on spherically symmetric basis functions (blobs) has been reported with results demonstrating a better image quality for iterative reconstruction algorithms. When combining the two approaches (i.e., using blobs in iterative cone‐beam reconstruction of divergent rays) the problem of blob sampling without introducing aliasing must be addressed. One solution to this problem is to select a blob size large enough to ensure a sufficient sampling, but this prevents a high resolution reconstruction, which is not desired. Another solution is a heuristic low‐pass filtering, which removes this aliasing, but neglects the different contributions of blobs to the absorption depending on the spatial position in the volume and, therefore, cannot achieve the best image quality. This article presents a model of sampling the blobs which is motivated by the beam geometry. It can be used for high resolution reconstruction and can be implemented efficiently.
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