锥形光束VOI重建的高效二维滤波

Yan Xia, A. Maier, F. Dennerlein, H. Hofmann, J. Hornegger
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引用次数: 12

摘要

在一些临床应用中,例如,在介入期间检查部署的支架或线圈,只有一小部分患者可能具有诊断价值。为了减少对患者的剂量,在感兴趣体积(VOl)外部署准直器来阻挡辐射剂量是可行的。然而,由此产生的截断,特别是在横向上,对传统的重建方法提出了挑战。计算机断层扫描的近似截断鲁棒算法(attrt)能够在不使用任何显式外推方案的情况下重建图像,即使对于高度截断的数据也是如此。它基于将标准斜坡滤波器分解为局部和非局部滤波步骤,其中局部步骤与二维(2D)拉普拉斯算子重合,非局部步骤是二维基于氡的滤波。在实际实现中,基于氡的滤波计算效率不高。在本文中,我们提出了对原始的吸引算法的改进。原始算法中基于二维氡的滤波步骤被解析二维卷积所取代,在保留VOl算法图像质量优势的同时,显著提高了计算性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient 2D filtering for cone-beam VOI reconstruction
In some clinical applications, e.g., examination of deployed stents or coils during the intervention, only a small portion of the patient may be of diagnostic interest. For the sake of dose reduction to the patient, it is practicable to deploy a collimator to block radiation dose outside volume of interest (VOl). The resulting truncation, however, particularly in lateral direction, poses a challenge to the conventional reconstruction methods. The Approximated Truncation Robust Algorithm for Computed Tomography (ATRACT) is able to reconstruct images without the use of any explicit extrapolation schemes, even for highly truncated data. It is based on a decomposition of the standard ramp-filter into a local and a non-local filtering step, where the local step coincides with the two-dimensional (2D) Laplace operator and the non-local step is a 2D Radon-based filtering. In a practical implementation, the Radon-based filtering is not computationally efficient. In this paper, we present an improvement of the original ATRACT algorithm. The 2D Radon-based filtering step in the original algorithm is replaced by an analytical 2D convolution, resulting in a significant improvement in computational performance while retaining the image quality benefits of the VOl algorithm.
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