潘晓川教授的反投影滤波(BPF)新型重建算法介绍

Xiaochuan Pan's New BPF-type Algorithms for Computed Tomography Image Reconstruction

计算机断面成像(CT)的精确重建方法一直是现代CT成像领域中一个活跃的研究方向。近几年,关于平行束、扇束、锥束CT精确重建的研究取得了一系列重要的突破和创新成果。本文主要介绍了美国芝加哥大学潘晓川教授为首的课题组提出的一类基于反投影卷积(BackprojectionFiltration:BPF)的CT精确重建算法。BPF算法最重要的贡献在于它成功地解决了从沿探测器方向截断的投影数据进行CT精确重建的问题;因此,通过BPF算法能够设计出针对目标的感兴趣区域成像策略,减少成像扫描、重建时间,辐照剂量和散射光子。

The development of image reconstruction in computed tomography （CT） remains one of the most active areas in modem imaging sciences. In the last few years, there have been significant breakthroughs in the development of mathematically exact and innovative methods for image reconstruction from parallel-beam, fan-beam and cone-heam projection data. This paper introduces a type of BPF-based algorithms proposed by the laboratory led by Dr. Xiaochuan Pan at The University of Chicago. One of important properties of the BPF-based algorithms lies in that it can provide exact image reconstruction within a region of interest （ROI） from projection data containing longitudinal and transverse truncations. Such a unique property of the BPF-based algorithm offer the opportunity to design targeted ROI-imaging strategy, thus reducing scanning effort, computation time, radiation dose, and imaging artifacts such as scatter.