Helical cone beam reconstruction using rotated 1D ramp filtering

迭代重建 重建算法 算法 截断(统计) 计算机视觉 投影(关系代数) 探测器 冗余(工程) 弹道 人工智能 噪音(视频) 数学 计算机科学 物理 图像(数学) 电信 统计 操作系统 天文
作者
Xiangyang Tang
出处
期刊:Proceedings of SPIE 卷期号:5370: 701-701 被引量:1
标识
DOI:10.1117/12.534613
摘要

With the evolution from multi-detector-row CT to cone beam volumetric CT, to maintain reconstruction accuracy becomes more challenging. To combat the severe artifacts caused by a large cone angle, three-dimensional reconstruction algorithms have to be used in CB volumetric CT. In practice, the filtered backprojection (FBP) reconstruction algorithm is the most desirable due to its pipe-line computational structure and image generation efficiency. The first CB-FBP reconstruction algorithm is the well-known FDK algorithm that was originally derived for a circular x-ray source trajectory by heuristically extending its two-dimensional counterpart. Later on, a general CB-FBP reconstruction algorithm was derived for non-circular, such as helical, source trajectories. It has been recognized that, a filtering operation in the projection data along the tangential direction of a helical x-ray source trajectory can significantly improve the reconstruction accuracy of helical CB volumetric CT. However, the tangential filtering encounters latitudinal data truncation, resulting in degraded noise characteristics or data manipulation inefficiency. A CB-FBP reconstruction algorithm using one-dimensional rotational filtering across detector rows (namely CB-RFBP) is proposed in this manuscript. In principal, the proposed CB-RFBP reconstruction algorithm is approximate, but approaches the reconstruction accuracy that can be achieved by exact helical CB-FBP reconstruction algorithms because of the rotational filtering. Unlike exact CB-FBP reconstruction algorithms in which all redundant data are usually discarded to maintain data redundancy, the proposed CB-RFBP reconstruction algorithm makes use of all available projection data, resulting in significantly improved noise characteristics and dose efficiency. Moreover, the rotational filtering across detector rows not only survives the so-called long object problem, but also avoids latitudinal data truncation existing in other helical CB-FBP reconstruction algorithm in which a tangential filtering is carried out, providing improved noise characteristics, dose efficiency or data manipulation efficiency.
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