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基于球面轨迹的CT扫描成像方法

CT Scanning Imaging Method Based on a Spherical Trajectory.

作者信息

Chen Ping, Han Yan, Gui Zhiguo

机构信息

National Key Laboratory for Electronic Measurement Technology, North University of China, Taiyuan 030051, China.

Key Laboratory of Instrumentation Science & Dynamic Measurement, North University of China, Taiyuan 030051, China.

出版信息

PLoS One. 2016 Mar 2;11(3):e0149779. doi: 10.1371/journal.pone.0149779. eCollection 2016.

DOI:10.1371/journal.pone.0149779
PMID:26934744
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4775072/
Abstract

In industrial computed tomography (CT), the mismatch between the X-ray energy and the effective thickness makes it difficult to ensure the integrity of projection data using the traditional scanning model, because of the limitations of the object's complex structure. So, we have developed a CT imaging method that is based on a spherical trajectory. Considering an unrestrained trajectory for iterative reconstruction, an iterative algorithm can be used to realise the CT reconstruction of a spherical trajectory for complete projection data only. Also, an inclined circle trajectory is used as an example of a spherical trajectory to illustrate the accuracy and feasibility of this new scanning method. The simulation results indicate that the new method produces superior results for a larger cone-beam angle, a limited angle and tabular objects compared with traditional circle trajectory scanning.

摘要

在工业计算机断层扫描(CT)中,由于物体复杂结构的限制,X射线能量与有效厚度之间的不匹配使得使用传统扫描模型难以确保投影数据的完整性。因此,我们开发了一种基于球形轨迹的CT成像方法。考虑到用于迭代重建的无约束轨迹,迭代算法可用于仅对完整投影数据实现球形轨迹的CT重建。此外,以倾斜圆轨迹作为球形轨迹的示例来说明这种新扫描方法的准确性和可行性。模拟结果表明,与传统圆轨迹扫描相比,新方法在更大的锥束角、有限角度和板状物体的情况下产生了更好的结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b58/4775072/7b6527189350/pone.0149779.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b58/4775072/acda14e0a422/pone.0149779.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b58/4775072/8a6c610ba221/pone.0149779.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b58/4775072/4b3deb9cdb5f/pone.0149779.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b58/4775072/c37f9c9fc847/pone.0149779.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b58/4775072/7eae41ea7b9d/pone.0149779.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b58/4775072/7c2d76022416/pone.0149779.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b58/4775072/c974c56d65af/pone.0149779.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b58/4775072/7b6527189350/pone.0149779.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b58/4775072/acda14e0a422/pone.0149779.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b58/4775072/8a6c610ba221/pone.0149779.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b58/4775072/4b3deb9cdb5f/pone.0149779.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b58/4775072/c37f9c9fc847/pone.0149779.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b58/4775072/7eae41ea7b9d/pone.0149779.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b58/4775072/7c2d76022416/pone.0149779.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b58/4775072/c974c56d65af/pone.0149779.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b58/4775072/7b6527189350/pone.0149779.g008.jpg

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