@inproceedings{6d857807b81c4662b9b845885c746fc8,
title = "Synchronized Multi-Helical Computed Tomography",
abstract = "Limited by the field of view (FOV), most existed X-ray industrial computed tomography (ICT) techniques require multi scans for stitching projections when detecting long objects, which significantly increases the scanning time. In addition, these techniques usually adopt the one-by-one scanning mode that further reduces the scanning efficiency. Therefore, this paper proposes a synchronized multi-helical computed tomography. It allows multi objects to be helical scanned simultaneously without signal crosstalk, while it further improves the detecting efficiency. Besides, the reconstruction method suitable for the synchronized multi-helical CT is reported. This method utilizes projection segmentation and helical projection calibration to convert multi-object helical projections into single-object projections. The generated single-object projection can be then reconstructed by conventional algorithms, e.g. the filtered back projection (FBP). This work can improve the efficiency of CT scanning and will promote the applications of CT in large-scale long object detection.",
keywords = "calibration, efficiency, multi-helical CT, multi-object, segmentation, synchronized",
author = "Changsheng Zhang and Guogang Zhu and Jian Fu",
note = "Publisher Copyright: {\textcopyright} 2021 ACM.; 2nd International Conference on Control, Robotics and Intelligent System, CCRIS 2021 ; Conference date: 20-08-2021 Through 22-08-2021",
year = "2021",
month = aug,
day = "20",
doi = "10.1145/3483845.3483883",
language = "英语",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery ",
pages = "214--218",
booktitle = "CCRIS 2021 - Proceedings of 2021 2nd International Conference on Control, Robotics and Intelligent System",
address = "美国",
}