Non-Linear 3d Reconstruction for Compressive X-Ray Tomosynthesis

Qile Zhao, Xu Ma*, Angela Cuadros, Gonzalo R. Arce, Rui Chen

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

Compressive X-ray tomosynthesis is an emerging technology that can be used for medical diagnosis, safety inspection and industrial non-destructive testing. Traditional compressive X-ray tomosynthesis uses sequential illumination to interrogate the object of interest, which generates non-overlapping projection measurements. However, when multiple X-ray sources emit simultaneously, the projections corresponding to different sources overlap creating multiplexed measurements. Such measurement strategy leads to a non-linear reconstruction problem. The reconstruction of the three-dimensional (3D) object from multiplexed projections is an important problem. This paper proposes a non-linear 3D reconstruction approach for compressive X-ray tomosynthesis, where a set of coding masks are used to generate structured illumination and reduce radiation dose. The effectiveness of the method is verified by simulation experiments. It is shown that the proposed approach can reconstruct high-quality images with just a few snapshots.

源语言英语
主期刊名2020 IEEE International Conference on Image Processing, ICIP 2020 - Proceedings
出版商IEEE Computer Society
3149-3153
页数5
ISBN(电子版)9781728163956
DOI
出版状态已出版 - 10月 2020
活动2020 IEEE International Conference on Image Processing, ICIP 2020 - Virtual, Abu Dhabi, 阿拉伯联合酋长国
期限: 25 9月 202028 9月 2020

出版系列

姓名Proceedings - International Conference on Image Processing, ICIP
2020-October
ISSN(印刷版)1522-4880

会议

会议2020 IEEE International Conference on Image Processing, ICIP 2020
国家/地区阿拉伯联合酋长国
Virtual, Abu Dhabi
时期25/09/2028/09/20

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