[口头报告]A preliminary study on multi-energy CT reconstruction via weighted tensor nuclear norm combining image sparsity - 报告详情

A preliminary study on multi-energy CT reconstruction via weighted tensor nuclear norm combining image sparsity
编号:70 稿件编号:42 访问权限:仅限参会人 更新:2021-11-05 17:30:05 浏览:578次 口头报告

报告开始:2021年11月14日 14:15 (Asia/Shanghai)

报告时间:15min

所在会议:[PS1] Plenary Session 1 [CT1] Workshop on CT

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摘要
Multi-energy computed tomography has attracted much attention in recent years. One of the key tasks focuses on developing efficient and accurate reconstruction algorithm of multi-channel image, especially for low-dose and incomplete dataset. This work proposed a tensor low rank and image sparsity based reconstruction method. The regularization functional is formed by introducing the weighted tensor nuclear norm and L0-norm on image gradient of each channel. The alternating direction method of multipliers is applied to develop the corresponding algorithm. Preliminary experiments on simulated dataset are performed, and both visual inspection and numerical criteria indicate the advantages of the proposed new method.
关键字
multi-channel reconstruction,tensor low rank,weighted tensor nuclear norm,image gradient sparsity,alternating direction method of multipliers
报告人
Ailong Cai
Associate Professor Information Engineering University

Dr. Ailong Cai is an associate professor of Information Engineering University at Zhengzhou City, Henan Province, P.R. China. His research interests foucs on theory and algorithms of imaging problems.

稿件作者
Ailong Cai Information Engineering University
Xinyi Zhong Information Engineering University
Xiaohuan Yu Information Engineering University
Yizhong Wang Information Engineering University
Lei Li Information Engineering University
Bin Yan Information Engineering University
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重要日期

摘要提交日期:

2021/08/31

2021/10/25

全文投稿日期:  

2021/09/15

2021/10/25

录取通知日期: 

2021/09/30

2021/11/01

会议日期:   2021-11-12-2021-11-14

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