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CT image restoration method via total variation and L 0 smoothing filter

  • Hai Yin , Xianyun Li , Zhi Liu , Wei Peng , Chengxiang Wang EMAIL logo and Wei Yu EMAIL logo
Published/Copyright: January 30, 2024

Abstract

In X-ray CT imaging, there are some cases where the obtained CT images have serious ring artifacts and noise, and these degraded CT images seriously affect the quality of clinical diagnosis. Thus, developing an effective method that can simultaneously suppress ring artifacts and noise is of great importance. Total variation (TV) is a famous prior regularization for image denoising in the image processing field, however, for degraded CT images, it can suppress the noise but fail to reduce the ring artifacts. To address this issue, the L 0 smoothing filter is incorporated with TV prior for CT ring artifacts and noise removal problem where the problem is transformed into several optimization sub-problems which are iteratively solved. The experiments demonstrate that the ring artifacts and noise presented in the CT image can be effectively suppressed by the proposed method and meanwhile the detailed features such as edge structure can be well preserved. As the superiority of TV and L 0 smoothing filters are fully utilized, the performance of the proposed method is better than the existing methods such as the TV-based method and L 0 -based method.

MSC 2020: 94A08; 90C90

Award Identifier / Grant number: 62371184

Award Identifier / Grant number: 61801086

Funding statement: This work was partially funded by the National Natural Science Foundation of China (No. 62371184 and No. 61801086), the Natural Science Foundation of Chongqing (No. cstc2019jcyj-msxmX0345), the Science and Technology Research Program of Chongqing Municipal Education Commission (No. KJQN202000534), and the National College Students Innovation and Entrepreneurship Training Program (No. 202110927008). The authors also thank Guangzhou Huaduan Technology co., LTD for providing real data for CT reconstruction.

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Received: 2023-07-02
Revised: 2023-11-05
Accepted: 2023-12-30
Published Online: 2024-01-30
Published in Print: 2024-10-01

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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