Lung CT Image Enhancement Based on Image Segmentation and Total Variational

Hongfei Wang; ShiQing Ma; Lei Min; Shuai Wang; Wei Yang; Chuan Xu; Ping Yang

doi:10.3788/CJL202249.2007210

Journals >Chinese Journal of Lasers >Volume 49 >Issue 20 >Page 2007210 > Article

Chinese Journal of Lasers
Vol. 49, Issue 20, 2007210 (2022)

Lung CT Image Enhancement Based on Image Segmentation and Total Variational

Hongfei Wang^1、2、3, ShiQing Ma^1、2, Lei Min^1、2, Shuai Wang^1、2, Wei Yang^5、***, Chuan Xu^4、**, and Ping Yang^1、2、*

Author Affiliations

¹Key Laboratory of Adaptive Optics, Chinese Academy of Sciences, Chengdu 610209, Sichuan, China

²Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, Sichuan, China

³School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China

⁴Affiliated Cancer Hospital of University of Electronic Science and Technology of China/Sichuan Cancer Hospital, Chengdu 610209, Sichuan, China

⁵School of Aeronautics and Astronautics Xihua University, Chengdu 610209, Sichuan, China

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DOI: 10.3788/CJL202249.2007210 Cite this Article Set citation alerts

Hongfei Wang, ShiQing Ma, Lei Min, Shuai Wang, Wei Yang, Chuan Xu, Ping Yang. Lung CT Image Enhancement Based on Image Segmentation and Total Variational[J]. Chinese Journal of Lasers, 2022, 49(20): 2007210 Copy Citation Text

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Fig. 1. Twice wavelet transformation of image

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Fig. 2. Flowchart of proposed algorithm

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Fig. 3. Experimental results for suppressing artifacts by different algorithms. (a) Original image screenshot; (b) WTHE algorithm; (c) GAAHE algorithm; (d) CLAHE algorithm; (e) KH-RHE algorithm; (f) proposed algorithm

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Fig. 4. Experimental results of proposed algorithm and comparison algorithms on test data sets

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