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Fiber bundle image restoration using deep learning
Shao, Jianbo1,2; Zhang JC(张俊超)1,3; Huang, Xiao1,4; Liang, Rongguang1; Barnard, Kobus2,5
Department光电信息技术研究室
Source PublicationOptics Letters
ISSN0146-9592
2019
Volume44Issue:5Pages:1080-1083
Indexed BySCI ; EI
EI Accession number20191006584066
WOS IDWOS:000460109200005
Contribution Rank2
Funding OrganizationNational Institute of Biomedical Imaging and Bioengineering (NIBIB)
AbstractWe propose a deep learning-based restoration method to remove honeycomb patterns and improve resolution for fiber bundle (FB) images. By building and calibrating a dual-sensor imaging system, we capture FB images and corresponding ground truth data to train the network. Images without fiber bundle fixed patterns are restored from raw FB images as direct inputs, and spatial resolution is significantly enhanced for the trained sample type. We also construct the brightness mapping between the two image types for the effective use of all data, providing the ability to output images of the expected brightness. We evaluate our framework with data obtained from lens tissues and human histological specimens using both objective and subjective measures. © 2019 Optical Society of America.
Language英语
WOS SubjectOptics
WOS Research AreaOptics
Funding ProjectNational Institute of Biomedical Imaging and Bioengineering (NIBIB)[R21EB022378] ; National Institute of Biomedical Imaging and Bioengineering (NIBIB)[R21EB022378]
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/24406
Collection光电信息技术研究室
Corresponding AuthorLiang, Rongguang
Affiliation1.College of Optical Sciences, University of Arizona, Tucson, AZ 85721, United States
2.Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ 85721, United States
3.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning Province 110016, China
4.College of Optical Science and Engineering, Zhejiang University, Hangzhou
5.Zhejiang Province 310027, China
6.Department of Computer Science, University of Arizona, Tucson, AZ 85721, United States
Recommended Citation
GB/T 7714
Shao, Jianbo,Zhang JC,Huang, Xiao,et al. Fiber bundle image restoration using deep learning[J]. Optics Letters,2019,44(5):1080-1083.
APA Shao, Jianbo,Zhang JC,Huang, Xiao,Liang, Rongguang,&Barnard, Kobus.(2019).Fiber bundle image restoration using deep learning.Optics Letters,44(5),1080-1083.
MLA Shao, Jianbo,et al."Fiber bundle image restoration using deep learning".Optics Letters 44.5(2019):1080-1083.
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