Elimination of stripe artifacts in light sheet fluorescence microscopy using an attention-based residual neural network
文献类型:期刊论文
作者 | Wei, Zechen4,5,6; Wu, Xiangjun3; Tong, Wei2; Zhang, Suhui2; Yang, Xin4,5,6; Tian, Jie1,5,6; Hui, Hui4,5,6 |
刊名 | BIOMEDICAL OPTICS EXPRESS |
出版日期 | 2022-03-01 |
卷号 | 13期号:3页码:1292-1311 |
ISSN号 | 2156-7085 |
DOI | 10.1364/BOE.448838 |
通讯作者 | Tian, Jie(tian@ieee.org) |
英文摘要 | Stripe artifacts can deteriorate the quality of light sheet fluorescence microscopy (LSFM) images. Owing to the inhomogeneous, high-absorption, or scattering objects located in the excitation light path, stripe artifacts are generated in LSFM images in various directions and types, such as horizontal, anisotropic, or multidirectional anisotropic. These artifacts severely degrade the quality of LSFM images. To address this issue, we proposed a new deep-learning based approach for the elimination of stripe artifacts. This method utilizes an encoder-decoder structure of UNet integrated with residual blocks and attention modules between successive convolutional layers. Our attention module was implemented in the residual blocks to learn useful features and suppress the residual features. The proposed network was trained and validated by generating three different degradation datasets with different types of stripe artifacts in LSFM images. Our method can effectively remove different stripes in generated and actual LSFM images distorted by stripe artifacts. Besides, quantitative analysis and extensive comparison results demonstrated that our method performs the best compared with classical image-based processing algorithms and other powerful deep-learning-based destriping methods for all three generated datasets. Thus, our method has tremendous application prospects to LSFM, and its use can be easily extended to images reconstructed by other modalities affected by the presence of stripe artifacts. (c) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement |
WOS关键词 | SINGLE-CELL RESOLUTION ; EXCITATION ; REMOVAL |
资助项目 | National Key Research and Development Program of China[2017YFA0700401] ; National Key Research and Development Program of China[2016YFC0103803] ; National Key Research and Development Program of China[2017YFA0205200] ; National Natural Science Foundation of China[62027901] ; National Natural Science Foundation of China[81527805] ; National Natural Science Foundation of China[81671851] ; National Natural Science Foundation of China[81827808] ; Youth Innovation Promotion Association of the Chinese Academy of Sciences[2018167] ; Chinese Academy of Sciences Key Technology Talent Program ; Project of High-Level Talents Team Introduction in Zhuhai City[HLHPTP201703] |
WOS研究方向 | Biochemistry & Molecular Biology ; Optics ; Radiology, Nuclear Medicine & Medical Imaging |
语种 | 英语 |
出版者 | OPTICAL SOC AMER |
WOS记录号 | WOS:000764828300003 |
资助机构 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Youth Innovation Promotion Association of the Chinese Academy of Sciences ; Chinese Academy of Sciences Key Technology Talent Program ; Project of High-Level Talents Team Introduction in Zhuhai City |
源URL | [http://ir.ia.ac.cn/handle/173211/48038] |
专题 | 自动化研究所_中国科学院分子影像重点实验室 |
通讯作者 | Tian, Jie |
作者单位 | 1.Jinan Univ, Zhuhai Peoples Hosp, Zhuhai Precis Med Ctr, Jinan 519000, Zhuhai, Peoples R China 2.Peoples Liberat Army Gen Hosp, Med Ctr 6, Dept Cardiol, Beijing 100853, Peoples R China 3.Beihang Univ, Sch Med & Engn, Beijing Adv Innovat Ctr Big Data Based Precis Med, Beijing 100083, Peoples R China 4.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100190, Peoples R China 5.Beijing Key Lab Mol Imaging, Beijing 100190, Peoples R China 6.CAS Key Lab Mol Imaging, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
推荐引用方式 GB/T 7714 | Wei, Zechen,Wu, Xiangjun,Tong, Wei,et al. Elimination of stripe artifacts in light sheet fluorescence microscopy using an attention-based residual neural network[J]. BIOMEDICAL OPTICS EXPRESS,2022,13(3):1292-1311. |
APA | Wei, Zechen.,Wu, Xiangjun.,Tong, Wei.,Zhang, Suhui.,Yang, Xin.,...&Hui, Hui.(2022).Elimination of stripe artifacts in light sheet fluorescence microscopy using an attention-based residual neural network.BIOMEDICAL OPTICS EXPRESS,13(3),1292-1311. |
MLA | Wei, Zechen,et al."Elimination of stripe artifacts in light sheet fluorescence microscopy using an attention-based residual neural network".BIOMEDICAL OPTICS EXPRESS 13.3(2022):1292-1311. |
入库方式: OAI收割
来源:自动化研究所
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