Reconstruction of structured illumination microscopy with an untrained neural network | |
Liu, Xin1![]() ![]() ![]() ![]() | |
作者部门 | 瞬态光学研究室 |
2023-06-15 | |
发表期刊 | OPTICS COMMUNICATIONS
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ISSN | 0030-4018;1873-0310 |
卷号 | 537 |
产权排序 | 3 |
摘要 | Structured illumination microscopy (SIM) is one of super-resolution optical microscopic techniques, and it has been widely used in biological research. In this paper, a physics-driven deep image prior framework for super-resolution reconstruction of SIM (entitled DIP-SIM) is proposed. DIP-SIM does not rely on a large number of labeled data, and the output becomes more interpretable due to the intrinsic constraint of a physical model. Both the simulation and experiment verify that DIP-SIM can reconstruct a super-resolution image with a quality comparable to conventional SIM. Of note, it allows for super-resolution reconstruction from three raw images for two-orientation SIM and four raw images for three-orientation SIM, and hence it has a much faster imaging speed and lower photobleaching compared with the traditional SIM. We can envisage that the proposed method can be applied to chemistry and biomedical fields, etc. |
关键词 | Structured illumination microscopy Deep learning Neural network Super-resolution Image reconstruction |
DOI | 10.1016/j.optcom.2023.129431 |
收录类别 | SCI |
语种 | 英语 |
WOS记录号 | WOS:001162906900001 |
出版者 | ELSEVIER |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/97228 |
专题 | 瞬态光学研究室 |
通讯作者 | Zuo, Chao; Gao, Peng; An, Sha |
作者单位 | 1.Xidian Univ, Sch Phys, Xian, Peoples R China 2.Xidian Univ, Sch Optoelect Engn, Xian 710071, Peoples R China 3.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Xian 710119, Peoples R China 4.Nanjing Univ Sci & Technol, Sch Elect & Opt Engn, Smart Computat Imaging Lab SCILab, Nanjing, Peoples R China |
推荐引用方式 GB/T 7714 | Liu, Xin,Li, Jinze,Fang, Xiang,et al. Reconstruction of structured illumination microscopy with an untrained neural network[J]. OPTICS COMMUNICATIONS,2023,537. |
APA | Liu, Xin.,Li, Jinze.,Fang, Xiang.,Li, Jiaoyue.,Zheng, Juanjuan.,...&An, Sha.(2023).Reconstruction of structured illumination microscopy with an untrained neural network.OPTICS COMMUNICATIONS,537. |
MLA | Liu, Xin,et al."Reconstruction of structured illumination microscopy with an untrained neural network".OPTICS COMMUNICATIONS 537(2023). |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Reconstruction of st(3641KB) | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 请求全文 |
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