Parameter estimation of the structured illumination pattern based on principal component analysis (PCA): PCA-SIM

被引：6

作者：

Chen, Xin ^{[1
,2
]}

Hou, Yiwei ^{[1
,2
]}

Xi, Peng ^{[1
,2
]}

机构：

[1] Peking Univ, Coll Future Technol, Dept Biomed Engn, Beijing 100871, Peoples R China

[2] Peking Univ, Natl Biomed Imaging Ctr, Beijing 100871, Peoples R China

来源：

LIGHT-SCIENCE & APPLICATIONS | 2023年 / 12卷 / 01期

关键词：

PHASE-SHIFT ESTIMATION; MICROSCOPY; LIVE; CELLS;

D O I：

10.1038/s41377-022-01043-9

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

Principal component analysis (PCA), a common dimensionality reduction method, is introduced into SIM to identify the frequency vectors and pattern phases of the illumination pattern with precise subpixel accuracy, fast speed, and noise-robustness, which is promising for real-time and long-term live-cell imaging.

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页数：3

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