Radial distortion evaluation and correction of dual-channel microscopic imaging system in quantitative FRET imaging

• Radial distortion evaluation and correction of cameras in microscopic imaging system . • Using real captured images for building distortion models rather than data simulation. • Use checkerboard images and fluorescent pattern images to test distortion models. • Carry out E-FRET experiments to verify the improvement of the accuracy of the experimental results before and after distortion correction. Fluorescence resonance energy transfer (FRET) technology is widely used for real-time quantitative detection of protein interactions in living cells. Among FRET measurement techniques, Channel-based sensitized emission method (E-FRET) is becoming the most popular method due to its rapid detection, non-destructive nature, operational simplicity, and compatibility with both wide-field and confocal microscopy. In FRET imaging, image quality is crucial for the success of the FRET experiment. However, distortion, an inevitable problem for any microscopic imaging system equipped with an optical lens, often compromises image quality. The most important distortion type is radial distortion. This paper focuses on the radial distortion degree and distribution of cameras and the influence of image distortion on E-FRET experiments in the dual-channel microscopic imaging system. We fit multiple models to correct the radial distortion of the cameras and compare the quality of E-FRET imaging and the accuracy of FRET efficiency calculation before and after distortion correction. The final E-FRET imaging experiment demonstrates that distortion correction significantly enhances imaging quality and experimental accuracy.

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Publication Details

Journal
Optics and Lasers in Engineering
Published
2025-04-15
DOI
https://doi.org/10.1016/j.optlaseng.2025.109005
Primary Topic
Integrated Circuits and Semiconductor Failure Analysis
Type
article
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article

Radial distortion evaluation and correction of dual-channel microscopic imaging system in quantitative FRET imaging

Zhengfei Zhuang, Min Hu, Wang Zheng-yin, Jian Wang et al.
Optics and Lasers in Engineering
Integrated Circuits and Semiconductor Failure Analysis
article

Radial distortion evaluation and correction of dual-channel microscopic imaging system in quantitative FRET imaging

Zhengfei Zhuang, Min Hu, Wang Zheng-yin, Jian Wang, G. Zhuang
article en

Abstract

• Radial distortion evaluation and correction of cameras in microscopic imaging system . • Using real captured images for building distortion models rather than data simulation. • Use checkerboard images and fluorescent pattern images to test distortion models. • Carry out E-FRET experiments to verify the improvement of the accuracy of the experimental results before and after distortion correction. Fluorescence resonance energy transfer (FRET) technology is widely used for real-time quantitative detection of protein interactions in living cells. Among FRET measurement techniques, Channel-based sensitized emission method (E-FRET) is becoming the most popular method due to its rapid detection, non-destructive nature, operational simplicity, and compatibility with both wide-field and confocal microscopy. In FRET imaging, image quality is crucial for the success of the FRET experiment. However, distortion, an inevitable problem for any microscopic imaging system equipped with an optical lens, often compromises image quality. The most important distortion type is radial distortion. This paper focuses on the radial distortion degree and distribution of cameras and the influence of image distortion on E-FRET experiments in the dual-channel microscopic imaging system. We fit multiple models to correct the radial distortion of the cameras and compare the quality of E-FRET imaging and the accuracy of FRET efficiency calculation before and after distortion correction. The final E-FRET imaging experiment demonstrates that distortion correction significantly enhances imaging quality and experimental accuracy.

Optics and Lasers in EngineeringVol. 191
South China Normal University (CN), Zhuhai Institute of Advanced Technology (CN)
Openalex Percentile: Top 94%
Integrated Circuits and Semiconductor Failure Analysis
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