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Noise learning of instruments for high-contrast, high-resolution and fast hyperspectral microscopy and nanoscopy

Author

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  • Hao He

    (Xiamen University
    Xiamen University
    Southern University of Science and Technology)

  • Maofeng Cao

    (Xiamen University)

  • Yun Gao

    (Xiamen University)

  • Peng Zheng

    (Xiamen University)

  • Sen Yan

    (Xiamen University)

  • Jin-Hui Zhong

    (Southern University of Science and Technology)

  • Lei Wang

    (Xiamen University)

  • Dayong Jin

    (Southern University of Science and Technology
    University of Technology Sydney)

  • Bin Ren

    (Xiamen University
    Tan Kah Kee Innovation Laboratory)

Abstract

The low scattering efficiency of Raman scattering makes it challenging to simultaneously achieve good signal-to-noise ratio (SNR), high imaging speed, and adequate spatial and spectral resolutions. Here, we report a noise learning (NL) approach that estimates the intrinsic noise distribution of each instrument by statistically learning the noise in the pixel-spatial frequency domain. The estimated noise is then removed from the noisy spectra. This enhances the SNR by ca. 10 folds, and suppresses the mean-square error by almost 150 folds. NL allows us to improve the positioning accuracy and spatial resolution and largely eliminates the impact of thermal drift on tip-enhanced Raman spectroscopic nanoimaging. NL is also applicable to enhance SNR in fluorescence and photoluminescence imaging. Our method manages the ground truth spectra and the instrumental noise simultaneously within the training dataset, which bypasses the tedious labelling of huge dataset required in conventional deep learning, potentially shifting deep learning from sample-dependent to instrument-dependent.

Suggested Citation

  • Hao He & Maofeng Cao & Yun Gao & Peng Zheng & Sen Yan & Jin-Hui Zhong & Lei Wang & Dayong Jin & Bin Ren, 2024. "Noise learning of instruments for high-contrast, high-resolution and fast hyperspectral microscopy and nanoscopy," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-44864-5
    DOI: 10.1038/s41467-024-44864-5
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    1. Tianye Huang & Xuecou Tu & Changqing Shen & Binjie Zheng & Junzhuan Wang & Hao Wang & Kaveh Khaliji & Sang Hyun Park & Zhiyong Liu & Teng Yang & Zhidong Zhang & Lei Shao & Xuesong Li & Tony Low & Yi S, 2022. "Observation of chiral and slow plasmons in twisted bilayer graphene," Nature, Nature, vol. 605(7908), pages 63-68, May.
    2. Cheng Zong & Ranjith Premasiri & Haonan Lin & Yimin Huang & Chi Zhang & Chen Yang & Bin Ren & Lawrence D. Ziegler & Ji-Xin Cheng, 2019. "Plasmon-enhanced stimulated Raman scattering microscopy with single-molecule detection sensitivity," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
    3. R. Zhang & Y. Zhang & Z. C. Dong & S. Jiang & C. Zhang & L. G. Chen & L. Zhang & Y. Liao & J. Aizpurua & Y. Luo & J. L. Yang & J. G. Hou, 2013. "Chemical mapping of a single molecule by plasmon-enhanced Raman scattering," Nature, Nature, vol. 498(7452), pages 82-86, June.
    4. Chi-Sing Ho & Neal Jean & Catherine A. Hogan & Lena Blackmon & Stefanie S. Jeffrey & Mark Holodniy & Niaz Banaei & Amr A. E. Saleh & Stefano Ermon & Jennifer Dionne, 2019. "Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning," Nature Communications, Nature, vol. 10(1), pages 1-8, December.
    5. Joonhee Lee & Kevin T. Crampton & Nicholas Tallarida & V. Ara Apkarian, 2019. "Visualizing vibrational normal modes of a single molecule with atomically confined light," Nature, Nature, vol. 568(7750), pages 78-82, April.
    6. Logan G. Wright & Tatsuhiro Onodera & Martin M. Stein & Tianyu Wang & Darren T. Schachter & Zoey Hu & Peter L. McMahon, 2022. "Deep physical neural networks trained with backpropagation," Nature, Nature, vol. 601(7894), pages 549-555, January.
    7. Jian Feng Li & Yi Fan Huang & Yong Ding & Zhi Lin Yang & Song Bo Li & Xiao Shun Zhou & Feng Ru Fan & Wei Zhang & Zhi You Zhou & De Yin Wu & Bin Ren & Zhong Lin Wang & Zhong Qun Tian, 2010. "Shell-isolated nanoparticle-enhanced Raman spectroscopy," Nature, Nature, vol. 464(7287), pages 392-395, March.
    8. Håkon Høgset & Conor C. Horgan & James P. K. Armstrong & Mads S. Bergholt & Vincenzo Torraca & Qu Chen & Timothy J. Keane & Laurence Bugeon & Margaret J. Dallman & Serge Mostowy & Molly M. Stevens, 2020. "In vivo biomolecular imaging of zebrafish embryos using confocal Raman spectroscopy," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
    9. Luhong Jin & Bei Liu & Fenqiang Zhao & Stephen Hahn & Bowei Dong & Ruiyan Song & Timothy C. Elston & Yingke Xu & Klaus M. Hahn, 2020. "Deep learning enables structured illumination microscopy with low light levels and enhanced speed," Nature Communications, Nature, vol. 11(1), pages 1-7, December.
    10. Charalambos Kallepitis & Mads S. Bergholt & Manuel M. Mazo & Vincent Leonardo & Stacey C. Skaalure & Stephanie A. Maynard & Molly M. Stevens, 2017. "Quantitative volumetric Raman imaging of three dimensional cell cultures," Nature Communications, Nature, vol. 8(1), pages 1-9, April.
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