Deep learning-based spectroscopic single-molecule localization microscopy.

Journal: Journal of biomedical optics
PMID: 38799979

Abstract

SIGNIFICANCE: Spectroscopic single-molecule localization microscopy (sSMLM) takes advantage of nanoscopy and spectroscopy, enabling sub-10 nm resolution as well as simultaneous multicolor imaging of multi-labeled samples. Reconstruction of raw sSMLM data using deep learning is a promising approach for visualizing the subcellular structures at the nanoscale.

Authors

  • Sunil Kumar Gaire
    North Carolina Agricultural and Technical State University, Department of Electrical and Computer Engineering, Greensboro, North Carolina, United States.
  • Ali Daneshkhah
    Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA.
  • Ethan Flowerday
    University of Tulsa, Department of Computer Science and Cyber Security, Tulsa, Oklahoma, United States.
  • Ruyi Gong
    Northwestern University, Department of Biomedical Engineering, Evanston, Illinois, United States.
  • Jane Frederick
    Northwestern University, Department of Biomedical Engineering, Evanston, Illinois, United States.
  • Vadim Backman
    Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA. v-backman@northwestern.edu.

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