Resolution enhancement of wide-field interferometric microscopy by coupled deep autoencoders

Çaǧatay Işil, Mustafa Yorulmaz, Berkan Solmaz, Adil Burak Turhan, Celalettin Yurdakul, Selim Ünlü, Ekmel Ozbay, Aykut Koç

Research output: Contribution to journalArticle

Abstract

Wide-field interferometric microscopy is a highly sensitive, label-free, and low-cost biosensing imaging technique capable of visualizing individual biological nanoparticles such as viral pathogens and exosomes. However, further resolution enhancement is necessary to increase detection and classification accuracy of subdiffraction-limited nanoparticles. In this study, we propose a deep-learning approach, based on coupled deep autoencoders, to improve resolution of images of L-shaped nanostructures. During training, our method utilizes microscope image patches and their corresponding manual truth image patches in order to learn the transformation between them. Following training, the designed network reconstructs denoised and resolution-enhanced image patches for unseen input.

Original languageEnglish (US)
Pages (from-to)2545-2552
Number of pages8
JournalApplied Optics
Volume57
Issue number10
DOIs
StatePublished - Apr 1 2018

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ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering (miscellaneous)
  • Electrical and Electronic Engineering

Cite this

Işil, Ç., Yorulmaz, M., Solmaz, B., Turhan, A. B., Yurdakul, C., Ünlü, S., Ozbay, E., & Koç, A. (2018). Resolution enhancement of wide-field interferometric microscopy by coupled deep autoencoders. Applied Optics, 57(10), 2545-2552. https://doi.org/10.1364/AO.57.002545