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 journalArticlepeer-review


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
Issue number10
StatePublished - Apr 1 2018
Externally publishedYes

ASJC Scopus subject areas

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


Dive into the research topics of 'Resolution enhancement of wide-field interferometric microscopy by coupled deep autoencoders'. Together they form a unique fingerprint.

Cite this