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

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      Author(s)
      Işıl, Ç.
      Yorulmaz, M.
      Solmaz, B.
      Turhan, Adil Burak
      Yurdakul, C.
      Ünlü, S.
      Özbay, Ekmel
      Koç, A.
      Date
      2018
      Source Title
      Applied Optics
      Print ISSN
      1559-128X
      Publisher
      OSA - The Optical Society
      Volume
      57
      Issue
      10
      Pages
      2545 - 2552
      Language
      English
      Type
      Article
      Item Usage Stats
      215
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      428
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      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.
      Permalink
      http://hdl.handle.net/11693/50375
      Published Version (Please cite this version)
      https://doi.org/10.1364/AO.57.002545
      Collections
      • Department of Electrical and Electronics Engineering 4011
      • Department of Physics 2550
      • Nanotechnology Research Center (NANOTAM) 1179
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