Resolution enhancement of wide-field interferometric microscopy by coupled deep autoencoders
Author(s)
Date
2018Source Title
Applied Optics
Print ISSN
1559-128X
Publisher
OSA - The Optical Society
Volume
57
Issue
10
Pages
2545 - 2552
Language
English
Type
ArticleItem 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.