Affiliation:
1. UiT The Arctic University of Norway
2. Indian Institute of Technology Delhi
Abstract
Multispectral quantitative phase imaging (MS-QPI) is a high-contrast label-free technique for morphological imaging of the specimens. The aim of the present study is to extract spectral dependent quantitative information in single-shot using a highly spatially sensitive digital holographic microscope assisted by a deep neural network. There are three different wavelengths used in our method: λ=532, 633, and 808 nm. The first step is to get the interferometric data for each wavelength. The acquired datasets are used to train a generative adversarial network to generate multispectral (MS) quantitative phase maps from a single input interferogram. The network was trained and validated on two different samples: the optical waveguide and MG63 osteosarcoma cells. Validation of the present approach is performed by comparing the predicted MS phase maps with numerically reconstructed (FT+TIE) phase maps and quantifying with different image quality assessment metrices.
Funder
Norges Forskningsråd
Council of Scientific and Industrial Research, India
Subject
Atomic and Molecular Physics, and Optics,Engineering (miscellaneous),Electrical and Electronic Engineering
Cited by
1 articles.
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