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High space-bandwidth in quantitative phase imaging using partially spatially coherent digital holographic microscopy and a deep neural network

Permanent link
https://hdl.handle.net/10037/19938
DOI
https://doi.org/10.1364/OE.402666
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Date
2020-11-16
Type
Journal article
Tidsskriftartikkel
Peer reviewed

Author
Butola, Ankit; Kanade, Sheetal Raosaheb; Bhatt, Sunil; Dubey, Vishesh Kumar; Kumar, Anand; Ahmad, Azeem; Prasad, Dilip K.; Senthilkumaran, Paramasivam; Ahluwalia, Balpreet Singh; Mehta, Dalip Singh
Abstract
Quantitative phase microscopy (QPM) is a label-free technique that enables monitoring of morphological changes at the subcellular level. The performance of the QPM system in terms of spatial sensitivity and resolution depends on the coherence properties of the light source and the numerical aperture (NA) of objective lenses. Here, we propose high space-bandwidth quantitative phase imaging using partially spatially coherent digital holographic microscopy (PSC-DHM) assisted with a deep neural network. The PSC source synthesized to improve the spatial sensitivity of the reconstructed phase map from the interferometric images. Further, compatible generative adversarial network (GAN) is used and trained with paired low-resolution (LR) and high-resolution (HR) datasets acquired from the PSC-DHM system. The training of the network is performed on two different types of samples, i.e. mostly homogenous human red blood cells (RBC), and on highly heterogeneous macrophages. The performance is evaluated by predicting the HR images from the datasets captured with a low NA lens and compared with the actual HR phase images. An improvement of 9× in the space-bandwidth product is demonstrated for both RBC and macrophages datasets. We believe that the PSC-DHM + GAN approach would be applicable in single-shot label free tissue imaging, disease classification and other high-resolution tomography applications by utilizing the longitudinal spatial coherence properties of the light source.
Publisher
Optical Society of America
Citation
Butola A, Kanade, Bhatt, Dubey VK, Kumar A, Ahmad A, Prasad DK, Senthilkumaran P, Ahluwalia BS, Mehta DS. High space-bandwidth in quantitative phase imaging using partially spatially coherent digital holographic microscopy and a deep neural network. Optics Express. 2020;28(24):36229-36244
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