Holographic polarization microscopy using deep learning

Tairan Liu; Kevin de Haan; Bijie Bai; Yair Rivenson; Yi Luo; Hongda Wang; David Karalli; Hongxiang Fu; Yibo Zhang; John FitzGerald; Aydogan Ozcan

doi:10.1117/12.2580286

5 March 2021 Holographic polarization microscopy using deep learning

Tairan Liu, Kevin de Haan, Bijie Bai, Yair Rivenson, Yi Luo, Hongda Wang, David Karalli, Hongxiang Fu, Yibo Zhang, John FitzGerald, Aydogan Ozcan

Author Affiliations +

Proceedings Volume 11653, Quantitative Phase Imaging VII; 116530C (2021) https://doi.org/10.1117/12.2580286
Event: SPIE BiOS, 2021, Online Only

Abstract

We present a deep learning-enabled holographic polarization microscope that only requires one polarization state to image/quantify birefringent specimen. This framework reconstructs quantitative birefringence retardance and orientation images from the amplitude/phase information obtained using a lensless holographic microscope with a pair of polarizer and analyzer. We tested this technique with various birefringent samples including monosodium urate and triamcinolone acetonide crystals to demonstrate that the deep network can accurately reconstruct the retardance and orientation image channels. This method has a simple optical design and presents a large field-of-view (>20-30mm2), which might broaden the access to advanced polarization microscopy techniques in low-resource-settings.

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Tairan Liu, Kevin de Haan, Bijie Bai, Yair Rivenson, Yi Luo, Hongda Wang, David Karalli, Hongxiang Fu, Yibo Zhang, John FitzGerald, and Aydogan Ozcan "Holographic polarization microscopy using deep learning", Proc. SPIE 11653, Quantitative Phase Imaging VII, 116530C (5 March 2021); https://doi.org/10.1117/12.2580286

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