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arXiv · 1806.03982

Quantitative Phase Imaging and Artificial Intelligence: A Review

YoungJu Jo·Hyungjoo Cho·Sang Yun Lee·Gunho Choi·Geon Kim·Hyun-seok Min·YongKeun Park
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Abstract

Recent advances in quantitative phase imaging (QPI) and artificial intelligence (AI) have opened up the possibility of an exciting frontier. The fast and label-free nature of QPI enables the rapid generation of large-scale and uniform-quality imaging data in two, three, and four dimensions. Subsequently, the AI-assisted interrogation of QPI data using data-driven machine learning techniques results in a variety of biomedical applications. Also, machine learning enhances QPI itself. Herein, we review the synergy between QPI and machine learning with a particular focus on deep learning. Further, we provide practical guidelines and perspectives for further development.

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BibTeXRIS

YoungJu Jo, Hyungjoo Cho, Sang Yun Lee, Gunho Choi, Geon Kim, Hyun-seok Min, YongKeun Park. 2018-06-06. Quantitative Phase Imaging and Artificial Intelligence: A Review. https://arxiv.org/abs/1806.03982

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