CVDATA-ANOPTICSJun 6, 2018

Quantitative Phase Imaging and Artificial Intelligence: A Review

arXiv:1806.03982v2165 citations
Originality Synthesis-oriented
AI Analysis

It addresses the integration of imaging and AI for biomedical research, but it is a review paper, so it is incremental by nature.

This review explores the synergy between quantitative phase imaging (QPI) and artificial intelligence (AI), highlighting how QPI generates large-scale, label-free imaging data and AI techniques, especially deep learning, enhance biomedical applications and improve QPI itself.

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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