Quantitative Phase Imaging and Artificial Intelligence: A Review

TL;DR

This review discusses how recent advances in quantitative phase imaging combined with artificial intelligence, especially deep learning, are transforming biomedical applications through rapid, label-free imaging and data analysis.

Contribution

It provides a comprehensive overview of the integration of QPI and AI, highlighting recent progress, practical guidelines, and future perspectives in this emerging field.

Findings

QPI enables rapid, label-free, multi-dimensional imaging.

AI enhances both the analysis and capabilities of QPI.

The synergy leads to significant biomedical applications.

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.