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A Camera-Like Dual-Defocus Curvature Wavefront Sensor With GPU Acceleration for Real-Time Quantitative Phase Imaging.

Wei Wang^1,2, Zihao Zhang¹, Yaxi Li³

¹School of Electronics and Information Engineering, Wuxi University, Wuxi, China.

Microscopy Research and Technique

|December 14, 2025

Summary

This summary is machine-generated.

A new camera-like curvature wavefront sensor (CWS) enables real-time, label-free cell imaging. This compact, cost-effective quantitative phase imaging (QPI) system overcomes limitations of existing solutions for dynamic biological studies.

Keywords:

curvature wavefront sensor (CWS)high frame rate imaging parallel computing plug‐and‐play quantitative phase imaging (QPI)

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Area of Science:

Biomedical Optics
Microscopy
Quantitative Phase Imaging

Background:

Quantitative Phase Imaging (QPI) offers high-contrast, label-free cell imaging.
Existing QPI systems face challenges: incompatibility with commercial microscopes, bulky designs, and slow frame rates due to complex phase reconstruction.

Purpose of the Study:

To develop a compact, cost-effective, and high-frame-rate QPI system compatible with commercial microscopes.
To overcome limitations of current QPI technologies for dynamic imaging applications.

Main Methods:

Development of a camera-like curvature wavefront sensor (CWS) integrating dual-view transport-of-intensity phase imaging.
Utilizing parallel computing for real-time phase reconstruction.
System integration within a compact module (55.7 × 58.0 × 49.4 mm³) compatible with standard microscopes.

Main Results:

The CWS system achieves 20 fps at 1024 × 1024 resolution, enabling real-time acquisition, retrieval, and visualization.
Demonstrated robust performance in field-of-view correction, phase recovery accuracy, and computational efficiency.
Validated practical utility in QPI-based flow cytometry and live-cell dynamic imaging.

Conclusions:

The developed CWS platform is a plug-and-play, cost-effective solution for practical QPI.
Its compact size, compatibility, and real-time capabilities make it suitable for dynamic biological imaging scenarios.
Offers a versatile tool for advancing label-free cell analysis in research and diagnostics.