显微镜
材料科学
相(物质)
多路复用
纳米技术
光学
光电子学
物理
计算机科学
电信
量子力学
作者
Junxiao Zhou,Ang Li,Ming Lei,Jie Hu,Guanghao Chen,Zachary Burns,Fanglin Tian,Xinyu Chen,Yu-Hwa Lo,Din Ping Tsai,Zhaowei Liu
出处
期刊:Nano Letters
[American Chemical Society]
日期:2025-01-22
卷期号:25 (5): 2034-2040
被引量:6
标识
DOI:10.1021/acs.nanolett.4c06039
摘要
Quantitative optical phase information provides an alternative method to observe biomedical properties, where conventional phase imaging fails. Phase retrieval typically requires multiple intensity measurements and iterative computations to ensure uniqueness and robustness against detection noise. To increase the measurement speed, we propose a single-shot quantitative phase imaging method with metasurface optics that can be conveniently integrated into conventional imaging systems with minimal modification. The improvement of the measurement speed is simultaneously made possible by combining deep learning with the transport-of-intensity equation. As a proof-of-concept, we demonstrate phase retrieval on both calibrated phase objects and biological specimens by using an imaging system integrated with our metasurface. When combined with the matched neural network, the system yields result with errors as low as 5% and increased space-bandwidth-product. A multitude of commercial applications can benefit from the compactness and rapid implementation of our proposed method.
科研通智能强力驱动
Strongly Powered by AbleSci AI