Bessel beam illuminated digital holographic microscopy for anti-scattering quantitative phase imaging

Z Zhiwen Mu (School of Artificial Intelligence Science and Technology, University of Shanghai for Science and Technology 1 , Shanghai 200093,) J Jianxin Lin (School of Artificial Intelligence Science and Technology, University of Shanghai for Science and Technology 1 , Shanghai 200093,) Y Yanping He B Baoli Li X Xinyuan Fang

Abstract

Quantitative phase imaging (QPI) is a powerful noninvasive and label-free technique widely used in biomedical measurement, including cellular analysis and disease diagnosis. Among various QPI techniques, digital holographic microscopy (DHM) has attracted growing attention, owing to its high-precision and high-speed imaging capabilities. However, reliable phase imaging of thick or highly scattering samples remains a substantial challenge for existing DHM methods due to rapid degradation of spatial coherence of object wave. Here, we report an anti-scattering DHM method that integrates DHM with Bessel beam illumination. Leveraging the self-healing and scattering-resilient properties of Bessel beams, our approach maintains stable phase retrieval across scattering layers exceeding 50 μm. The approach achieves 16-fold enhancement in imaging quality, compared to conventional Gaussian beam illumination. Both numerical simulations and experimental results demonstrate that our approach provides significantly enhanced imaging robustness compared to Gaussian beam. This work establishes a promising pathway toward reliable DHM of complex biological specimens and scattering media, and it can be easily extended to other QPI techniques.

Article Details

Volume / Issue Vol. 128, Issue 14
Published April 06, 2026
ISSN 0003-6951
Publisher American Institute of Physics

Journal Info

Applied Physics Letters

American Institute of Physics

ISSN: 0003-6951 Physical Sciences

Authors (5)

Z

Zhiwen Mu

School of Artificial Intelligence Science and Technology, University of Shanghai for Science and Technology 1 , Shanghai 200093,

J

Jianxin Lin

School of Artificial Intelligence Science and Technology, University of Shanghai for Science and Technology 1 , Shanghai 200093,

Y

Yanping He

B

Baoli Li

X

Xinyuan Fang