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Three-dimensional optical imaging for label-free sensing and classification of microorganisms and microparticles in fluidic environments: a review [Invited]

Optics Express 2026
Rahul Sharma, Harsh Chatwani, Vidhi Singh, Vani Chhaniwal, Gyanendra Sheoran, Bahram Javidi, Arun Anand

Summary

This review paper rounds up recent advances in a 3D imaging technology that can identify tiny particles—like microplastics and microorganisms—floating in water or other fluids without needing to add dyes or labels. Using light patterns and computer analysis, the technology can tell different types of particles apart with about 84-90% accuracy, including distinguishing different plastic types and similar-looking cells. This matters because as concerns grow about microplastics in our water and food supply, having affordable, reliable tools to detect and identify these contaminants is an important step toward better monitoring and understanding their potential health impacts.

Polymers

Digital holographic microscopy provides label-free imaging and quantitative phase information for microscopic particles in aquatic and fluidic environments. In this review paper, we review a number of digital holographic microscopy (DHM) configurations, including two-beam Mach-Zehnder, lateral shearing self-referencing, and lens-less systems for imaging, analysis, and classification of biological cells and microplastic particles. Phase-based features are used to classify morphologically similar yeast cells, achieving an accuracy of ∼90% using classical machine learning models. Lateral shearing DHM demonstrates improved temporal stability and enables three-dimensional tracking and imaging of diatoms and microspheres. A lens-less configuration is used for high-throughput imaging of highly scattering microplastics, where combined intensity and phase features enable classification of polystyrene and PMMA particles with ∼84% accuracy. The integration of digital holographic microscopy with microfluidics further enables real-time imaging and tracking under controlled flow conditions. The results show that reliable classification and characterization can be achieved using simple optical setups and engineered features, making DHM suitable for practical applications in aquatic and fluidic environments.

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