Polarization fingerprint for microalgae classification

Li, Jiajin; Wei, Jinfu; Liu, Hongyuan; Wan, Jiachen; Huang, Tongyu; Wang, Hongjian; Yan, Meng; Ma, Hui

doi:10.1016/j.optlaseng.2023.107567

Cited by 8 publications

(1 citation statement)

References 31 publications

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“…Polarization measurement technology has many advantages, such as sensitivity to the anisotropic microstructure of samples, non-destructive to the samples, and high optical structural compatibility, therefore it has played an important role in marine particle detection [1], material analysis [2], and biomedical fields [3]. Among different polarization measurement methods, Mueller matrix microscopy can obtain the full-polarization properties of the sample and has gradually received more and more attention in recent years.…”

Section: Introductionmentioning

confidence: 99%

Analysis and evaluation of measurement errors in Mueller matrix microscopy

Huang,

Hu,

2024

Polarized Light and Optical Angular Momentum for Biomedical Diagnostics 2024

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Mueller matrix microscopy can provide a comprehensive description of sample’s polarization properties non-invasively, and has shown attractive applications in many different fields such as biomedicine, marine particle monitoring, and material identification. Mueller matrix measurements are based on multiple light intensity measurements under illuminations of different polarization states, therefore have more error sources compared to other imaging methods, which reduce the image quality and hinder efforts for quantitatively characterizing the polarization features of weak polarization biological samples such as living cells. Measurement errors of a Mueller matrix microscope are mainly classified into three categories including systematical error, random noise, and mismatch error. In this paper, based on the physical realizability of Mueller matrix and image frequency analysis, different categories and sources of measurement errors in Mueller matrix microscopy are analyzed in detail, a no-reference Mueller matrix image quality evaluator (MIQE) is also proposed to estimate the error level of biomedical sample’s Mueller matrix.

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Section: Introductionmentioning

confidence: 99%