Morphologic tomography of nonspherical particles using multispectral diffusing light measurements

Hajihashemi, Mohammad Reza; Li, Xiaoqi; Jiang, Huabei

doi:10.1117/1.3650313

Cited by 5 publications

(1 citation statement)

References 22 publications

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“…Using experimental data, we already extracted the aspect ratio ( ε ) in spheroidal particles, with a T-matrix based inverse algorithm [2]. The aspect ratio ( ε ) is the ratio of the equatorial radius to the polar radius of the base spheroid.…”

Section: Introductionmentioning

confidence: 99%

Gaussian random ellipsoid geometry-based morphometric recovery of irregular particles using light scattering spectroscopy

Hajihashemi

Jiang

2013

Journal of Quantitative Spectroscopy and Radiative Transfer

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The purpose of this study is to extend the capabilities of multispectral optical imaging techniques for morphological characterization of irregular particles, encountered in several applications. We have utilized the Gaussian random ellipsoid model to quantize the shape elongation and deviation in complex-shaped particles. Compared with the Gaussian random sphere model, it is more realistic and is applicable to wider range of irregular particles with minimum possible of free parameters. By processing the reduced light scattering spectra, the proposed inverse technique can simultaneously recover the size, volume fraction, elongation, and shape deformation of particles that are randomly oriented within a colloidal suspension. The discrete dipole approximation is employed in forward light scattering calculations and input synthetic data generation. To investigate the robustness of our algorithm in coping with real scenarios, we have added different levels of noise to the observed scattering spectra. The results demonstrate the potential of our technique to non-invasively recover the morphology parameters of irregular particles.

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Section: Introductionmentioning

confidence: 99%

Gaussian random ellipsoid geometry-based morphometric recovery of irregular particles using light scattering spectroscopy

Hajihashemi

Jiang

2013

Journal of Quantitative Spectroscopy and Radiative Transfer

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Convolutional neural networks for particle shape classification using light-scattering patterns

Ding

2020

Journal of Quantitative Spectroscopy and Radiative Transfer

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Scattering pulse of label free fine structure cells to determine the size scale of scattering structures

Zhang

Chen

Zhang

et al. 2016

Review of Scientific Instruments

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Scattering pulse is sensitive to the morphology and components of each single label-free cell. The most direct detection result, label free cell's scattering pulse is studied in this paper as a novel trait to recognize large malignant cells from small normal cells. A set of intrinsic scattering pulse calculation method is figured out, which combines both hydraulic focusing theory and small particle's scattering principle. Based on the scattering detection angle ranges of widely used flow cytometry, the scattering pulses formed by cell scattering energy in forward scattering angle 2°-5° and side scattering angle 80°-110° are discussed. Combining the analysis of cell's illuminating light energy, the peak, area, and full width at half maximum (FWHM) of label free cells' scattering pulses for fine structure cells with diameter 1-20 μm are studied to extract the interrelations of scattering pulse's features and cell's morphology. The theoretical and experimental results show that cell's diameter and FWHM of its scattering pulse agree with approximate linear distribution; the peak and area of scattering pulse do not always increase with cell's diameter becoming larger, but when cell's diameter is less than about 16 μm the monotone increasing relation of scattering pulse peak or area with cell's diameter can be obtained. This relationship between the features of scattering pulse and cell's size is potentially a useful but very simple criterion to distinguishing malignant and normal cells by their sizes and morphologies in label free cells clinical examinations.

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Morphologic tomography of nonspherical particles using multispectral diffusing light measurements

Cited by 5 publications

References 22 publications

Gaussian random ellipsoid geometry-based morphometric recovery of irregular particles using light scattering spectroscopy

Gaussian random ellipsoid geometry-based morphometric recovery of irregular particles using light scattering spectroscopy

Convolutional neural networks for particle shape classification using light-scattering patterns

Scattering pulse of label free fine structure cells to determine the size scale of scattering structures

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