2021
DOI: 10.1016/j.optlastec.2020.106700
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Spectral approach to recognize spherical particles among non-spherical ones by angle-resolved light scattering

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Cited by 13 publications
(8 citation statements)
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“…The median errors play a role of the numerical indicator of analytical quality or reliability formed by three factors above mentioned. We assume that difference between the geometry of the real erythrocyte and its optical model gives maximal contribution into the error because the near‐perfect sphered erythrocytes can be analyzed with the SFC technology with the median errors of 1.2 fl and 0.6 pg for volume and hemoglobin content, respectively [50].…”
Section: Resultsmentioning
confidence: 99%
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“…The median errors play a role of the numerical indicator of analytical quality or reliability formed by three factors above mentioned. We assume that difference between the geometry of the real erythrocyte and its optical model gives maximal contribution into the error because the near‐perfect sphered erythrocytes can be analyzed with the SFC technology with the median errors of 1.2 fl and 0.6 pg for volume and hemoglobin content, respectively [50].…”
Section: Resultsmentioning
confidence: 99%
“…The points with error bar relate to the relative number of cells measured per time unit. The line is the fitted curve described by equations from the Reference[3] with parameters shown in the frame of the real erythrocyte and its optical model gives maximal contribution into the error because the near-perfect sphered erythrocytes can be analyzed with the SFC technology with the median errors of 1.2 fl and 0.6 pg for volume and hemoglobin content, respectively[50].…”
mentioning
confidence: 99%
“…where 𝑤(𝜉) is a Hann window function. Other window functions can also be used, for example, the Blackman-Nuttall window [18,20]. The numerical calculations are performed with the fast Fourier transform.…”
Section: Measured Signal and Fourier Transformationmentioning
confidence: 99%
“…Later these two parameters were tuned to obtain a solution in a wider range of characteristics [18]. The phase spectrum found applications in non-sphericity estimation [19] and classification [20]. Here we consider the use of the phase spectrum for characterization and start with the results obtained in Ref.…”
Section: Spectral Parametersmentioning
confidence: 99%
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