It was found that the diffraction images acquired along the side scattering directions with objects in a cell sample contain pattern variations at both the global and local scales. We show here that the global pattern variation is associated with the categorical size and morphological heterogeneity of the imaged objects. An automated image processing method has been developed to separate the acquired diffraction images into three types of global patterns. Combined with previously developed method for quantifying local texture pattern variations, the new method allows fully automated analysis of diffraction images for rapid and label-free classification of cells according to their 3D morphology.
We report a novel method of diffraction imaging flow cytometry to measure and analyze size distribution of microspheres. An automated and robust image processing software based on the short-time-Fourier-transform algorithm has been developed to analyze the characteristic and spatially varying oscillations of side scatters recorded as a diffraction image. Our results demonstrate that the new method allows accurate and rapid determination of single microspheres' diameters ranging from 1 to 100 μm. The capacity for analysis of light scattering by two-sphere aggregates has been demonstrated but analytical tools for characterization of aggregates by multiple microspheres remain to be developed.
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