Analysis of cellular objects through diffraction images acquired by flow cytometry
Author(s) -
Jun Zhang,
Yuanming Feng,
Marina S. Moran,
Jun Q. Lu,
Li V. Yang,
Yu Sa,
Ning Zhang,
Lixue Dong,
XinHua Hu
Publication year - 2013
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.21.024819
Subject(s) - diffraction , optics , categorical variable , sample (material) , image processing , computer science , scattering , artificial intelligence , pattern recognition (psychology) , physics , image (mathematics) , machine learning , thermodynamics
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.
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