Traditional light scattering analysis of cells relies mostly on the one-dimensional distribution of the light scattering
intensity, where only the cell size and some limited information regarding the internal structure can be obtained. More
recent studies have attempted to analyze the two-dimensional diffraction images of cells using standard texture analysis
techniques to extract additional intracellular information. We recently compared the effectiveness of several major
methods that are often used in image texture analysis and found that the Gabor filter approach is more effective than
most methods and is capable of providing information regarding the major structural features and mitochondrial
properties of the cell. In this report we further our investigation by utilizing a Gabor filter technique to analyze light
scattering patterns of cells and to correlate their changes to that of the mitochondrial properties of the cells. Numerical
simulations of light scattering are performed using the discrete dipole approximation on analytically generated biological
cell models with various mitochondrial characteristics. A set of two-dimensional scattering images is produced
corresponding to systematic variations in the size, shape, and distribution of mitochondria and is processed with a bank
of Gabor filters. Selected mean values of the Gabor-filtered images are displayed in scatter plots, providing a novel
approach to grouping the cell models according to mitochondria size, shape, and distribution.
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