Image analysis and pattern recognition are key elements of many biomedical analysis schemes. In this work,
we show the use of pattern recognition and classification for the study of an interesting biomedical problem-
the prediction of organelle arrangement within a cell based on wide-angle light scattering patterns. Organelle
distribution is known to relate to disease and drug resistance. However, up until this point it has been unclear
how changes to organelle distribution relate to the composition of wide-angle light scattering patterns. As such,
we use a rapid new scattering simulation method and standard pattern analysis techniques to demonstrate
clear correlations between scattering pattern composition and organelle distribution. The texture of scattering
images-specifically the spot and edge content of samples is found to directly relate to the type and size of
organelle distributions within a cell. These relationships are used to quickly classify organelle distributions to a
high degree of accuracy.
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