  Investigation of cell structure is hardly imaginable without bright-field
microscopy. Numerous modifications such as depth-wise scanning or
videoenhancement make this method being state-of-the-art. This raises a
question what maximal information can be extracted from ordinary (but well
acquired) bright-field images in a model-free way. Here we introduce a method
of a physically correct extraction of features for each pixel when these
features resemble a transparency spectrum. The method is compatible with
existent ordinary bright-field microscopes and requires mathematically
sophisticated data processing. Unsupervised clustering of the spectra yields
reasonable semantic segmentation of unstained living cells without any a priori
information about their structures. Despite the lack of reference data (to
prove strictly that the proposed feature vectors coincide with transparency),
we believe that this method is the right approach to an intracellular
(semi)quantitative and qualitative chemical analysis.
