Fig. 1 | Scientific Reports

Fig. 1

From: Spatial mapping of influenza and coronavirus receptors in the respiratory and intestinal tract epithelium of beef cattle using advanced PixF image analysis

Fig. 1

PixF workflow—color scheme analysis, chromaticity mapping, and image segmentation modules. (A) PixF has been built to learn multiple color schemes used for different biological imaging experiments spanning scales of life. (B) By reasoning over the data, PixF can identify a color palette (albeit without directionality) where the user should indicate which end of the spectrum is high and which is low. (C) A chromaticity analysis enables projecting the travel of a color palette from a given image on the visible spectrum (convex hull). This is important for calculating the definitions of neighborhoods for a given color in the image. For example, Rainbow and Custom Scales have a larger travel and hence have a larger neighborhood for each color in comparison to FuchsiaTones. This means sensitivity towards variance in pixel-level intensity for FuchsiaTones must be stringent during PixF analysis. (D) Overview of the image segmentation, color picker (without a palette), and analyzer modules in PixF.

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