Cell layers estimation. Example of the typical sub-results from thickness evaluation step. (A) Color segmentation to separate nuclei from the rest of the image. (B) The black and white mask generated by Hildebrand and Ruegsegger algorithm. (C) Histogram of the image intensity, showing the number of pixels counted for each histogram bin in both normal (red) and pathological (blue) example cases: it can be noticed that in the normal sample the pixels corresponding to higher intensity are more numerous than in the pathological sample, due to the presence of thicker structures within physiological tissues.