HisTOOLogy is an open-source software for the quantification of digital colour images of histological sections. The simple graphical user interface enables both expert and non-expert users to rapidly extract useful information from stained tissue sections. The software's main feature is a generalizable colour separation algorithm based on k-means clustering which accurately and reproducibly returns the amount of colour per unit area for any stain, thus allowing the quantification of tissue components. Here we describe HisTOOLogy's algorithms and graphical user interface structure, showing how it can be used to separate different dye colours in several classical stains. In addition, to demonstrate how the tool can be employed to obtain quantitative information on biological tissues, the effect of different hepatic tissue decellularization protocols on cell removal and matrix preservation was assessed through image analysis using HisTOOLogy and compared with conventional DNA and total protein content assays. HisTOOLogy's performance was also compared with ImageJ's colour deconvolution plug-in, demonstrating its advantages in terms of ease of use and speed of colour separation.
Keywords: Colour image processing; histochemical staining; image analysis.
© 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.