FISH is a direct and relatively rapid and sensitive in situ technique. No cell culture is needed in order to apply this method and results are easier to interpret than kariotype.

However, the manual evaluation of FISH image is a time consuming process prone to error involving manual counting of FISH signals over a tissue slide. Although many studies have focused on automated evaluation of FISH images, this approach remains challenging. The intensity of positive signals may be different in different experiments, even for the same sample. The differences in intensity are due to a number of factors such as the hybridization conditions and the image acquisition parameters. Many types of samples have additional complications due to the presence of cell aggregates and non uniform background fluorescence.

Therefore the FISH analysis is currently performed in a semi-automated way. The counting of dots in a semi-automated manner still remains impractical for a pathologist since it requires substantial user intervention. The Aristotle University of Thessaloniki has developed a novel automated system which aims to address these issues. The system was tested in two parallel evaluation studies at two different institutions, the University of Pisa and the Aristotle University of Thessaloniki.

The study shows that developed FISH image analysis software can impove evaluation of HER2 status in breast cancer cases.