作者: Paolo Aretini , Generoso Bevilacqua
DOI:
关键词: Image acquisition 、 Image analysis 、 Fish <Actinopterygii> 、 Clinical Oncology 、 Biomedical engineering 、 Machine learning 、 Engineering 、 Informatics 、 Sample (material) 、 Image evaluation 、 Artificial intelligence 、 Process (engineering)
摘要: FISH is a direct and relatively rapid sensitive in situ technique. No cell culture needed order to apply this method results are easier interpret than kariotype. However, the manual evaluation of image time consuming process prone error involving counting signals over tissue slide. Although many studies have focused on automated images, approach remains challenging. The intensity positive may be different experiments, even for same sample. differences due number factors such as hybridization conditions acquisition parameters. Many types samples additional complications presence aggregates non uniform background fluorescence. Therefore analysis currently performed semi-automated way. dots manner still impractical pathologist since it requires substantial user intervention. Aristotle University Thessaloniki has developed novel system which aims address these issues. was tested two parallel at institutions, Pisa Thessaloniki. The study shows that software can impove HER2 status breast cancer cases.