title: Automated analysis of FISH and immunohistochemistry images: a review.
abstract: Fluorescent in-situ hybridization (FISH) and immunohistochemistry (IHC) constitute a pair of complimentary techniques for detecting gene amplification and overexpression, respectively. The advantages of IHC include relatively cheap materials and high sample durability, while FISH is the more accurate and reproducible method. Evaluation of FISH and IHC images is still largely performed manually, with automated or semiautomated techniques increasing in popularity. Here, we provide a comprehensive review of a number of (semi-) automated FISH and IHC image processing systems, focusing on the algorithmic aspects of each technique. Our review verifies the increasingly important role of such methods in FISH and IHC; however, manual intervention is still necessary in order to resolve particularly challenging or ambiguous cases. In addition, large-scale validation is required in order for these systems to enter standard clinical practice.
authors.affiliation: Department of Informatics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.
authors.forename: Zenonas
authors.initials: Z
authors.lastname: Theodosiou
authors.forename: Ioannis N
authors.initials: IN
authors.lastname: Kasampalidis
authors.forename: George
authors.initials: G
authors.lastname: Livanos
authors.forename: Michalis
authors.initials: M
authors.lastname: Zervakis
authors.forename: Ioannis
authors.initials: I
authors.lastname: Pitas
authors.forename: Kleoniki
authors.initials: K
authors.lastname: Lyroudia
mesh_terms: D000465:Algorithms; D000818:Animals; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007150:Immunohistochemistry; D017404:In Situ Hybridization, Fluorescence; D008962:Models, Theoretical