Automated analysis of FISH and immunohistochemistry images

dc.contributor.author	Θεοδοσίου, Ζήνωνας	el
dc.contributor.author	Κασαμπαλίδης, Ιωάννης Ν.	el
dc.contributor.author	Λιβανός, Γεώργιος Α.	el
dc.contributor.author	Ζερβάκης, Μιχάλης Ε.	el
dc.contributor.author	Πήτας, Ιωάννης Κ.	el
dc.date.accessioned	2015-06-04T18:09:12Z
dc.date.available	2015-06-04T18:09:12Z
dc.date.issued	2015-06-04
dc.identifier.uri	http://hdl.handle.net/11400/15112
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://www.scopus.com/record/display.url?origin=recordpage&eid=2-s2.0-34447125022&citeCnt=0&noHighlight=false&sort=plf-f&src=s&sid=638613000D25AD0C226F3925E157AFD1.WeLimyRvBMk2ky9SFKc8Q%3a1550&sot=autdocs&sdt=autdocs&sl=18&s=AU-ID%2816833442400%29&relpos=19	en
dc.subject	ακρίβεια
dc.subject	αλγόριθμος
dc.subject	αυτοανάλυση
dc.subject	πυρήνας κυττάρου
dc.subject	συσκευή
dc.subject	accuracy
dc.subject	algorithm
dc.subject	autoanalysis
dc.subject	cell nucleus
dc.subject	device
dc.title	Automated analysis of FISH and immunohistochemistry images	en
heal.type	journalArticle
heal.secondaryTitle	a review	en
heal.classification	Πληροφορική
heal.classification	Μηχανική υπολογιστών
heal.classification	Computer science
heal.classification	Computer engineering
heal.classificationURI	N/A-Πληροφορική
heal.classificationURI	N/A-Μηχανική υπολογιστών
heal.classificationURI	http://skos.um.es/unescothes/C00750
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85029495
heal.keywordURI	http://lod.nal.usda.gov/2177
heal.keywordURI	http://lod.nal.usda.gov/23416
heal.contributorName	Λυρούδια, Κλεονίκη	el
heal.identifier.secondary	DOI: 10.1002/cyto.a.20409
heal.language	en
heal.access	campus
heal.recordProvider	Τεχνολογικό Εκπαιδευτικό Ίδρυμα Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Ναυπηγών Μηχανικών Τ.Ε.	el
heal.publicationDate	2007-07
heal.bibliographicCitation	Theodosiou, Z., Kasampalidis, I.N., Livanos, G., Zervakis, M., Pitas, I. et al (2007) Automated analysis of FISH and immunohistochemistry images: A review. Cytometry Part A. [Online] 71 (7), pp.439-450. Available from: http://www.scopus.com [Accessed 04/06/2015]	en
heal.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.	en
heal.journalName	Cytometry Part A	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true