Detection and classification of suspicious areas in autofluorescence bronchoscopy

Bountris, P; Haritou, M; Passalidou, E; Apostolou, N; Koutsouris, D

dc.contributor.author	Bountris, P	en
dc.contributor.author	Haritou, M	en
dc.contributor.author	Passalidou, E	en
dc.contributor.author	Apostolou, N	en
dc.contributor.author	Koutsouris, D	en
dc.date.accessioned	2014-03-01T02:51:59Z
dc.date.available	2014-03-01T02:51:59Z
dc.date.issued	2009	en
dc.identifier.issn	16800737	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/35789
dc.subject	Autofluorescence bronchoscopy	en
dc.subject	Digital image processing	en
dc.subject	Lung cancer	en
dc.subject	Neural networks	en
dc.subject	Pattern classification	en
dc.subject.other	Auto fluorescences	en
dc.subject.other	Clinical trial	en
dc.subject.other	Detection and localization	en
dc.subject.other	Diagnostic value	en
dc.subject.other	Digital image processing	en
dc.subject.other	False positive	en
dc.subject.other	High rate	en
dc.subject.other	Lung cancer	en
dc.subject.other	Malignant lesion	en
dc.subject.other	Pattern classification	en
dc.subject.other	Biological organs	en
dc.subject.other	Biomechanics	en
dc.subject.other	Biomedical engineering	en
dc.subject.other	Biophysics	en
dc.subject.other	Image processing	en
dc.subject.other	Imaging systems	en
dc.subject.other	Intelligent computing	en
dc.subject.other	Medical imaging	en
dc.subject.other	Neural networks	en
dc.subject.other	Endoscopy	en
dc.title	Detection and classification of suspicious areas in autofluorescence bronchoscopy	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-3-642-03882-2-488	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-642-03882-2-488	en
heal.publicationDate	2009	en
heal.abstract	Autofluorescence bronchoscopy (AFB) has been utilized over the past decade, proving to be a powerful tool for the detection and localization of premalignant and malignant lesions of the airways. Autofluorescence bronchoscopy is, however, characterized by low specificity and a high rate of false positive findings (FPFs). The majority of FPFs are due to inflammations, as they often fluoresce at the same wavelengths with cancer. According to several clinical trials, the percentage of the FPFs is about 30%. In this paper we present an intelligent computing system for the classification of suspicious areas of the bronchial mucosa, in order to decrease the rate of FPFs, to increase the specificity and sensitivity of AFB and enhance the overall diagnostic value of the AFB method.	en
heal.journalName	IFMBE Proceedings	en
dc.identifier.doi	10.1007/978-3-642-03882-2-488	en
dc.identifier.volume	25	en
dc.identifier.issue	4	en
dc.identifier.spage	1842	en
dc.identifier.epage	1845	en