Computer image analysis of ultrasound images for discriminating and grading liver parenchyma disease employing a hierarchical decision tree scheme and the multiplayer perceptron neural network classifier

dc.contributor.author	Κάβουρας, Διονύσης Α.	el
dc.contributor.author	Κανδαράκης, Ιωάννης Σ.	el
dc.contributor.author	Θεοτοκάς, Ι.	el
dc.contributor.author	Κανελλόπουλος, Ε.	el
dc.contributor.author	Τριάντης, Δήμος Α.	el
dc.date.accessioned	2015-04-25T19:01:53Z
dc.date.issued	2015-04-25
dc.identifier.uri	http://hdl.handle.net/11400/8950
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://ebooks.iospress.nl/	en
dc.subject	liver cirrhosis
dc.subject	radiological problem
dc.subject	software
dc.subject	κύρωση του ήπατος
dc.subject	ακτινολογικό πρόβλημα
dc.subject	λογισμικό
dc.title	Computer image analysis of ultrasound images for discriminating and grading liver parenchyma disease employing a hierarchical decision tree scheme and the multiplayer perceptron neural network classifier	en
heal.type	conferenceItem
heal.classification	Science
heal.classification	Physics
heal.classification	Επιστήμες
heal.classification	Φυσική
heal.classificationURI	http://zbw.eu/stw/descriptor/15685-2
heal.classificationURI	http://zbw.eu/stw/descriptor/15669-0
heal.classificationURI	N/A-Επιστήμες
heal.classificationURI	N/A-Φυσική
heal.keywordURI	http://lod.nal.usda.gov/26370
heal.contributorName	Μπεχράκης, Ι.	el
heal.contributorName	Μάνεσης, Ε.Κ.	el
heal.contributorName	Βαφειάδη - Ζουμπούλη, Ειρήνη	el
heal.contributorName	Ζουμπούλης, Παύλος	el
heal.dateAvailable	10000-01-01
heal.language	en
heal.access	forever
heal.publicationDate	1997
heal.bibliographicCitation	Cavouras, D.A., Kandarakis, I.S., Theotokas, I., Kanellopoulos, E., Triantis, D.A., et al. (1997) Computer image analysis of ultrasound images for discriminating and grading liver parenchyma disease employing a hierarchical decision tree scheme and the multiplayer perceptron neural network classifier, In: Proceedings of the Medical Informatics Europe 97 (MIE 97). Halkidiki, Greece, 1997.[online]. p.522-526. Available from: http://ebooks.iospress.nl/	en
heal.abstract	Differential diagnosis of liver parenchyma disease and grading of the hepatic disease on ultrasound is a common radiological problem that influences patient management. The aim of this study was to apply image analysis methods on ultrasound images for discriminating liver cirrhosis from fatty liver infiltration and for grading hepatic disease, which is important in the management of the patients. Ultrasound images of histologically confirmed 18 livers with cirrhosis, 37 livers with fatty infiltration, and 24 normal livers of healthy volunteers were selected and were digitized for further computer processing. Twenty two textural features were calculated from small matrix samples selected from the ultrasound image matrix of the liver parenchyma. These features were used in the design a three level hierarchical decision tree classification scheme, employing the multilayer perceptron neural network classifier at each hierarchical tree level. At the first tree level, classification accuracy for distinguishing normal from abnormal livers was 93.7%, at the second level the accuracy for discriminating cirrhosis from fatty infiltration was 90.9%, and at the third level the accuracy in distinguishing between low and high grading liver cirrhosis or fatty infiltration was 94.1% and 84.9% respectively. The proposed computer software system may be of value to the radiologists in assessing liver parenchyma disease.	en
heal.publisher	IOS Press	en
heal.fullTextAvailability	false
heal.conferenceName	Medical Informatics Europe ’97 (MIE 97)	en
heal.conferenceItemType	abstract