A fractal analysis of CT liver images for the discrimination of hepatic lesions

dc.contributor.author	Σαριγιάννη, Κ.	el
dc.contributor.author	Ασβεστάς, Παντελής Α.	el
dc.contributor.author	Ματσόπουλος, Γεώργιος Κ.	el
dc.contributor.author	Νικήτα, Κωνσταντίνα Σ.	el
dc.contributor.author	Νικήτα, Α.	el
dc.date.accessioned	2015-02-07T13:21:07Z
dc.date.available	2015-02-07T13:21:07Z
dc.date.issued	2015-02-07
dc.identifier.uri	http://hdl.handle.net/11400/5788
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://ieeexplore.ieee.org/	en
dc.subject	Brownian motion processes
dc.subject	Computerised tomography
dc.subject	Κίνηση Brown
dc.subject	Αξονική τομογραφία
dc.title	A fractal analysis of CT liver images for the discrimination of hepatic lesions	en
heal.type	conferenceItem
heal.secondaryTitle	a comparative study	en
heal.generalDescription	Proccedings of the 23rd Annual International Conference of the Engineering in Medicine and Biology Society	en
heal.classification	Medicine
heal.classification	Biomedical engineering
heal.classification	Ιατρική
heal.classification	Βιοϊατρική τεχνολογία
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh00006614
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85014237
heal.classificationURI	N/A-Ιατρική
heal.classificationURI	N/A-Βιοϊατρική τεχνολογία
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh85017265
heal.contributorName	Κελέκης, Δ.	el
heal.identifier.secondary	DOI: 10.1109/IEMBS.2001.1020508
heal.language	en
heal.access	campus
heal.recordProvider	Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε.	el
heal.publicationDate	2001
heal.bibliographicCitation	Sariyianni, C., Asvestas, P., Matsopoulos, G., Nikita, K., Nikita, A., et al. (2001). A fractal analysis of CT liver images for the discrimination of hepatic lesions: a comparative study. In the In the 23rd Annual International Conference of the Engineering in Medicine and Biology Society. Istanbul, 25th-28th October 2001. vol. 2. pp. 1557-1560. IEEE. Available from: http://ieeexplore.ieee.org/	en
heal.abstract	A quantitative study for the discrimination of different hepatic lesions is presented in this paper. The study is based on the fractal analysis of CT liver images in order to estimate their fractal dimension and to differentiate normal liver parenchyma from hepatocellular carcinoma. Four fractal dimension estimators have been implemented throughout this work; three well-established methods and a novel implementation of a method. Analytically, these methods correspond to the power spectrum method, the box counting method, the morphological fractal estimator and the novel modification of the kth-nearest neighbour method. The Fuzzy C-Means algorithm is finally applied revealing that the k-th nearest neighbour method outperforms the other methods; thus discriminating up to 93% of the normal parenchyma and up to 82% of the hepatocellular carcinoma, correctly.	en
heal.publisher	IEEE	en
heal.fullTextAvailability	true
heal.conferenceName	Annual International Conference of the Engineering in Medicine and Biology Society	en
heal.conferenceItemType	full paper