A decision support system for the automatic assessment of hip osteoarthritis severity by hip joint space contour spectral analysis

Boniatis, I; Cavouras, D; Costaridou, L; Kalatzis, I; Panagiotopoulos, E; Panayiotakis, G

dc.contributor.author	Boniatis, I	en
dc.contributor.author	Cavouras, D	en
dc.contributor.author	Costaridou, L	en
dc.contributor.author	Kalatzis, I	en
dc.contributor.author	Panagiotopoulos, E	en
dc.contributor.author	Panayiotakis, G	en
dc.date.accessioned	2014-03-01T02:50:17Z
dc.date.available	2014-03-01T02:50:17Z
dc.date.issued	2006	en
dc.identifier.issn	03029743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/35034
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-34547415639&partnerID=40&md5=8bb513cc94f549b37ca8f99262077889	en
dc.subject.other	Decision support systems	en
dc.subject.other	Decision trees	en
dc.subject.other	Fourier analysis	en
dc.subject.other	Patient monitoring	en
dc.subject.other	Radiography	en
dc.subject.other	Spectrum analysis	en
dc.subject.other	Hip osteoarthritis	en
dc.subject.other	Kellgren and Lawrence scale	en
dc.subject.other	Space contour spectral analysis	en
dc.subject.other	Hip prostheses	en
dc.title	A decision support system for the automatic assessment of hip osteoarthritis severity by hip joint space contour spectral analysis	en
heal.type	conferenceItem	en
heal.publicationDate	2006	en
heal.abstract	A decision support system was developed for the grading of hip osteoarthritis (OA) severity. Sixty four hips (18 normal, 46 osteoarthritic) were studied from the digitized radiographs of 32 patients with unilateral or bilateral hip-OA. Hips were allocated into three OA-severity categories, formed accordingly to the Kellgren and Lawrence scale: ""Normal"", ""Mild-Moderate"", and ""Severe"". Employing custom developed algorithms: (i) the radiographic contrast was enhanced, (ii) 64 ROIs, corresponding to patients' radiographic Hip Joint Spaces (HJSs), were determined, and (iii) Fourier descriptors of the HJS-ROIs boundary were generated. These descriptors were used in the design of a two-level hierarchical decision tree structure, employed for the discrimination of the OA-severity categories. The overall classification accuracies accomplished by the system, regarding the discrimination between: (i) Normal and osteoarthritic hips, and (ii) hips of ""Mild-Moderate"" OA and of ""Severe"" OA were 92.2% and 86.0%, respectively. The proposed system may contribute to osteoarthritic patients management. © Springer-Verlag Berlin Heidelberg 2006.	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
dc.identifier.volume	4345 LNBI	en
dc.identifier.spage	451	en
dc.identifier.epage	462	en