Utilization of evidence theory in the detection of salient regions in successive CT images.

Athanasiadis, T; Wallace, M; Karpouzis, K; Kollias, S

dc.contributor.author	Athanasiadis, T	en
dc.contributor.author	Wallace, M	en
dc.contributor.author	Karpouzis, K	en
dc.contributor.author	Kollias, S	en
dc.date.accessioned	2014-03-01T01:25:28Z
dc.date.available	2014-03-01T01:25:28Z
dc.date.issued	2006	en
dc.identifier.issn	1021-335X	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/17673
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-33645779288&partnerID=40&md5=3c4df87e045aac0d551e7a3e08d10d8b	en
dc.subject	computed tomography images	en
dc.subject	salient regions	en
dc.subject	image segmentation	en
dc.subject	evidence theory	en
dc.subject	minimum uncertainty principle	en
dc.subject.classification	Oncology	en
dc.subject.other	algorithm	en
dc.subject.other	article	en
dc.subject.other	computer assisted tomography	en
dc.subject.other	human	en
dc.subject.other	image processing	en
dc.subject.other	liver tumor	en
dc.subject.other	radiography	en
dc.subject.other	Algorithms	en
dc.subject.other	Humans	en
dc.subject.other	Image Processing, Computer-Assisted	en
dc.subject.other	Liver Neoplasms	en
dc.subject.other	Tomography, X-Ray Computed	en
dc.title	Utilization of evidence theory in the detection of salient regions in successive CT images.	en
heal.type	journalArticle	en
heal.language	English	en
heal.publicationDate	2006	en
heal.abstract	This study presents an integrated approach to locating and presenting the medical practitioner with salient regions in a computed tomography (CT) scan when focusing on the area of the liver. A number of image processing tasks are performed in successive scans to extract areas with a different features than that of the greater part of the organ. In general, these areas do not always correspond to pathological patterns, but may be the result of noise in the scanned image or related to veins passing through the tissue. The result of the algorithm is the original image with a mask indicating these regions, so the attention of the medical practitioner is drawn to them for further examination. The algorithm also calculates a measure of confidence of the system, with respect to the extraction of the salient region, based on the fact that a region with a similar pattern is also located in successive scans. This essentially represents the hypothesis that the volume of both pathological patterns and blood vessels, but not noise patterns, is large enough to be captured in successive scans.	en
heal.publisher	PROFESSOR D A SPANDIDOS	en
heal.journalName	Oncology reports.	en
dc.identifier.isi	ISI:000236066000018	en
dc.identifier.volume	15 Spec no.	en
dc.identifier.spage	1071	en
dc.identifier.epage	1076	en