Growing region technique in the detection of autonomous structures within X-ray radiographs

Raptis Sotiris, N; Tzafestas Spyros, G; Pavlopoulos, S; Koutsouris, D; Kollias, S

dc.contributor.author	Raptis Sotiris, N	en
dc.contributor.author	Tzafestas Spyros, G	en
dc.contributor.author	Pavlopoulos, S	en
dc.contributor.author	Koutsouris, D	en
dc.contributor.author	Kollias, S	en
dc.date.accessioned	2014-03-01T02:41:28Z
dc.date.available	2014-03-01T02:41:28Z
dc.date.issued	1997	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/30474
dc.subject	Cancer Prevention	en
dc.subject	Chest Radiograph	en
dc.subject	Chest X Ray	en
dc.subject	X Rays	en
dc.subject.other	Diagnostic radiography	en
dc.subject.other	Feature extraction	en
dc.subject.other	Image analysis	en
dc.subject.other	Image quality	en
dc.subject.other	Iterative methods	en
dc.subject.other	Object recognition	en
dc.subject.other	Oncology	en
dc.subject.other	Cancer nodule characteristics	en
dc.subject.other	Growing region techniques	en
dc.subject.other	X ray radiography	en
dc.title	Growing region technique in the detection of autonomous structures within X-ray radiographs	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/NSSMIC.1997.670619	en
heal.identifier.secondary	http://dx.doi.org/10.1109/NSSMIC.1997.670619	en
heal.publicationDate	1997	en
heal.abstract	Nodule identification is a major issue in chest radiography and cancer prevention and detection. The recognition of cancer nodule characteristics in chest radiographs is a key point to the detection procedure. The method described here is based on the extraction of the major geometrical as well as luminance characteristics that make nodule recognizable and easy to detect. The purpose of the proposed method is to detect within a given block of chest x-ray image any homogeneous and autonomous mass that might means the existence of a nodule or some structure within it. The idea of pixels of interest is introduced which makes the growing a finite steps procedure. The growing of the region around a given point is realized gradually in a finite number of iterations at each one of which a set of criteria is evaluated. These criteria are established in a prior training procedure.	en
heal.publisher	IEEE, Piscataway, NJ, United States	en
heal.journalName	IEEE Nuclear Science Symposium & Medical Imaging Conference	en
dc.identifier.doi	10.1109/NSSMIC.1997.670619	en
dc.identifier.volume	2	en
dc.identifier.spage	1576	en
dc.identifier.epage	1580	en