Εμφάνιση απλής εγγραφής

dc.creatorTasoulis, S. K.en
dc.creatorDoukas, C. N.en
dc.creatorMaglogiannis, I.en
dc.creatorPlagianakos, V. P.en
dc.date.accessioned2015-11-23T10:49:32Z
dc.date.available2015-11-23T10:49:32Z
dc.date.issued2010
dc.identifier10.1109/IEMBS.2010.5626777
dc.identifier.isbn9781424441235
dc.identifier.urihttp://hdl.handle.net/11615/33570
dc.description.abstractProgrammed cell death, also known as apoptosis is of fundamental importance in many biological processes and also highly associated with serious diseases like cancer and HIV. The current paper presents an innovative method for apoptosis phenomenon characterization based on apoptotic cell quantification and detection using active contours. Subsequently, we employ appropriate data mining techniques and perform characterization of apoptosis on digital microscopic images. A particular class of clustering algorithms, utilizing information driven by the Principal Component Analysis, has been very successful in dealing with such data. In this work, we employ a recently proposed clustering algorithm to solve this real world clustering task. © 2010 IEEE.en
dc.source.urihttp://www.scopus.com/inward/record.url?eid=2-s2.0-78650803132&partnerID=40&md5=61726a89380271ac6fc1fee515c70a31
dc.subjectActive contoursen
dc.subjectApoptosisen
dc.subjectApoptotic cellsen
dc.subjectBiological processen
dc.subjectClustering techniquesen
dc.subjectData mining techniquesen
dc.subjectDigital microscopic imagesen
dc.subjectInnovative methoden
dc.subjectProgrammed cell deathsen
dc.subjectCell deathen
dc.subjectCluster analysisen
dc.subjectData miningen
dc.subjectPrincipal component analysisen
dc.subjectClustering algorithmsen
dc.titleClassification of apoptosis using advanced clustering techniques on digital microscopic imagesen
dc.typeconferenceItemen


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