Εμφάνιση απλής εγγραφής

dc.creatorGoudas, T.en
dc.creatorMaglogiannis, I.en
dc.date.accessioned2015-11-23T10:28:43Z
dc.date.available2015-11-23T10:28:43Z
dc.date.issued2012
dc.identifier10.1109/EMBC.2012.6346946
dc.identifier.isbn9781424441198
dc.identifier.issn1557170X
dc.identifier.urihttp://hdl.handle.net/11615/28079
dc.description.abstractThis paper presents an advanced image analysis tool for the accurate and fast characterization and quantification of cancer and apoptotic cells in microscopy images utilizing adaptive thresholding and a Support Vector Machines classifier. The segmentation results are also enhanced through a Majority Voting and a Watershed technique. The proposed tool was evaluated by experts on breast cancer images and the reported results were accurate and reproducible. © 2012 IEEE.en
dc.source.urihttp://www.scopus.com/inward/record.url?eid=2-s2.0-84870800082&partnerID=40&md5=e8338a3edc4ce1a06f6c63911b8ea66f
dc.subjectAdaptive thresholdingen
dc.subjectApoptotic cellsen
dc.subjectBreast Canceren
dc.subjectCancer cellsen
dc.subjectImage analysis techniquesen
dc.subjectImage analysis toolsen
dc.subjectMajority votingen
dc.subjectMicroscopy imagesen
dc.subjectSegmentation resultsen
dc.subjectImage analysisen
dc.subjectImage segmentationen
dc.subjectMedical imagingen
dc.subjectDiseasesen
dc.titleCancer cells detection and pathology quantification utilizing image analysis techniquesen
dc.typeconferenceItemen


Αρχεία σε αυτό το τεκμήριο

ΑρχείαΜέγεθοςΤύποςΠροβολή

Δεν υπάρχουν αρχεία που να σχετίζονται με αυτό το τεκμήριο.

Αυτό το τεκμήριο εμφανίζεται στις ακόλουθες συλλογές

Εμφάνιση απλής εγγραφής