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dc.contributor.authorKaya, Mert
dc.contributor.authorBebek, Özkan
dc.date.accessioned2016-02-17T11:05:43Z
dc.date.available2016-02-17T11:05:43Z
dc.date.issued2014
dc.identifier.issn1558-2809
dc.identifier.urihttp://hdl.handle.net/10679/2853
dc.identifier.urihttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=6958456
dc.descriptionDue to copyright restrictions, the access to the full text of this article is only available via subscription.
dc.description.abstractThis paper presents an entropy based parameter tuning method for needle segmentation, and a probability map based needle tip estimation method using Gabor-based line filter. The proposed automatic parameter tuning method optimizes the threshold value that is used by the Otsu's thresholding technique to binarize the ultrasound image. A probability map is created to estimate the needle tip location using the Gabor filtered image and the binarized image. The pixel with the maximum probability represents the needle tip location. Finally, an enhancement method to improve needle visibility is proposed. The proposed methods are experimentally tested in four different phantoms and distilled water. The image processing time is reduced by 24% using the proposed tuning method, and the needle tip location can be successfully estimated using the probability map.
dc.description.sponsorshipTÜBİTAK
dc.language.isoengen_US
dc.publisherIEEE
dc.relationinfo:turkey/grantAgreement/TUBITAK/112E312
dc.relation.ispartof2014 IEEE International Conference on Imaging Systems and Techniques (IST) Proceedings
dc.rightsrestrictedAccess
dc.titleGabor filter based localization of needles in ultrasound guided robotic interventionsen_US
dc.typeConference paperen_US
dc.peerreviewedyes
dc.publicationstatuspublisheden_US
dc.contributor.departmentÖzyeğin University
dc.contributor.authorID(ORCID 0000-0003-2721-9777 & YÖK ID 43734) Bebek, Özkan
dc.contributor.ozuauthorBebek, Özkan
dc.identifier.startpage112
dc.identifier.endpage117
dc.identifier.doi10.1109/IST.2014.6958456
dc.subject.keywordsGabor filters
dc.subject.keywordsControl engineering computing
dc.subject.keywordsEntropy
dc.subject.keywordsImage enhancement
dc.subject.keywordsImage segmentation
dc.subject.keywordsMedical image processing
dc.subject.keywordsMedical robotics
dc.subject.keywordsProbability
dc.subject.keywordsRobot vision
dc.subject.keywordsUltrasonic imaging
dc.identifier.scopusSCOPUS:2-s2.0-84916633757
dc.contributor.ozugradstudentKaya, Mert
dc.contributor.authorMale2


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