Automatic detection of meniscal area in the knee MR images

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dc.authorid0000-0001-7947-5508
dc.authorid0000-0002-1786-6869
dc.authorid0000-0001-8625-4842
dc.authorwosidKAYA, Heysem/V-4493-2019
dc.authorwosidVarlı, Songül/AAZ-4672-2020
dc.authorwosidSAYGILI, AHMET/AAG-4161-2019
dc.contributor.authorSaygılı, Ahmet
dc.contributor.authorKaya, Heysem
dc.contributor.authorAlbayrak, Songül
dc.date.accessioned2022-05-11T14:15:48Z
dc.date.available2022-05-11T14:15:48Z
dc.date.issued2016
dc.departmentFakülteler, Çorlu Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description24th Signal Processing and Communication Application Conference (SIU) -- MAY 16-19, 2016 -- Zonguldak, TURKEY
dc.description.abstractNowadays computer-aided medical systems has become widespread. These systems assist the scientists in the medical field with diagnosis and treatment. In the same vein, in this study detection of medial meniscus from MR images of the knee is performed automatically. Knee MR images used in this study were obtained from Osteoarthritis initiative. 75% of MR images were used for training, while the remainder was used for the test. Attributes to be used in the training and test process were obtained by the Histogram of Oriented Gradients (HOG) method. The regression approach used in the training process and found correlation and mean square error value for patch in different sizes. The maximum correlation value detected is about 91%. The objective of the study will be to accelerate the current system for minimizing the time for treatment in the later stages and to provide a functional decision support system.
dc.description.sponsorshipIEEE, Bulent Ecevit Univ, Dept Elect & Elect Engn, Bulent Ecevit Univ, Dept Biomed Engn, Bulent Ecevit Univ, Dept Comp Engn
dc.identifier.endpage1340
dc.identifier.isbn978-1-5090-1679-2
dc.identifier.scopus2-s2.0-84982843961
dc.identifier.startpage1337
dc.identifier.urihttps://hdl.handle.net/20.500.11776/6078
dc.identifier.wosWOS:000391250900311
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorSaygılı, Ahmet
dc.institutionauthorKaya, Heysem
dc.language.isotr
dc.publisherIEEE
dc.relation.ispartof2016 24th Signal Processing and Communication Application Conference (Siu)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectKnee MR
dc.subjectHOG
dc.subjectmedical image processing
dc.subjectSegmentation
dc.subjectTears
dc.titleAutomatic detection of meniscal area in the knee MR images
dc.typeConference Object

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