A comparison of feature extraction techniques for diagnosis of lumbar intervertebral degenerative disc disease

dc.contributor.authorÜnal, Yavuz
dc.contributor.authorKoçer, Hasan Erdinç
dc.contributor.authorAkkurt, Halil Ekrem
dc.date.accessioned2020-03-26T18:22:07Z
dc.date.available2020-03-26T18:22:07Z
dc.date.issued2011
dc.departmentSelçuk Üniversitesien_US
dc.descriptionTUBITAK;IEEEen_US
dc.description2011 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2011 -- 15 June 2011 through 18 June 2011 -- Istanbul-Kadikoy -- 85879en_US
dc.description.abstractThe reduction of fluid that acts as shock absorber placed in lumbar intervertebral discs causes pains and this case is named as degenerative disc disease. Magentic Resonance Imaging is generally used for diagnosis of this disease by radiologists or doctors. However, due to personal errors such as fatigue, inexperience, oversight, wrong diagnosis is possible. In order to prevent these, computer-aided diagnostic (CAD) methods are mostly preferred. In this work, the performance of two different feature extraction methods is compared. The saggital MR images taken from 9 patients were feature extracted by using grey level co-occurrence matrix (GLCM) and average absolute deviation (AAD) methods. The obtained feature vectors were classified by using multi-layered perceptron (MLP) artificial neural networks. © 2011 IEEE.en_US
dc.identifier.doi10.1109/INISTA.2011.5946147en_US
dc.identifier.endpage494en_US
dc.identifier.isbn9.78161E+12
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage490en_US
dc.identifier.urihttps://dx.doi.org/10.1109/INISTA.2011.5946147
dc.identifier.urihttps://hdl.handle.net/20.500.12395/27155
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.relation.ispartofINISTA 2011 - 2011 International Symposium on INnovations in Intelligent SysTems and Applicationsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectartificial neural networksen_US
dc.subjectaverage absolute deviationen_US
dc.subjectgrey level co-occurrence matrixen_US
dc.subjectintervertebral degenerative disk diseaseen_US
dc.titleA comparison of feature extraction techniques for diagnosis of lumbar intervertebral degenerative disc diseaseen_US
dc.typeConference Objecten_US

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