A Novel Approach for the Classification of Liver MR Images Using Complex Orthogonal Ripplet-II and Wavelet-Based Transforms

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dc.contributor.authorCanbilen, Ayse Elif
dc.contributor.authorCeylan, Murat
dc.date.accessioned2020-03-26T19:52:45Z
dc.date.available2020-03-26T19:52:45Z
dc.date.issued2018
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractThis study presents a decision support system aid to radiologists for defining focal lesions and making diagnosis more accurate by using liver magnetic resonance images. A new method called the complex orthogonal Ripplet-II transform is proposed as a feature extraction procedure. Artificial neural network is utilized to classify the obtained features as a hemangioma or cyst. The results are evaluated with the results of the systems using Ridgelet, Ripplet type-II and orthogonal Ripplet type-II transforms. The highest accuracy ratio (85.3%) and area under curve value (0.92) are achived by the complex orthogonal Ripplet-II transform. The accuracy of the classification procedure is increased up to 95.6% by a combined system that collectively analyzes the results obtained from the artificial neural network outputs of the two methods (Ridgelet and complex orthogonal Ripplet-II transforms). While this combined system is built up of three methods (adding Ripplet type-II), the accuracy rate reaches 97.06% and the area under curve value to 0.99.en_US
dc.identifier.doi10.1007/978-3-319-65981-7_2en_US
dc.identifier.endpage56en_US
dc.identifier.isbn978-3-319-65981-7; 978-3-319-65980-0
dc.identifier.issn2212-9391en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage33en_US
dc.identifier.urihttps://dx.doi.org/10.1007/978-3-319-65981-7_2
dc.identifier.urihttps://hdl.handle.net/20.500.12395/36274
dc.identifier.volume26en_US
dc.identifier.wosWOS:000460338400003en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSPRINGER INTERNATIONAL PUBLISHING AGen_US
dc.relation.ispartofCLASSIFICATION IN BIOAPPS: AUTOMATION OF DECISION MAKINGen_US
dc.relation.ispartofseriesLecture Notes in Computational Vision and Biomechanics
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectArtificial neural networken_US
dc.subjectBiomedical image classificationen_US
dc.subjectComplex orthogonal Ripplet-II transformen_US
dc.subjectComplex wavelet transformen_US
dc.subjectLiver MR imagingen_US
dc.subjectRipplet type-II transformen_US
dc.titleA Novel Approach for the Classification of Liver MR Images Using Complex Orthogonal Ripplet-II and Wavelet-Based Transformsen_US
dc.typeBook Chapteren_US

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