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dc.contributor.authorGhassemi, A.
dc.contributor.authorKazemi, K.
dc.contributor.authorSefidbakht, S.
dc.contributor.authorDanyali, H.
dc.date.accessioned2020-05-04T09:39:04Z
dc.date.available2020-05-04T09:39:04Z
dc.date.issued2020-04cs
dc.identifier.citationRadioengineering. 2020 vol. 29, č. 1, s. 251-258. ISSN 1210-2512cs
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/186956
dc.description.abstractIntra-voxel incoherent motion (IVIM) imaging can characterize diffusion and perfusion of tissues. Traditionally, the least-square method has been used to determine IVIM parameters consisting of pure diffusion coefficient (D), pseudo-diffusion coefficient (D*) and the micro-vascular volume fraction (f). This paper proposes an accurate estimation method for IVIM parameters in human brain tissues using θ-teaching-learning-based-optimization (θ-TLBO). θ-TLBO as an evolutionary algorithm provides high quality solutions for parameter estimations in curve fitting problems. Evaluation of the proposed method was performed on simulated data with different levels of noise and experimental data. The estimated parameters were compared with the results of TLBO and three conventional algorithms: Segmented-Unconstrained (“SU”), Segmented-Constrained (“SC”) and “Full”. The results show that the proposed θ-TLBO has higher accuracy, precision and robustness than other methods in estimating parameters of simulated and experimental data in human brain images especially in low SNR images according to analysis of variance (ANOVA), coefficient of variation (CV), relative bias and relative root mean square errors.en
dc.formattextcs
dc.format.extent251-258cs
dc.format.mimetypeapplication/pdfen
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttps://www.radioeng.cz/fulltexts/2019/20_01_0251_0258.pdfcs
dc.rightsCreative Commons Attribution 4.0 International licenseen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectHuman brainen
dc.subjectIntra-Voxel Incoherent Motion (IVIM)en
dc.subjectdiffusionen
dc.subjectperfusionen
dc.subjectθ-Teaching-Learning-Based Optimization (θ-TLBO).en
dc.titleReliable Estimation of the Intra-Voxel Incoherent Motion Parameters of Brain Diffusion Imaging Using θ-Teaching-Learning-Based Optimizationen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
dc.coverage.issue1cs
dc.coverage.volume29cs
dc.identifier.doi10.13164/re.2020.0251en
dc.rights.accessopenAccessen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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Except where otherwise noted, this item's license is described as Creative Commons Attribution 4.0 International license