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dc.contributor.authorChahid, Abderrazak
dc.contributor.authorSerrai, Hacene
dc.contributor.authorAchten, Eric
dc.contributor.authorLaleg-Kirati, Taous-Meriem
dc.date.accessioned2018-11-28T14:27:07Z
dc.date.available2018-11-28T14:27:07Z
dc.date.issued2018-11-16
dc.identifier.citationChahid A, Serrai H, Achten E, Laleg-Kirati T-M (2018) A New ROI-Based performance evaluation method for image denoising using the Squared Eigenfunctions of the Schrödinger Operator. 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Available: http://dx.doi.org/10.1109/EMBC.2018.8513615.
dc.identifier.doi10.1109/EMBC.2018.8513615
dc.identifier.urihttp://hdl.handle.net/10754/630099
dc.description.abstractIn this paper a new Region Of Interest (ROI) characterization for image denoising performance evaluation is proposed. This technique consists of balancing the contrast between the dark and bright ROIs, in Magnetic Resonance (MR) images, to track the noise removal. It achieves an optimal compromise between removal of noise and preservation of image details. The ROI technique has been tested using synthetic MRI images from the BrainWeb database. Moreover, it has been applied to a recently developed denoising method called Semi-Classical Signal Analysis (SCSA). The SCSA decomposes the image into the squared eigenfunctions of the Schrödinger operator where a soft threshold h is used to remove the noise. The results obtained using real MRI data suggest that this method is suitable for real medical image processing evaluation where the noise-free image is not available.
dc.description.sponsorshipResearch reported in this publication was supported by King Abdullah University of Science and Technology.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttps://ieeexplore.ieee.org/document/8513615
dc.rightsArchived with thanks to 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
dc.subjectRegions Of Interest (ROI)
dc.subjectMRI
dc.subjectimage enhancement
dc.subjectSemi-Classical Signal Analysis
dc.subjectSchrödinger Operator
dc.titleA New ROI-Based performance evaluation method for image denoising using the Squared Eigenfunctions of the Schrödinger Operator
dc.typeConference Paper
dc.contributor.departmentComputational Bioscience Research Center (CBRC)
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.identifier.journal2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
dc.conference.name2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
dc.eprint.versionPost-print
dc.contributor.institutionUniversity of Western Ontario, Robarts Research Institute, London ON, Canada.
dc.contributor.institutionUniversity of Gent, Department of Radiology, Belgium.
kaust.personChahid, Abderrazak
kaust.personLaleg-Kirati, Taous-Meriem
dc.source.beginpage5579
dc.source.endpage5582
refterms.dateFOA2018-11-28T14:27:07Z
dc.date.published-online2018-11-16
dc.date.published-print2018-07


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