Automated image reconstruction for non-cartesian magnetic particle imaging

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buir.advisorÇukur, Emine Ülkü Sarıtaş
dc.contributor.authorÖzaslan, Ali Alper
dc.date.accessioned2019-09-18T08:57:58Z
dc.date.available2019-09-18T08:57:58Z
dc.date.copyright2019-09
dc.date.issued2019-09
dc.date.submitted2019-09-17
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (M.S.): Bilkent University, Department of Electrical and Electronics Engineering, İhsan Doğramacı Bilkent University, 2019.en_US
dc.descriptionIncludes bibliographical references (leaves 45-52).en_US
dc.description.abstractMagnetic particle imaging (MPI) is a high-contrast imaging modality that images the spatial distribution of superparamagnetic iron oxide (SPIO) nanoparticles by exploiting their nonlinear response. In MPI, image reconstruction is performed via two di erent methods: system function reconstruction (SFR) and x-space reconstruction. For the SFR approach, analysis of various scanning trajectories provided important insight about their image quality performances. While Cartesian trajectories remain the most popular choice for x-space-based reconstruction, recent work suggests that non-Cartesian trajectories such as the Lissajous trajectory may prove bene cial for improving image quality. In this thesis, a generalized reconstruction scheme is proposed for x-space MPI that can be used in conjunction with any scanning trajectory. The proposed technique automatically tunes the reconstruction parameters from the scanning trajectory, and does not induce any additional blurring. To demonstrate the proposed technique, ve di erent trajectories were utilized with varying density levels. Comparison to alternative reconstruction methods show signi cant improvement in image quality achieved by the proposed technique. Among the tested trajectories, the Lissajous and bidirectional Cartesian trajectories prove more favorable for x-space MPI, and the resolution of the images from these two trajectories can further be improved via deblurring. The fully automated gridding reconstruction proposed in this thesis can be utilized with these trajectories to improve the image quality in x-space MPI.en_US
dc.description.degreeM.S.en_US
dc.description.statementofresponsibilityby Ali Alper Özaslanen_US
dc.format.extentxv, 54 leaves : illustrations (some color), charts ; 30 cm.en_US
dc.identifier.itemidB122329
dc.identifier.urihttp://hdl.handle.net/11693/52450
dc.language.isoEnglishen_US
dc.publisherBilkent Universityen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectMagnetic particle imagingen_US
dc.subjectImage reconstructionen_US
dc.subjectGridding reconstructionen_US
dc.subjectNon-Cartesian trajectoriesen_US
dc.titleAutomated image reconstruction for non-cartesian magnetic particle imagingen_US
dc.title.alternativeKartezyen olmayan manyetik parçacık görüntüleme için otomatik görüntü geriçatımıen_US
dc.typeThesisen_US
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