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dc.contributor.advisorWonka, Peter
dc.contributor.authorZang, Guangming
dc.date.accessioned2016-04-14T07:13:26Z
dc.date.available2016-04-14T07:13:26Z
dc.date.issued2016-04-14
dc.identifier.doi10.25781/KAUST-TH10I
dc.identifier.urihttp://hdl.handle.net/10754/605208
dc.description.abstractIn this thesis, we present ProxiSART, a flexible proximal framework for robust 3D cone beam tomographic reconstruction based on the Simultaneous Algebraic Reconstruction Technique (SART). We derive the proximal operator for the SART algorithm and use it for minimizing the data term in a proximal algorithm. We show the flexibility of the framework by plugging in different powerful regularizers, and show its robustness in achieving better reconstruction results in the presence of noise and using fewer projections. We compare our framework to state-of-the-art methods and existing popular software tomography reconstruction packages, on both synthetic and real datasets, and show superior reconstruction quality, especially from noisy data and a small number of projections.
dc.language.isoen
dc.subjectX-Ray imaging
dc.subjectcomputed tomography
dc.subject3D volume
dc.subjectvolume reconstruction
dc.subjectoptimization
dc.subjectSART
dc.titleIndustrial Computed Tomography using Proximal Algorithm
dc.typeThesis
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentComputer Science
thesis.degree.grantorKing Abdullah University of Science and Technology
dc.contributor.committeememberHeidrich, Wolfgang
dc.contributor.committeememberSundaramoorthi, Ganesh
thesis.degree.disciplineComputer Science
thesis.degree.nameMaster of Science
refterms.dateFOA2017-04-14T00:00:00Z


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