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dc.contributor.advisorHeidrich, Wolfgang
dc.contributor.authorLi, Muxingzi
dc.date.accessioned2017-04-24T08:17:28Z
dc.date.available2017-04-24T08:17:28Z
dc.date.issued2017-04-24
dc.identifier.doi10.25781/KAUST-B4Z34
dc.identifier.urihttp://hdl.handle.net/10754/623270
dc.description.abstractOptical Coherence Tomography (OCT) is a coherence-gated, micrometer-resolution imaging technique that focuses a broadband near-infrared laser beam to penetrate into optical scattering media, e.g. biological tissues. The OCT resolution is split into two parts, with the axial resolution defined by half the coherence length, and the depth-dependent lateral resolution determined by the beam geometry, which is well described by a Gaussian beam model. The depth dependence of lateral resolution directly results in the defocusing effect outside the confocal region and restricts current OCT probes to small numerical aperture (NA) at the expense of lateral resolution near the focus. Another limitation on OCT development is the presence of a mixture of speckles due to multiple scatterers within the coherence length, and other random noise. Motivated by the above two challenges, a multiple scattering model based on Rytov approximation and Gaussian beam optics is proposed for the OCT setup. Some previous papers have adopted the first Born approximation with the assumption of small perturbation of the incident field in inhomogeneous media. The Rytov method of the same order with smooth phase perturbation assumption benefits from a wider spatial range of validity. A deconvolution method for solving the inverse problem associated with the first Rytov approximation is developed, significantly reducing the defocusing effect through depth and therefore extending the feasible range of NA.
dc.language.isoen
dc.subjectOptical coherence tomography
dc.subjectscattering
dc.subjectDenoising
dc.subjectinverse scattering problem
dc.subjectrytov approximation
dc.titleMultiple Scattering Model for Optical Coherence Tomography with Rytov Approximation
dc.typeThesis
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
thesis.degree.grantorKing Abdullah University of Science and Technology
dc.contributor.committeememberSundaramoorthi, Ganesh
dc.contributor.committeememberLeiknes, TorOve
thesis.degree.disciplineApplied Mathematics and Computational Science
thesis.degree.nameMaster of Science
refterms.dateFOA2018-06-13T16:59:33Z


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