Type
ThesisAuthors
Zang, Guangming
Advisors
Wonka, Peter
Committee members
Heidrich, Wolfgang
Sundaramoorthi, Ganesh

Program
Computer ScienceDate
2016-04-14Embargo End Date
2017-04-14Permanent link to this record
http://hdl.handle.net/10754/605208
Metadata
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At the time of archiving, the student author of this thesis opted to temporarily restrict access to it. The full text of this thesis became available to the public after the expiration of the embargo on 2017-04-14.Abstract
In 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.Citation
Zang, G. (2016). Industrial Computed Tomography using Proximal Algorithm. KAUST Research Repository. https://doi.org/10.25781/KAUST-TH10Iae974a485f413a2113503eed53cd6c53
10.25781/KAUST-TH10I