| dc.rights.license | CC-BY-NC-ND | |
| dc.contributor.advisor | van Leeuwen, Tristan | |
| dc.contributor.author | Liu, H. | |
| dc.date.accessioned | 2018-10-16T17:00:37Z | |
| dc.date.available | 2018-10-16T17:00:37Z | |
| dc.date.issued | 2018 | |
| dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/38999 | |
| dc.description.abstract | In this thesis, reconstruction algorithms for spectral computed tomography are studied and tested. A reconstruction algorithm for inverse problem usually consists of: (1) formulating an optimization problem that includes a data fidelity term and a regularization term; (2) applying a proper numerical method to solve the optimization problem. The first part of the thesis works on single-energy reconstructions, with a focus on effects of regularization terms and acceleration techniques. When turning to the spectral CT, a general reconstruction framework is formulated, and a two-step algorithm is then developed and tested. Numerical experiments have shown that the two-step algorithm can reconstruct the material-specific images from spectral data, and that the two-step reconstruction can be computed efficiently after applying proper numerical methods. | |
| dc.description.sponsorship | Utrecht University | |
| dc.format.extent | 2281897 | |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en | |
| dc.title | Reconstruction Algorithms for Spectral Computed Tomography | |
| dc.type.content | Master Thesis | |
| dc.rights.accessrights | Open Access | |
| dc.subject.keywords | inverse problem; computed tomography; numerical optimization; regularization; | |
| dc.subject.courseuu | Mathematical Sciences | |
