|
Title
|
|
|
|
Newton-Krylov methods for polychromatic X-Ray CT
| |
|
Author
|
|
|
|
| |
|
Abstract
|
|
|
|
| Most lab-based X-ray sources are polychromatic, making the acquisition follow a non-linear model. However, widespread reconstruction algorithms, such as FBP and SIRT, assume the reconstruction to be a linear problem, leading to artefacts in the reconstructions. We propose a non-linear optimization technique, Newton-Krylov, to minimize a polychromatic objective function instead. The objective function can also easily be extended with regularisation terms, in a mathematically sound framework. Results on Monte-Carlo simulated projection data show a lower error in the data fidelity term, as well as improved reconstruction quality. |
| |
|
Language
|
|
|
|
English
| |
|
Source (journal)
|
|
|
|
Proceedings. - Los Alamitos, Calif, 1994, currens
| |
|
Source (book)
|
|
|
|
2020 IEEE International Conference on Image Processing (ICIP), 25-28 October, 2020, Abu Dhabi, United Arab Emirates
| |
|
Publication
|
|
|
|
Los Alamitos, Calif
:
IEEE
,
2020
| |
|
ISSN
|
|
|
|
1522-4880
| |
|
ISBN
|
|
|
|
978-1-7281-6395-6
| |
|
DOI
|
|
|
|
10.1109/ICIP40778.2020.9190717
| |
|
Volume/pages
|
|
|
|
p. 3045-3049
| |
|
ISI
|
|
|
|
000646178503031
| |
|
Full text (Publisher's DOI)
|
|
|
|
| |
|