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Split-Bregman-based sparse-view CT reconstruction

Bert Vandeghinste UGent, Bart Goossens UGent, Jan De Beenhouwer UGent, Aleksandra Pizurica UGent, Wilfried Philips UGent, Stefaan Vandenberghe UGent and Steven Staelens UGent (2011) Fully 3D 2011 proceedings. p.431-434
abstract
Total variation minimization has been extensively researched for image denoising and sparse view reconstruction. These methods show superior denoising performance for simple images with little texture, but result in texture information loss when applied to more complex images. It could thus be beneficial to use other regularizers within medical imaging. We propose a general regularization method, based on a split-Bregman approach. We show results for this framework combined with a total variation denoising operator, in comparison to ASD-POCS. We show that sparse-view reconstruction and noise regularization is possible. This general method will allow us to investigate other regularizers in the context of regularized CT reconstruction, and decrease the acquisition times in µCT.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
keyword
Noise, Computed Tomography, Reconstruction Algorithms, Iterative Algorithms
in
Fully 3D 2011 proceedings
pages
431 - 434
conference name
11th International meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully 3D 11)
conference location
Potsdam, Germany
conference start
2011-07-11
conference end
2011-07-15
language
English
UGent publication?
yes
classification
C1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1957394
handle
http://hdl.handle.net/1854/LU-1957394
date created
2011-12-01 12:34:10
date last changed
2012-10-05 15:45:26
@inproceedings{1957394,
  abstract     = {Total variation minimization has been extensively researched for image denoising and sparse view reconstruction. These methods show superior denoising performance for simple images with little texture, but result in texture information loss when applied to more complex images. It could thus be beneficial to use other regularizers within medical imaging. We propose a general regularization method, based on a split-Bregman approach. We show results for this framework combined with a total variation denoising operator, in comparison to ASD-POCS. We show that sparse-view reconstruction and noise regularization is possible. This general method will allow us to investigate other regularizers in the context of regularized CT reconstruction, and decrease the acquisition times in {\textmu}CT.},
  author       = {Vandeghinste, Bert and Goossens, Bart and De Beenhouwer, Jan and Pizurica, Aleksandra and Philips, Wilfried and Vandenberghe, Stefaan and Staelens, Steven},
  booktitle    = {Fully 3D 2011 proceedings},
  keyword      = {Noise,Computed Tomography,Reconstruction Algorithms,Iterative Algorithms},
  language     = {eng},
  location     = {Potsdam, Germany},
  pages        = {431--434},
  title        = {Split-Bregman-based sparse-view CT reconstruction},
  year         = {2011},
}

Chicago
Vandeghinste, Bert, Bart Goossens, Jan De Beenhouwer, Aleksandra Pizurica, Wilfried Philips, Stefaan Vandenberghe, and Steven Staelens. 2011. “Split-Bregman-based Sparse-view CT Reconstruction.” In Fully 3D 2011 Proceedings, 431–434.
APA
Vandeghinste, B., Goossens, B., De Beenhouwer, J., Pizurica, A., Philips, W., Vandenberghe, S., & Staelens, S. (2011). Split-Bregman-based sparse-view CT reconstruction. Fully 3D 2011 proceedings (pp. 431–434). Presented at the 11th International meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully 3D 11).
Vancouver
1.
Vandeghinste B, Goossens B, De Beenhouwer J, Pizurica A, Philips W, Vandenberghe S, et al. Split-Bregman-based sparse-view CT reconstruction. Fully 3D 2011 proceedings. 2011. p. 431–4.
MLA
Vandeghinste, Bert, Bart Goossens, Jan De Beenhouwer, et al. “Split-Bregman-based Sparse-view CT Reconstruction.” Fully 3D 2011 Proceedings. 2011. 431–434. Print.