loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
18th International Conference on Pattern Recognition (ICPR'06) Volume 3
Adaptive variational sinogram interpolation of sparsely sampled CT data
Hong Kong
August 20-August 24
ISBN: 0-7695-2521-0
ASCII Text
x 
 
H. Kostler, M. Prummer, U. Rude, J. Hornegger, "Adaptive variational sinogram interpolation of sparsely sampled CT data," Pattern Recognition, International Conference on, vol. 3, pp. 778-781, 18th International Conference on Pattern Recognition (ICPR'06) Volume 3, 2006.
 
 
BibTex
x
 
@article{ 10.1109/ICPR.2006.225,
author = {H. Kostler and M. Prummer and U. Rude and J. Hornegger},
title = {Adaptive variational sinogram interpolation of sparsely sampled CT data},
journal ={Pattern Recognition, International Conference on},
volume = {3},
year = {2006},
issn = {1051-4651},
pages = {778-781},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.225},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Pattern Recognition, International Conference on
TI - Adaptive variational sinogram interpolation of sparsely sampled CT data
SN - 1051-4651
SP778
EP781
A1 - H. Kostler,
A1 - M. Prummer,
A1 - U. Rude,
A1 - J. Hornegger,
PY - 2006
KW - null
VL - 3
JA - Pattern Recognition, International Conference on
ER -
 
H. Kostler, Friedrich-Alexander University of Erlangen-Nuremberg 91058 Erlangen, Germany
M. Prummer, Friedrich-Alexander University of Erlangen-Nuremberg 91058 Erlangen, Germany
U. Rude, Friedrich-Alexander University of Erlangen-Nuremberg 91058 Erlangen, Germany
J. Hornegger, Friedrich-Alexander University of Erlangen-Nuremberg 91058 Erlangen, Germany
We present various kinds of variational PDE based methods to interpolate missing sinogram data for tomographic image reconstruction. Using the observed sinogram data we inpaint the projection data by diffusion. To overcome the problem of contour blurring we consider nonlinear and anisotropic diffusion based regularizers and include optical flow information in order to preserve the sinuodal traces corresponding to object contours in the reconstructed image. We compare our results to a spectral deconvolution based interpolation and show that the method can easily be extended to 3D.
Citation:
H. Kostler, M. Prummer, U. Rude, J. Hornegger, "Adaptive variational sinogram interpolation of sparsely sampled CT data," icpr, vol. 3, pp.778-781, 18th International Conference on Pattern Recognition (ICPR'06) Volume 3, 2006
Usage of this product signifies your acceptance of the Terms of Use.