Adaptive variational sinogram interpolation of sparsely sampled CT data

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Hornegger J, Köstler H, Rüde U, Prümmer M
Publication year: 2006
Volume: 3
Journal issue: null
Conference Proceedings Title: Proceedings of the ICPR 2006
Pages range: 778-781
ISSN: 1051-4651
Language: English


Abstract


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, © 2006 IEEE.



FAU Authors / FAU Editors

Hornegger, Joachim Prof. Dr.-Ing.
Lehrstuhl für Informatik 5 (Mustererkennung)
Köstler, Harald Prof. Dr.
Lehrstuhl für Informatik 10 (Systemsimulation)
Rüde, Ulrich Prof. Dr.
Lehrstuhl für Informatik 10 (Systemsimulation)


How to cite

APA:
Hornegger, J., Köstler, H., Rüde, U., & Prümmer, M. (2006). Adaptive variational sinogram interpolation of sparsely sampled CT data. In Proceedings of the ICPR 2006 (pp. 778-781). Hong Kong, CN.

MLA:
Hornegger, Joachim, et al. "Adaptive variational sinogram interpolation of sparsely sampled CT data." Proceedings of the 18th International Conference on Pattern Recognition, ICPR 2006, Hong Kong 2006. 778-781.

BibTeX: 

Last updated on 2019-18-04 at 16:05