DocumentCode :
3475182
Title :
Introducing shape priors in object-based tomographic reconstruction
Author :
Gaullier, Gil ; Charbonnier, Pierre ; Heitz, Fabrice
Author_Institution :
Lab. Regional des Ponts et Chaussees, ERA 27 LCPC, Strasbourg, France
fYear :
2009
fDate :
7-10 Nov. 2009
Firstpage :
1077
Lastpage :
1080
Abstract :
Regularized pixel-based tomographic reconstruction techniques suffer from streaking artifacts when only few projection angles are available. Shape-based methods, that reconstruct objects by optimizing their boundaries typically enforce a length penalty on the evolving curve, which is not suited to all possible shapes or topologies. To overcome this limitation, we propose in this paper to introduce high-level shape priors in tomographic reconstruction using active contours. Our shape descriptor is moment-based-hence rather compact and hierarchical - and may be made invariant to geometric transformations up to affine ones. It can handle multiple references simultaneously to accommodate shape variations. Experimental results on synthetic data show the effectiveness of the prior, especially for small numbers of noisy projections.
Keywords :
image reconstruction; optical tomography; geometric transformations; object-based tomographic reconstruction; regularized pixel-based tomographic reconstruction techniques; shape descriptor; shape priors; shape-based methods; streaking artifacts; Active contours; Computed tomography; Gas insulated transmission lines; Image reconstruction; Multi-stage noise shaping; Noise level; Noise shaping; Optimization methods; Shape; Topology; Active contours; Computerized tomography; Image reconstruction; Shape prior;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location :
Cairo
ISSN :
1522-4880
Print_ISBN :
978-1-4244-5653-6
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2009.5413470
Filename :
5413470
Link To Document :
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