%0 Journal Article %T Strategy of computed tomography sinogram inpainting based on sinusoid-like curve decomposition and eigenvector-guided interpolation. %+ Centre de Recherche en Information Biomédicale sino-français (CRIBS) %+ Laboratory of Image Science and Technology [Nanjing] (LIST) %+ School of Biomedical Engineering %+ Laboratoire Traitement du Signal et de l'Image (LTSI) %A Li, Yinsheng %A Chen, Yang %A Hu, Yining %A Oukili, Ahmed %A Luo, Limin %A Chen, Wufan %A Toumoulin, Christine %Z This research was supported by National Basic Research Program of China under grant (2010CB732503), National Natural Science Foundation under grant (81000636), and the Project supported by Natural Science Foundation of Jiangsu Province (BK2009012). %< avec comité de lecture %@ 1084-7529 %J Journal of the Optical Society of America. A Optics, Image Science, and Vision %I Optical Society of America %V 29 %N 1 %P 153-63 %8 2012-01-01 %D 2012 %R 10.1364/JOSAA.29.000153 %M 22218362 %K computed tomography (CT) %K sinogram completion %K detector truncation %K sparse sampling %Z Life Sciences [q-bio]/BioengineeringJournal articles %X Projection incompleteness in x-ray computed tomography (CT) often relates to sparse sampling or detector gaps and leads to degraded reconstructions with severe streak and ring artifacts. To suppress these artifacts, this study develops a new sinogram inpainting strategy based on sinusoid-like curve decomposition and eigenvector-guided interpolation, where each missing sinogram point is considered located within a group of sinusoid-like curves and estimated from eigenvector-guided interpolation to preserve the sinogram texture continuity. The proposed approach is evaluated on real two-dimensional fan-beam CT data, for which the projection incompleteness, due to sparse sampling and symmetric detector gaps, is simulated. A Compute Unified Device Architecture (CUDA)-based parallelization is applied on the operations of sinusoid fittings and interpolations to accelerate the algorithm. A comparative study is then conducted to evaluate the proposed approach with two other inpainting methods and with a compressed sensing iterative reconstruction. Qualitative and quantitative performances demonstrate that the proposed approach can lead to efficient artifact suppression and less structure blurring. %G English %2 https://inserm.hal.science/inserm-00677987/document %2 https://inserm.hal.science/inserm-00677987/file/joas_2012.pdf %L inserm-00677987 %U https://inserm.hal.science/inserm-00677987 %~ INSERM %~ UNIV-RENNES1 %~ LTSI %~ CRIBS %~ UR1-HAL %~ UR1-MATH-STIC %~ TEST-UNIV-RENNES %~ TEST-UR-CSS %~ UNIV-RENNES %~ UR1-MATH-NUM %~ UR1-BIO-SA