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Proceedings Paper

Data sinogram sparse reconstruction based on steering kernel regression and filtering strategies
Author(s): Miguel A. Marquez; Edson Mojica; Henry Arguello
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Paper Abstract

Computed tomography images have an impact in many applications such as medicine, and others. Recently, compressed sensing-based acquisition strategies have been proposed in order to reduce the x-ray radiation dose. However, these methods lose critical information of the sinogram. In this paper, a reconstruction method of sparse measurements from a sinogram is proposed. The proposed approach takes advantage of the redundancy of similar patches in the sinogram, and estimates a target pixel using a weighted average of its neighbors. Simulation results show that the proposed method obtained a gain up to 2 dB with respect to an l1 minimization algorithm.

Paper Details

Date Published: 12 May 2016
PDF: 8 pages
Proc. SPIE 9847, Anomaly Detection and Imaging with X-Rays (ADIX), 98470Z (12 May 2016); doi: 10.1117/12.2224385
Show Author Affiliations
Miguel A. Marquez, Univ. Industrial de Santander (Colombia)
Edson Mojica, Univ. Industrial de Santander (Colombia)
Henry Arguello, Univ. Industrial de Santander (Colombia)


Published in SPIE Proceedings Vol. 9847:
Anomaly Detection and Imaging with X-Rays (ADIX)
Amit Ashok; Mark A. Neifeld; Michael E. Gehm, Editor(s)

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