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Proceedings Article

On structured sparsity and selected applications in tomographic imaging

[+] Author Affiliations
Aleksandra Pižurica, Jan Aelterman, F. Bai, Sam Vanloocke, Hiep Quang Luong, Bart Goossens, Wilfried Philips

Ghent Univ. (Belgium)

Proc. SPIE 8138, Wavelets and Sparsity XIV, 81381D (September 27, 2011); doi:10.1117/12.893784
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From Conference Volume 8138

  • Wavelets and Sparsity XIV
  • Manos Papadakis; Dimitri Van De Ville; Vivek K. Goyal
  • San Diego, California, USA | August 21, 2011

abstract

This work explores the potentials of structure encoding in sparse tomographic reconstructions. We are encoding spatial structure with Markov Random Field (MRF) models and employ it within Magnetic Resonance Imaging (MRI) and Quantitative Microwave Tomography. We illustrate thereby also different ways of MRF modelling: as a discrete, binary field imposed on hidden labels and as a continuous model imposed on the observable field. In case of MRI, the analyzed approach is a straightforward extension of sparse MRI methods and is related to the so-called LaMP (Lattice Matching Pursuit) algorithm, but with a number of differences. In case of Microwave Tomography, we give another interpretation of structured sparsity using much different, but also effective approach. Thorough experiments demonstrate clear advantages of MRF based structure encoding in both cases and motivate strongly further development.

© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation

Aleksandra Pižurica ; Jan Aelterman ; F. Bai ; Sam Vanloocke ; Hiep Quang Luong, et al.
"On structured sparsity and selected applications in tomographic imaging", Proc. SPIE 8138, Wavelets and Sparsity XIV, 81381D (September 27, 2011); doi:10.1117/12.893784; http://dx.doi.org/10.1117/12.893784


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