Adapted Convex Optimization Algorithm for Wavelet-Based Dynamic PET Reconstruction

Abstract : This work deals with Dynamic Positron Emission Tomography (PET) data reconstruction, considering time as an additional variable (space+time). A convex optimization approach closely related to a Bayesian framework is adopted. The objective function to be minimized is expressed in the wavelet-frame domain and is non-necessarily differentiable in order to promote sparsity. We propose an adapted version of Forward-Backward- Douglas-Rachford (FBDR) algorithm to solve the resulting min- imization problem. The effectiveness of this approach is shown with simulated dynamic PET data. Comparative results are also provided.
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Communication dans un congrès
Fully3D, Sep 2009, Beijing, China. 10pp., 2009
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https://hal-upec-upem.archives-ouvertes.fr/hal-00621954
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Dernière modification le : jeudi 21 janvier 2016 - 15:20:11
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  • HAL Id : hal-00621954, version 1

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Nelly Pustelnik, Caroline Chaux, Jean-Christophe Pesquet, F. Sureau, E. Dush, et al.. Adapted Convex Optimization Algorithm for Wavelet-Based Dynamic PET Reconstruction. Fully3D, Sep 2009, Beijing, China. 10pp., 2009. <hal-00621954>

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