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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.
Cited literature [17 references]
https://hal-upec-upem.archives-ouvertes.fr/hal-00621954
Contributor : Caroline Chaux <>
Submitted on : Tuesday, July 9, 2013 - 4:14:14 PM
Last modification on : Wednesday, February 26, 2020 - 7:06:05 PM
Document(s) archivé(s) le : Thursday, October 10, 2013 - 4:07:40 AM
Contributor : Caroline Chaux <>
Submitted on : Tuesday, July 9, 2013 - 4:14:14 PM
Last modification on : Wednesday, February 26, 2020 - 7:06:05 PM
Document(s) archivé(s) le : Thursday, October 10, 2013 - 4:07:40 AM
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