Výsledky vyhledávání - "Savanier, Marion"

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Convergent ADMM Plug and Play PET Image Reconstruction

Autor: Sureau, Florent, Latreche, Mahdi, Savanier, Marion, Comtat, Claude

In this work, we investigate hybrid PET reconstruction algorithms based on coupling a model-based variational reconstruction and the application of a separately learnt Deep Neural Network operator (DNN) in an ADMM Plug and Play framework. Following r

Externí odkaz: http://arxiv.org/abs/2310.04299

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Deep Unfolding of the DBFB Algorithm with Application to ROI CT Imaging with Limited Angular Density

Autor: Savanier, Marion, Chouzenoux, Emilie, Pesquet, Jean-Christophe, Riddell, Cyril

This paper presents a new method for reconstructing regions of interest (ROI) from a limited number of computed tomography (CT) measurements. Classical model-based iterative reconstruction methods lead to images with predictable features. Still, they

Externí odkaz: http://arxiv.org/abs/2209.13264

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Iterative fixed point methods for image reconstruction in C-arm Cone Beam CT

Autor: Savanier, Marion

Publikováno v: Signal and Image Processing. Université Paris-Saclay, 2022. English. ⟨NNT : 2022UPAST130⟩

X-ray tomographic imaging, known as CT scanning, is available in clinical diagnostic routines thanks to the scanner. CT scanners allow precise differentiation of human tissues. However, these performances are obtained by technical choices incompatibl

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______165::ead308c71838605e89219849282241de
https://theses.hal.science/tel-03988504/file/109290_SAVANIER_2022_archivage.pdf

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Unmatched Preconditioning of the Proximal Gradient Algorithm

Autor: Savanier, Marion, Chouzenoux, Emilie, Pesquet, Jean-Christophe, Riddell, Cyril

Publikováno v: IEEE Signal Processing Letters
IEEE Signal Processing Letters, 2022, 29, pp.1122-1126. ⟨10.1109/LSP.2022.3169088⟩

International audience; This work addresses the resolution of penalized least-squares problems using the proximal gradient algorithm (PGA). PGA can be accelerated by preconditioning strategies. However, typical effective choices of preconditioners ma

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ec7d11009e4f78e8ba04c0ead3c2145
https://hal.science/hal-03654146/document

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A Matched CBCT Projector-Backprojector Based on the Convolution of B-splines

Autor: Savanier, Marion, Riddell, Cyril, Trousset, Yves, Chouzenoux, Emilie, Pesquet, Jean-Christophe

Publikováno v: CT Meeting 2020-6th International Conference on Image Formation in X-Ray Computed Tomography
CT Meeting 2020-6th International Conference on Image Formation in X-Ray Computed Tomography, Aug 2020, Regensburg (virtual), Germany

International audience; Discretizing tomographic operators is a crucial step in the design of reconstruction algorithms. In particular, for iterative methods, the projector and backprojector are usually assumed to be matched to guarantee convergence.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::99eb812fa727e76a1dbdd23ae863fa8c
https://hal.archives-ouvertes.fr/hal-03140763/file/A_Matched_CBCT_Projector_Backprojector_Based_on_the_Convolution_of_B-splines_final.pdf

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