Zobrazeno 1 - 10
of 982
pro vyhledávání: '"Weiss Pierre"'
Autor:
Touya Nicolas, Reiss Ségolène, Rouillon Thierry, Dutilleul Maeva, Veziers Joelle, Pare Arnaud, Brasset Ludmila, Weiss Pierre, Corre Pierre, Charbonnier Baptiste
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract The development of synthetic bone substitutes that equal or exceed the efficacy of autologous graft remains challenging. In this study, a rat calvarial defect model was used as a reference to investigate the influence of composition and arch
Externí odkaz:
https://doaj.org/article/b0a1d26b4f004e45bed68b793f8fb87b
Publikováno v:
Journal of Oral Medicine and Oral Surgery, Vol 25, Iss 3, p 23 (2019)
Introduction: Following any oral surgery procedure, postoperative pain is an inevitable outcome and can be described as moderate to severe. The pain management is essential for the comfort and the well-being of the patients. Topical delivery and more
Externí odkaz:
https://doaj.org/article/713e693a74b841ab8ad69fafcf714316
We propose an adaptive refinement algorithm to solve total variation regularized measure optimization problems. The method iteratively constructs dyadic partitions of the unit cube based on i) the resolution of discretized dual problems and ii) on th
Externí odkaz:
http://arxiv.org/abs/2301.07555
Publikováno v:
Machine.Learning.for.Biomedical.Imaging. 2 (2023)
Data-driven optimization of sampling patterns in MRI has recently received a significant attention.Following recent observations on the combinatorial number of minimizers in off-the-grid optimization, we propose a framework to globally optimize the s
Externí odkaz:
http://arxiv.org/abs/2209.07170
A recent trend in the signal/image processing literature is the optimization of Fourier sampling schemes for specific datasets of signals. In this paper, we explain why choosing optimal non Cartesian Fourier sampling patterns is a difficult nonconvex
Externí odkaz:
http://arxiv.org/abs/2207.10323
Autor:
Gossard, Alban, Weiss, Pierre
Neural networks allow solving many ill-posed inverse problems with unprecedented performance. Physics informed approaches already progressively replace carefully hand-crafted reconstruction algorithms in real applications. However, these networks suf
Externí odkaz:
http://arxiv.org/abs/2202.11342
Autor:
Debarnot, Valentin, Weiss, Pierre
Assume that an unknown integral operator living in some known subspace is observed indirectly, by evaluating its action on a few Dirac masses at unknown locations. Is this information enough to recover the operator and the impulse responses locations
Externí odkaz:
http://arxiv.org/abs/2111.02093
Autor:
R, Chaithya G, Weiss, Pierre, Daval-Frérot, Guillaume, Massire, Aurélien, Vignaud, Alexandre, Ciuciu, Philippe
The Spreading Projection Algorithm for Rapid K-space samplING, or SPARKLING, is an optimization-driven method that has been recently introduced for accelerated 2D T2*-w MRI using compressed sensing. It has then been extended to address 3D imaging usi
Externí odkaz:
http://arxiv.org/abs/2108.02991
Autor:
Rakic, Mia, Canullo, Luigi, Radovanovic, Sandro, Tatic, Zoran, Radunovic, Milena, Souedain, Assem, Weiss, Pierre, Struillou, Xavier, Vojvodic, Danilo
Publikováno v:
In Dental Materials January 2024 40(1):28-36
Publikováno v:
ITWIST 2020, Dec 2020, Nantes, France
We propose a novel learning based algorithm to generate efficient and physically plausible sampling patterns in MRI. This method has a few advantages compared to recent learning based approaches: i) it works off-the-grid and ii) allows to handle arbi
Externí odkaz:
http://arxiv.org/abs/2010.01817