A
Adrian Basarab
Researcher at University of Toulouse
Publications - 174
Citations - 2664
Adrian Basarab is an academic researcher from University of Toulouse. The author has contributed to research in topics: Motion estimation & Deconvolution. The author has an hindex of 26, co-authored 159 publications receiving 2125 citations. Previous affiliations of Adrian Basarab include Paul Sabatier University & Centre national de la recherche scientifique.
Papers
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Journal ArticleDOI
Fusion of Magnetic Resonance and Ultrasound Images for Endometriosis Detection
Oumaima El Mansouri,Fabien Vidal,Adrian Basarab,Pierre Payoux,Denis Kouame,Jean-Yves Tourneret +5 more
TL;DR: A new fusion method for magnetic resonance (MR) and ultrasound (US) images, which aims at combining the advantages of each modality, i.e., good contrast and signal to noise ratio for the MR image and good spatial resolution for the US image.
Journal ArticleDOI
Strong reflector-based beamforming in ultrasound medical imaging.
TL;DR: The ability of the proposed methods to precisely detect the number and the position of the strong reflectors in a sparse medium and to accurately reduce the speckle and highly enhance the contrast in a non-sparse medium is confirmed.
Posted Content
Joint Blind Deconvolution and Robust Principal Component Analysis for Blood Flow Estimation in Medical Ultrasound Imaging
TL;DR: Numerical experiments conducted on simulated and in vivo data demonstrate qualitatively and quantitatively the effectiveness of the proposed approach in comparison with the previous method based on experimentally measured PSF and two other state-of-the-art approaches.
Posted Content
A Novel Fast 3D Single Image Super-Resolution Algorithm
TL;DR: The proposed decomposition technique of the 3D decimation operator allows a straightforward implementation for Tikhonov regularization, and can be further used to take into consideration other regularization functions such as the total variation, enabling the computational cost of state-of-the-art algorithms to be considerably decreased.
Proceedings ArticleDOI
Ultrasound compressive deconvolution with ℓ P -Norm prior
TL;DR: This paper addresses the problem of compressive deconvolution for ultrasound imaging systems using an assumption of generalized Gaussian distributed tissue reflectivity function and proposes a novel ℓp-norm (1 ≤ p ≤ 2) algorithm based on Alternating Direction Method of Multipliers.