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
More filters
Journal ArticleDOI
Microbubble Identification Based on Decision Theory for Ultrasound Localization Microscopy
TL;DR: In this paper , the authors proposed a decision theory-based method for detecting microbubbles in ULM images, which is based on the Neyman-Pearson criterion and compared with the standard intensity-based and normalized cross-correlation detection methods on simulated and in vivo rat brain and kidney data.
Journal ArticleDOI
Simultaneous imaging of ultrasonic relative backscatter and attenuation coefficients for quantitative liver steatosis assessment
José Timaná,Hector Chahuara,Lokesh Basavarajappa,Adrian Basarab,Kenneth W Hoyt,Roberto Lavarello +5 more
TL;DR: In this paper , the authors presented an approach to detect the progression of liver steatosis based on quantitative ultrasound (QUS) imaging, which was performed on a group of 55 rats that were subjected to a control or methionine and choline deficient (MCD) diet.
Proceedings ArticleDOI
The role of the image phase in cardiac strain imaging
Martino Alessandrini,Adrian Basarab,M. De Craene,Maxime Sermesant,Herve Liebgott,Olivier Bernard,Jan D'hooge +6 more
TL;DR: This paper reviews the most recent contributions in the field of cardiac deformation imaging and shows an original evaluation of the proposed motion estimation technique based on the new benchmarking pipeline.
Journal ArticleDOI
Marmoset brain segmentation from deconvolved magnetic resonance images and estimated label maps.
TL;DR: In this article, a joint deconvolution and segmentation of the brain MR images is proposed, which is based on modeling locally the image statistics using a generalized Gaussian distribution and couples the deconvolved image and its corresponding labels map using the GGD-Potts model.
Proceedings ArticleDOI
Monogenic orientation-based blood flow estimation in high-frequency ultrasound imaging
TL;DR: In this article, a velocity estimation method was proposed based on the same assumption that a moving target leaves a trace in the spatio-temporal plane, generating an orientation of the texture related to its velocity.