56 citations · 317 across the 23 of their papers we have counts for
25 papers
Deep Unfolded Approximate Message Passing for Quantitative Acoustic Microscopy Image Reconstruction
Odysseas Pappas, Jonathan Mamou, Adrian Basarab +2
Quantitative Acoustic Microscopy (QAM) is an imaging technology utilising high frequency ultrasound to produce quantitative two-dimensional (2D) maps of acoustical and mechanical p…
Mask-guided Data Augmentation for Multiparametric MRI Generation with a Rare Hepatocellular Carcinoma
Karen Sanchez, Carlos Hinojosa, Kevin Arias +4
Data augmentation is classically used to improve the overall performance of deep learning models. It is, however, challenging in the case of medical applications, and in particular…
Deep Ultrasound Denoising Using Diffusion Probabilistic Models
Hojat Asgariandehkordi, Sobhan Goudarzi, Adrian Basarab +1
Ultrasound images are widespread in medical diagnosis for musculoskeletal, cardiac, and obstetrical imaging due to the efficiency and non-invasiveness of the acquisition methodolog…
DIVA: Deep Unfolded Network from Quantum Interactive Patches for Image Restoration
Sayantan Dutta, Adrian Basarab, Bertrand Georgeot +1
This paper presents a deep neural network called DIVA unfolding a baseline adaptive denoising algorithm (De-QuIP), relying on the theory of quantum many-body physics. Furthermore,…
Inverse Problem of Ultrasound Beamforming with Denoising-Based Regularized Solutions
Sobhan Goudarzi, Adrian Basarab, Hassan Rivaz
During the past few years, inverse problem formulations of ultrasound beamforming have attracted a growing interest. They usually pose beamforming as a minimization problem of a fi…
A Unifying Approach to Inverse Problems of Ultrasound Beamforming and Deconvolution
Sobhan Goudarzi, Adrian Basarab, Hassan Rivaz
Beamforming is an essential step in the ultrasound image formation pipeline and has recently attracted growing interest. An important goal of beamforming is to increase the image s…