activity
20192022
most citedFast Data-Driven Learning of MRI Sampling Pattern for Large Scale Problems

5 citations · 6 across the 4 of their papers we have counts for

collaborators

5 papers

physics.med-ph20221 cited

Optimizing Variable Flip-Angles in Magnetization-Prepared Gradient Echo Sequences for Efficient 3D-T1rho Mapping

Marcelo V W Zibetti, Hector L. De Moura, Mahesh B. Keerthivasan +1

Purpose: To optimize the choice of the flip-angles of magnetization-prepared gradient echo (MP-GRE) sequences for improved accuracy, precision, and speed of 3D-T1rho mapping. Metho…

eess.IV2021

Alternating Learning Approach for Variational Networks and Undersampling Pattern in Parallel MRI Applications

Marcelo V. W. Zibetti, Florian Knoll, Ravinder R. Regatte

Purpose: To propose an alternating learning approach to learn the sampling pattern (SP) and the parameters of variational networks (VN) in accelerated parallel magnetic resonance i…

eess.SP20205 cited

Fast Data-Driven Learning of MRI Sampling Pattern for Large Scale Problems

Marcelo V. W. Zibetti, Gabor T. Herman, Ravinder R. Regatte

Purpose: A fast data-driven optimization approach, named bias-accelerated subset selection (BASS), is proposed for learning efficacious sampling patterns (SPs) with the purpose of…

math.OC2020

Fast Proximal Gradient Methods for Nonsmooth Convex Optimization for Tomographic Image Reconstruction

Elias S. Helou, Marcelo V. W. Zibetti, Gabor T. Herman

The Fast Proximal Gradient Method (FPGM) and the Monotone FPGM (MFPGM) for minimization of nonsmooth convex functions are introduced and applied to tomographic image reconstruction…

cs.GR2019

The Discrete Fourier Transform for Golden Angle Linogram Sampling

Elias S. Helou, Marcelo V. W. Zibetti, Leon Axel +3

Estimation of the Discrete-Time Fourier Transform (DTFT) at points of a finite domain arises in many imaging applications. A new approach to this task, the Golden Angle Linogram Fo…