activity
20172022
most citeddAUTOMAP: decomposing AUTOMAP to achieve scalability and enhance performance

22 citations · 49 across the 14 of their papers we have counts for

collaborators

25 papers

physics.med-ph2022

Universal pulses for homogeneous excitation using single channel coils

Ronald Mooiweer, Ian A. Clark, Eleanor A. Maguire +3

Purpose: Universal Pulses (UPs) are excitation pulses that reduce the flip angle inhomogeneity in high field MRI systems without subject-specific optimization, originally developed…

physics.med-ph2020

Impact of aperture, depth, and acoustic clutter on performance of Coherent Multi-Transducer Ultrasound imaging

Laura Peralta, Alessandro Ramalli, Michael Reinwald +2

Transducers with larger aperture size are desirable in ultrasound imaging to improve resolution and image quality. A coherent multi-transducer ultrasound imaging system (CoMTUS) en…

eess.IV2020

Deep Generative Models to Simulate 2D Patient-Specific Ultrasound Images in Real Time

Cesare Magnetti, Veronika Zimmer, Nooshin Ghavami +6

We present a computational method for real-time, patient-specific simulation of 2D ultrasound (US) images. The method uses a large number of tracked ultrasound images to learn a fu…

physics.med-ph2019

Motion corrected MRI with DISORDER: Distributed and Incoherent Sample Orders for Reconstruction Deblurring using Encoding Redundancy

Lucilio Cordero-Grande, Giulio Ferrazzi, Rui Pedro A. G. Teixeira +3

Purpose: To enable rigid-body motion tolerant parallel volumetric magnetic resonance imaging by retrospective head motion correction on a variety of spatio-temporal scales and imag…

eess.IV20192 cited

Interpretable Convolutional Neural Networks for Preterm Birth Classification

Irina Grigorescu, Lucilio Cordero-Grande, A David Edwards +3

The use of convolutional neural networks (CNNs) for classification tasks has become dominant in various medical imaging applications. At the same time, recent advances in interpret…

eess.IV20193 cited

Data consistency networks for (calibration-less) accelerated parallel MR image reconstruction

Jo Schlemper, Jinming Duan, Cheng Ouyang +4

We present simple reconstruction networks for multi-coil data by extending deep cascade of CNN's and exploiting the data consistency layer. In particular, we propose two variants,…