53 citations · 144 across the 12 of their papers we have counts for
12 papers
Efficiency analysis for quantitative MRI of T1 and T2 relaxometry methods
David Leitão, Rui Pedro A. G. Teixeira, Anthony Price +3
This study presents a comparison of quantitative MRI methods based on an efficiency metric that quantifies their intrinsic ability to extract information about tissue parameters. U…
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…
k-t NEXT: Dynamic MR Image Reconstruction Exploiting Spatio-temporal Correlations
Chen Qin, Jo Schlemper, Jinming Duan +4
Dynamic magnetic resonance imaging (MRI) exhibits high correlations in k-space and time. In order to accelerate the dynamic MR imaging and to exploit k-t correlations from highly u…
In utero diffusion MRI: challenges, advances, and applications
Daan Christiaens, Paddy J. Slator, Lucilio Cordero-Grande +6
In utero diffusion MRI provides unique opportunities to non-invasively study the microstructure of tissue during fetal development. A wide range of developmental processes, such as…
Scattered slice SHARD reconstruction for motion correction in multi-shell diffusion MRI
Daan Christiaens, Lucilio Cordero-Grande, Maximilian Pietsch +8
Diffusion MRI offers a unique probe into neural microstructure and connectivity in the developing brain. However, analysis of neonatal brain imaging data is complicated by inevitab…
Generalizing Deep Learning MRI Reconstruction across Different Domains
Cheng Ouyang, Jo Schlemper, Carlo Biffi +5
We look into the robustness of deep learning based MRI reconstruction when tested on unseen contrasts and organs. We then propose to generalize the network by training with large p…
Fetal whole-heart 4D imaging using motion-corrected multi-planar real-time MRI
Joshua FP van Amerom, David FA Lloyd, Maria Deprez +7
Purpose: To develop a MRI acquisition and reconstruction framework for volumetric cine visualisation of the fetal heart and great vessels in the presence of maternal and fetal moti…
Complex diffusion-weighted image estimation via matrix recovery under general noise models
Lucilio Cordero-Grande, Daan Christiaens, Jana Hutter +2
We propose a patch-based singular value shrinkage method for diffusion magnetic resonance image estimation targeted at low signal to noise ratio and accelerated acquisitions. It op…
Learning compact q-space representations for multi-shell diffusion-weighted MRI
Daan Christiaens, Lucilio Cordero-Grande, Jana Hutter +4
Diffusion-weighted MRI measures the direction and scale of the local diffusion process in every voxel through its spectrum in q-space, typically acquired in one or more shells. Rec…
Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction
Chen Qin, Jo Schlemper, Jose Caballero +3
Accelerating the data acquisition of dynamic magnetic resonance imaging (MRI) leads to a challenging ill-posed inverse problem, which has received great interest from both the sign…
A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction
Jo Schlemper, Jose Caballero, Joseph V. Hajnal +2
Inspired by recent advances in deep learning, we propose a framework for reconstructing dynamic sequences of 2D cardiac magnetic resonance (MR) images from undersampled data using…
A Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction
Jo Schlemper, Jose Caballero, Joseph V. Hajnal +2
The acquisition of Magnetic Resonance Imaging (MRI) is inherently slow. Inspired by recent advances in deep learning, we propose a framework for reconstructing MR images from under…