activity
20182025
most citedLearning compact q-space representations for multi-shell diffusion-weighted MRI

24 citations · 27 across the 13 of their papers we have counts for

collaborators

12 papers

physics.med-ph2025

From Offline to Inline Without Pain: A Practical Framework for Translating Offline MR Reconstructions to Inline Deployment Using the Gadgetron Platform

Zihan Ning, Yannick Brackenier, Sarah McElroy +23

Purpose: To develop and validate a practical framework to overcome common issues in inline deployment of established offline MR reconstruction, including (1) delay from lengthy rec…

eess.IV2025

Meta-learning Slice-to-Volume Reconstruction in Fetal Brain MRI using Implicit Neural Representations

Maik Dannecker, Thomas Sanchez, Meritxell Bach Cuadra +6

High-resolution slice-to-volume reconstruction (SVR) from multiple motion-corrupted low-resolution 2D slices constitutes a critical step in image-based diagnostics of moving subjec…

cs.LG2024

CINA: Conditional Implicit Neural Atlas for Spatio-Temporal Representation of Fetal Brains

Maik Dannecker, Vanessa Kyriakopoulou, Lucilio Cordero-Grande +3

We introduce a conditional implicit neural atlas (CINA) for spatio-temporal atlas generation from Magnetic Resonance Images (MRI) of the neurotypical and pathological fetal brain,…

eess.IV2021

Fetal MRI by robust deep generative prior reconstruction and diffeomorphic registration: application to gestational age prediction

Lucilio Cordero-Grande, Juan Enrique Ortuño-Fisac, Alena Uus +4

Magnetic resonance imaging of whole fetal body and placenta is limited by different sources of motion affecting the womb. Usual scanning techniques employ single-shot multi-slice s…

eess.IV2020

Diffusion tensor driven image registration: a deep learning approach

Irina Grigorescu, Alena Uus, Daan Christiaens +6

Tracking microsctructural changes in the developing brain relies on accurate inter-subject image registration. However, most methods rely on either structural or diffusion data to…

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.IV2019★ 2 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…

physics.med-ph2019★ 1 cited

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…

physics.med-ph2019

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…

eess.IV2018

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…

stat.CO2018

MIXANDMIX: numerical techniques for the computation of empirical spectral distributions of population mixtures

Lucilio Cordero-Grande

The MIXANDMIX (mixtures by Anderson mixing) tool for the computation of the empirical spectral distribution of random matrices generated by mixtures of populations is described. Wi…

physics.med-ph2018★ 24 cited

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…