A. David Edwards

Daniel Rueckert, Joseph V. Hajnal, Kanwal K. Bhatia, 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).

Regional changes in thalamic shape and volume with increasing age

Joseph V. Hajnal, David J. Sharp, A. David Edwards, 2012, NeuroImage.

Robust segmentation of brain MRI using combination of registration and EM-based methods

Daniel Rueckert, Mary A. Rutherford, Joseph V. Hajnal, 2007, SCCG.

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction

Daniel Rueckert, Mark Jenkinson, Mary A. Rutherford, 2017, NeuroImage.

A framework for multi-component analysis of diffusion MRI data over the neonatal period

Joseph V. Hajnal, Jacques-Donald Tournier, Anthony N. Price, 2019, NeuroImage.

Scattered slice SHARD reconstruction for motion correction in multi-shell diffusion MRI

Joseph V. Hajnal, Jacques-Donald Tournier, Anthony N. Price, 2019, NeuroImage.

Construction of a consistent high-definition spatio-temporal atlas of the developing brain using adaptive kernel regression

Daniel Rueckert, Mary A. Rutherford, Joseph V. Hajnal, 2012, NeuroImage.

Characterising brain network topologies: A dynamic analysis approach using heat kernels

Paul Aljabar, Giovanni Montana, A. W. Chung, 2016, NeuroImage.

Automated processing pipeline for neonatal diffusion MRI in the developing Human Connectome Project

Daniel Rueckert, Stephen M. Smith, Mary A. Rutherford, 2019, NeuroImage.

Automatic Detection of Neonatal Brain Injury on MRI

A. David Edwards, Serena J. Counsell, Jonathan O'Muircheartaigh, 2020, ASMUS/PIPPI@MICCAI.

An optimised tract-based spatial statistics protocol for neonates: Applications to prematurity and chronic lung disease

Daniel Rueckert, Mary A. Rutherford, Tomoki Arichi, 2010, NeuroImage.

A multivariate statistical analysis of the developing human brain in preterm infants

Carlos E. Thomaz, Duncan Fyfe Gillies, Daniel Rueckert, 2007, Image Vis. Comput..

Probabilistic white matter and fiber tract atlas construction

Daniel Rueckert, Alexander Hammers, Emma C. Robinson, 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

A tract-specific approach to assessing white matter in preterm infants

Paul A. Yushkevich, Joseph V. Hajnal, Paul Aljabar, 2017, NeuroImage.

Diffusion tensor imaging with tract-based spatial statistics reveals local white matter abnormalities in preterm infants

Mary A. Rutherford, Joseph V. Hajnal, A. David Edwards, 2007, NeuroImage.

Quantifying brain development in early childhood using segmentation and registration

Daniel Rueckert, Mary A. Rutherford, Joseph V. Hajnal, 2007, SPIE Medical Imaging.

A Probabilistic Framework to Infer Brain Functional Connectivity from Anatomical Connections

Daniel Rueckert, Fani Deligianni, Gaël Varoquaux, 2011, IPMI.

Automatic segmentation and reconstruction of the cortex from neonatal MRI

Daniel Rueckert, Mary A. Rutherford, Joseph V. Hajnal, 2007, NeuroImage.

Early development of structural networks and the impact of prematurity on brain connectivity

Chiara Nosarti, Joseph V. Hajnal, Paul Aljabar, 2017, NeuroImage.

Identifying population differences in whole-brain structural networks: A machine learning approach

Daniel Rueckert, Alexander Hammers, Emma C. Robinson, 2010, NeuroImage.

Robust segmentation of brain structures in MRI

Daniel Rueckert, Joseph V. Hajnal, A. David Edwards, 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Magnetic Resonance Imaging of the Newborn Brain: Automatic Segmentation of Brain Images into 50 Anatomical Regions

Daniel Rueckert, Mary A. Rutherford, Alexander Hammers, 2013, PloS one.

Inference of functional connectivity from structural brain connectivity

Daniel Rueckert, Fani Deligianni, David J. Sharp, 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Diffusion Tensor Driven Image Registration: A Deep Learning Approach

Marc Modat, Joseph V. Hajnal, Daan Christiaens, 2020, WBIR.

Regional growth and atlasing of the developing human brain

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2016, NeuroImage.

Abnormal deep grey matter development following preterm birth detected using deformation-based morphometry

Daniel Rueckert, Mary A. Rutherford, Joseph V. Hajnal, 2006, NeuroImage.

Longitudinal Cortical Registration for Developing Neonates

Daniel Rueckert, Mary A. Rutherford, Joseph V. Hajnal, 2007, MICCAI.

Development of BOLD signal hemodynamic responses in the human brain

Gianlorenzo Fagiolo, Etienne Burdet, Tomoki Arichi, 2012, NeuroImage.

Exploiting hierarchy in structural brain networks

Daniel Rueckert, Fani Deligianni, David J. Sharp, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Inference of functional connectivity from direct and indirect structural brain connections

Daniel Rueckert, Fani Deligianni, David J. Sharp, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Learning and Combining Image Similarities for Neonatal Brain Population Studies

Ben Glocker, Daniel Rueckert, Mary A. Rutherford, 2015, MLMI.

A deep learning approach to segmentation of the developing cortex in fetal brain MRI with minimal manual labeling

Konstantinos Kamnitsas, Daniel Rueckert, Mary A. Rutherford, 2020, MIDL.

Normalisation of Neonatal Brain Network Measures Using Stochastic Approaches

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2013, MICCAI.

An Evaluation of Deformation-Based Morphometry Applied to the Developing Human Brain and Detection of Volumetric Changes Associated with Preterm Birth

Daniel Rueckert, Mary A. Rutherford, Joseph V. Hajnal, 2003, MICCAI.

A Combined Manifold Learning Analysis of Shape and Appearance to Characterize Neonatal Brain Development

Daniel Rueckert, Mary A. Rutherford, Joseph V. Hajnal, 2011, IEEE Transactions on Medical Imaging.

Erratum to Construction of a consistent high-definition spatio-temporal atlas of the developing brain using adaptive kernel regression [NeuroImage 59/3(2012) 2255–2265]

Daniel Rueckert, Mary A. Rutherford, Joseph V. Hajnal, 2012, NeuroImage.

Combining Morphological Information in a Manifold Learning Framework: Application to Neonatal MRI

Mary A. Rutherford, Joseph V. Hajnal, Robin Wolz, 2010, MICCAI.

Groupwise Combined Segmentation and Registration for Atlas Construction

Daniel Rueckert, Mary A. Rutherford, Joseph V. Hajnal, 2007, MICCAI.

Machine-learning to characterise neonatal functional connectivity in the preterm brain

Joseph V. Hajnal, Paul Aljabar, Tomoki Arichi, 2016, NeuroImage.

Multi-channel Registration for Diffusion MRI: Longitudinal Analysis for the Neonatal Brain

Joseph V. Hajnal, Jacques-Donald Tournier, Daan Christiaens, 2020, WBIR.

Construction of a dynamic 4D probabilistic atlas for the developing brain

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Somatosensory cortical activation identified by functional MRI in preterm and term infants

Etienne Burdet, Tomoki Arichi, A. David Edwards, 2010, NeuroImage.

A dynamic 4D probabilistic atlas of the developing brain

Daniel Rueckert, Mary A. Rutherford, Joseph V. Hajnal, 2011, NeuroImage.

An eye tracking based virtual reality system for use inside magnetic resonance imaging systems

Joseph V. Hajnal, Etienne Burdet, Anthony N. Price, 2021, Scientific Reports.

Uncertainty-Aware Deep Learning Based Deformable Registration

Marc Modat, Daan Christiaens, A. David Edwards, 2021, UNSURE/PIPPI@MICCAI.

Reinforcement of the Brain's Rich-Club Architecture Following Early Neurodevelopmental Disruption Caused by Very Preterm Birth

Chiara Nosarti, Robin M. Murray, A. David Edwards, 2016, Cerebral cortex.

Multimodal Surface Matching with Higher-Order Smoothness Constraints

Ben Glocker, Daniel Rueckert, Mark Jenkinson, 2017 .

Automatic tissue and structural segmentation of neonatal brain MRI using Expectation-Maximization

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2012 .

Assessment of Neonatal Encephalopathy by Amplitude-integrated Electroencephalography

A. David Edwards, Frances M. Cowan, F. Cowan, 1999, Pediatrics.

Atlas selection strategy for automatic segmentation of pediatric brain MRIs into 83 ROIs

Daniel Rueckert, Alexander Hammers, Rolf A. Heckemann, 2010, 2010 IEEE International Conference on Imaging Systems and Techniques.