Paul Aljabar

发表

Multi-region analysis of longitudinal FDG-PET for the classification of Alzheimer's disease

Daniel Rueckert, Katherine R Gray, Robin Wolz, 2012, NeuroImage.

Automatic segmentation of brain MRIs and mapping neuroanatomy across the human lifespan

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2009, Medical Imaging.

Diffeomorphic Registration Using B-Splines

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2006, MICCAI.

A 4D neonatal head model for diffuse optical imaging of pre-term to term infants

Simon R. Arridge, Paul Aljabar, Sabrina Brigadoi, 2014, NeuroImage.

Interpolation Artefacts in Non-rigid Registration

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2005, MICCAI.

Automatic quantification of normal cortical folding patterns from fetal brain MRI

Daniel Rueckert, Mary A. Rutherford, Joseph V. Hajnal, 2014, NeuroImage.

A Four-dimensional Atlas of Neonatal Brain MRI

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2011, MIUA.

Multi-atlas Segmentation as a Graph Labelling Problem: Application to Partially Annotated Atlas Data

Daniel Rueckert, Paul Aljabar, Tong Tong, 2015, IPMI.

2011 8TH IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO

Daniel Rueckert, Paul Aljabar, Ahmed Serag, 2011, ISBI 2011.

Analysis of growth in the developing brain using non-rigid registration

Daniel Rueckert, Mary A. Rutherford, Joseph V. Hajnal, 2006, 3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006..

Towards dense motion estimation in light and electron microscopy

Daniel Rueckert, Paul Aljabar, José Delpiano, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Medical Image Computing and Computer Assisted Intervention - MICCAI 2007

Daniel Rueckert, Mary A. Rutherford, Paul Aljabar, 2007 .

Chapter 3 – Functions

Paul Aljabar, Andrew P. King, 2017 .

Manifold Forests for Multi-modality Classification of Alzheimer’s Disease

Daniel Rueckert, Paul Aljabar, Alexander Hammers, 2013 .

Automatic Whole Brain MRI Segmentation of the Developing Neonatal Brain

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2014, IEEE Transactions on Medical Imaging.

Novel MRI Technique Enables Non-Invasive Measurement of Atrial Wall Thickness

Markus Henningsson, Paul Aljabar, Tobias Schaeffter, 2017, IEEE Transactions on Medical Imaging.

Measurement of hippocampal atrophy using 4D graph-cut segmentation: Application to ADNI

Jyrki Lötjönen, Daniel Rueckert, Joseph V. Hajnal, 2010, NeuroImage.

2012 9TH IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI)

Daniel Rueckert, Paul Aljabar, Ahmed Serag, 2012, ISBI 2012.

Improving intersubject image registration using tissue-class information benefits robustness and accuracy of multi-atlas based anatomical segmentation

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2010, NeuroImage.

Improved slice to volume reconstruction of the fetal brain for automated cortex segmentation

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2009 .

Chapter 7 – Program Design

Paul Aljabar, Andrew P. King, 2017 .

A common neonatal image phenotype predicts adverse neurodevelopmental outcome in children born preterm

Daniel Rueckert, Mary A. Rutherford, Paul Aljabar, 2010, NeuroImage.

Quantification of Growth and Motion Using Non-rigid Registration

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

Automatic multi-label segmentation of the preterm brain with the use of adaptive atlases

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

Fast Volume Reconstruction from Motion Corrupted Stacks of 2D Slices

Daniel Rueckert, Bernhard Kainz, Christina Malamateniou, 2015, IEEE Transactions on Medical Imaging.

Non-rigid registration using free-form deformations

Daniel Rueckert, Paul Aljabar, D. Rueckert, 2015 .

Random forest-based similarity measures for multi-modal classification of Alzheimer's disease

Daniel Rueckert, Paul Aljabar, Alexander Hammers, 2013, NeuroImage.

Nonlinear dimensionality reduction combining MR imaging with non-imaging information

Jyrki Lötjönen, Daniel Rueckert, Joseph V. Hajnal, 2012, Medical Image Anal..

Assessment of brain growth in early childhood using deformation-based morphometry

Daniel Rueckert, Mary A. Rutherford, Joseph V. Hajnal, 2008, NeuroImage.

Unsupervised Learning of Shape Complexity: Application to Brain Development

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

Multiview Machine Learning Using an Atlas of Cardiac Cycle Motion

Paul Aljabar, Mathieu De Craene, Hélène Langet, 2017, STACOM@MICCAI.

Temporal sparse free-form deformations

Daniel Rueckert, Haiyan Wang, Xiahai Zhuang, 2013, Medical Image Anal..

BRAIN-WIDE SURVEY OF ANATOMICAL STRUCTURES AS CLASSIFIERS IN TEMPORAL LOBE EPILEPSY USING AUTOMATIC SEGMENTATION AND STRUCTURE SELECTION

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2010 .

Spatio-temporal Image Analysis for Longitudinal and Time-Series Image Data

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2015, MICCAI 2015.

A Multi-channel 4D Probabilistic Atlas of the Developing Brain: Application to Fetuses and Neonates

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

Comparison and Evaluation of Segmentation Techniques for Subcortical Structures in Brain MRI

Daniel Rueckert, Timothy F. Cootes, Stephen M. Smith, 2008, MICCAI.

Graph-Based Label Propagation in Fetal Brain MR Images

Daniel Rueckert, Christina Malamateniou, Mary A. Rutherford, 2014, MLMI.

Classifier Selection Strategies for Label Fusion Using Large Atlas Databases

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2007, MICCAI.

LISA: Longitudinal image registration via spatio-temporal atlases

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2012, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI).

Signal and Image Processing

Paul Aljabar, Andrew P. King, 2017 .

Spatio-temporal Image Analysis for Longitudinal and Time-Series Image Data

Daniel Rueckert, Paul Aljabar, Christian Ledig, 2015, MICCAI 2015.

Parcellation-Independent Multi-Scale Framework for Brain Network Analysis

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2014 .

Analysis of serial magnetic resonance images of mouse brains using image registration

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2009, NeuroImage.

Appreciation to IJCV Reviewers of 2016

Hakan Cevikalp, Rama Chellappa, Anoop Cherian, 2016, International Journal of Computer Vision.

Automatic detection and quantification of hippocampal atrophy on MRI in temporal lobe epilepsy: A proof-of-principle study

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2007, NeuroImage.

Manifold Learning for Biomarker Discovery in MR Imaging

Daniel Rueckert, Joseph V. Hajnal, Robin Wolz, 2010, MLMI.

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.

Multi-atlas based segmentation of brain images: Atlas selection and its effect on accuracy

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2009, NeuroImage.

Chapter 1 – Introduction to Computer Programming and MATLAB

Paul Aljabar, Andrew P. King, 2017 .

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

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

Hierarchical Statistical Shape Analysis and Prediction of Sub-cortical Brain Structures

Daniel Rueckert, Paul Aljabar, Anil Rao, 2007 .

Automatic volumetry can reveal visually undetected disease features on brain MR images in temporal lobe epilepsy

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

Multi-Atlas Segmentation Using Partially Annotated Data: Methods and Annotation Strategies

Daniel Rueckert, Paul Aljabar, Wenjia Bai, 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Resting State fMRI in the moving fetus: A robust framework for motion, bias field and spin history correction

Christina Malamateniou, Mary A. Rutherford, Joseph V. Hajnal, 2014, NeuroImage.

Automatic morphometry in Alzheimer's disease and mild cognitive impairment☆☆☆

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2011, NeuroImage.

Regional analysis of FDG-PET for use in the classification of Alzheimer'S Disease

Daniel Rueckert, Robin Wolz, Paul Aljabar, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Construction of a 4D atlas of the developing brain using non-rigid registration

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

File Input/Output

Paul Aljabar, Andrew P. King, 2017 .

Machine learning meets medical imaging: Learning and discovery of clinically useful information from images

Daniel Rueckert, Robin Wolz, Paul Aljabar, 2013 .

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

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

Quantifying brain development in early childhood using segmentation and registration

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

MATLAB Programming for Biomedical Engineers and Scientists

Paul Aljabar, 2017 .

Nonrigid Registration of Medical Images: Theory, Methods, and Applications [Applications Corner]

Daniel Rueckert, Paul Aljabar, 2010, IEEE Signal Processing Magazine.

Chapter 9 – Code Efficiency

Paul Aljabar, Andrew P. King, 2017 .

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

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

Construction of a fetal spatio-temporal cortical surface atlas from in utero MRI: Application of spectral surface matching

Daniel Rueckert, Mary A. Rutherford, Joseph V. Hajnal, 2015, NeuroImage.

Automatic anatomical brain MRI segmentation combining label propagation and decision fusion

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2006, NeuroImage.

LEAP: Learning embeddings for atlas propagation

Daniel Rueckert, Joseph V. Hajnal, Robin Wolz, 2010, NeuroImage.

Towards a multimodal cardiac motion atlas

Paul Aljabar, Mathieu De Craene, Andrew P. King, 2016, 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI).

Spatio-Temporal Maps of T1 and T2 Weighted Signal Intensity Change in the Developing Brain

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2011 .

Construction of a patient-specific atlas of the brain: Application to normal aging

Daniel Rueckert, Paul Aljabar, Anders Ericsson, 2008, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

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.

A repository of MR morphometry data in Alzheimer's disease and mild cognitive impairment

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Machine Learning in Medical Imaging

Daniel Rueckert, Christina Malamateniou, Paul Aljabar, 2014, Lecture Notes in Computer Science.

Corrigendum to “An evaluation of four automatic methods of segmenting the subcortical structures in the brain” [NeuroImage 47 (2009) 1435–1447]

Daniel Rueckert, Timothy F. Cootes, Stephen M. Smith, 2010, NeuroImage.

Comparative evaluation of autocontouring in clinical practice: A practical method using the Turing test

Paul Aljabar, Andre Dekker, Devis Peressutti, 2018, Medical physics.

Chapter 2 – Control Structures

Paul Aljabar, Andrew P. King, 2017 .

Segmentation of subcortical structures and the hippocampus in brain MRI using graph-cuts and subject-specific a-priori information

Daniel Rueckert, Robin Wolz, Paul Aljabar, 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Large dynamic range relative B1+ mapping

Aaron T. Hess, Joseph V. Hajnal, Paul Aljabar, 2015, Magnetic resonance in medicine.

A multimodal spatiotemporal cardiac motion atlas from MR and ultrasound data

Paul Aljabar, Mathieu De Craene, Hélène Langet, 2017, Medical Image Anal..

Machine Learning in Medical Imaging

Daniel Rueckert, Paul Aljabar, Alexander Hammers, 2011, Lecture Notes in Computer Science.

Measuring atrophy by simultaneous segmentation of serial MR images using 4-D graph-cuts

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

Chapter 8 – Visualization

Paul Aljabar, Andrew P. King, 2017 .

Learning and Combining Image Similarities for Neonatal Brain Population Studies

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

Manifold-based classification incorporating subject metadata

Jyrki Lötjönen, Daniel Rueckert, Joseph V. Hajnal, 2011, MIUA.

Spectral Clustering as a Diagnostic Tool in Cross-Sectional MR Studies: An Application to Mild Dementia

Daniel Rueckert, Paul Aljabar, William R. Crum, 2008, MICCAI.

Program Development and Testing

Paul Aljabar, Andrew P. King, 2017 .

Normalisation of Neonatal Brain Network Measures Using Stochastic Approaches

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

Cerebral atrophy measurements using Jacobian integration: Comparison with the boundary shift integral

Daniel Rueckert, Jennifer L. Whitwell, Paul Aljabar, 2006, NeuroImage.

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.

Multi-atlas propagation with enhanced registration { MAPER

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

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.

Brain Extraction Using Label Propagation and Group Agreement: Pincram

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2015, PloS one.

Groupwise Combined Segmentation and Registration for Atlas Construction

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

The mirror method of assessing segmentation quality in atlas label propagation

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Multi-class brain segmentation using atlas propagation and EM-based refinement

Jyrki Lötjönen, Daniel Rueckert, Robin Wolz, 2012, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI).

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

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

Manifold Learning for Medical Image Registration, Segmentation, and Classification

Daniel Rueckert, Robin Wolz, Paul Aljabar, 2012 .

Regional Analysis of FDG-PET for the Classification of Alzheimers Disease

Daniel Rueckert, Robin Wolz, Paul Aljabar, 2011, MIUA.

Super-Resolved Micro-Vascular Imaging Using Microbubbles and Machine Learning

Paul Aljabar, Robert J. Eckersley, Christopher Dunsby, 2014 .

Multiclassifier Fusion in Human Brain MR Segmentation: Modelling Convergence

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2006, MICCAI.

Manifold learning combining imaging with non-imaging information

Jyrki Lötjönen, Daniel Rueckert, Joseph V. Hajnal, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Spatial transformation of motion and deformation fields using nonrigid registration

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2004, IEEE Transactions on Medical Imaging.

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.

Automated super-resolution image processing in ultrasound using machine learning

Paul Aljabar, Markus Schirmer, Sevan Harput, 2017, 2017 IEEE International Ultrasonics Symposium (IUS).

Random Forest-Based Manifold Learning for Classification of Imaging Data in Dementia

Daniel Rueckert, Paul Aljabar, Alexander Hammers, 2011, MLMI.

Automated morphological analysis of magnetic resonance brain imaging using spectral analysis

Daniel Rueckert, Paul Aljabar, William R. Crum, 2008, NeuroImage.

An evaluation of four automatic methods of segmenting the subcortical structures in the brain

Daniel Rueckert, Timothy F. Cootes, Stephen M. Smith, 2009, NeuroImage.

A dynamic 4D probabilistic atlas of the developing brain

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

Tracking developmental changes in subcortical structures of the preterm brain using multi-modal MRI

Daniel Rueckert, Joseph V. Hajnal, Paul Aljabar, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Fetal cardiac cine imaging using highly accelerated dynamic MRI with retrospective motion correction and outlier rejection

Paul Aljabar, Reza Razavi, Kuberan Pushparajah, 2017, Magnetic resonance in medicine.

Deep Learning-Based Landmark Localisation in the Liver for Couinaud Segmentation

Paul Aljabar, Ged Ridgway, Zobair Arya, 2021, MIUA.

Slice-to-Volume Registration Enables Automated Pancreas MRI Quantification in UK Biobank

Paul Aljabar, Alexandre Triay Bagur, John McGonigle, 2021, MIUA.

Pancreas Volumetry in UK Biobank: Comparison of Models and Inference at Scale

Paul Aljabar, Alexandre Triay Bagur, John McGonigle, 2021, MIUA.

Machine learning shows association between genetic variability in PPARG and cerebral connectivity in preterm infants

Joseph V. Hajnal, Paul Aljabar, Giovanni Montana, 2017, Proceedings of the National Academy of Sciences.

Multimodal image analysis of clinical influences on preterm brain development

Paul Aljabar, Serena J. Counsell, Gareth Ball, 2017, Annals of neurology.

Development of cortical microstructure in the preterm human brain

Joseph V. Hajnal, Paul Aljabar, Serena J. Counsell, 2013, Proceedings of the National Academy of Sciences.

Longitudinal Regional Brain Development and Clinical Risk Factors in Extremely Preterm Infants.

Paul Aljabar, Antonios Makropoulos, Floris Groenendaal, 2016, The Journal of pediatrics.

Age dependent fetal MR segmentation using manual and automated approaches

Daniel Rueckert, Robin Wolz, Paul Aljabar, 2013 .

Microbubble Axial Localization Errors in Ultrasound Super-Resolution Imaging

Paul Aljabar, Sevan Harput, Robert J. Eckersley, 2017, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control.

Automatically determined hippocampal atrophy rates in ADNI: Their usability to discriminate between clinical groups and to detect changes in atrophy rate

Daniel Rueckert, Joseph V. Hajnal, Robin Wolz, 2010, Alzheimer's & Dementia.

The influence of preterm birth on the developing thalamocortical connectome

Daniel Rueckert, Paul Aljabar, Tomoki Arichi, 2013, Cortex.

Neonatal brain segmentation using second order neighborhood information

Paul Aljabar, Christian Ledig, Ahmed Serag, 2012 .

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

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

Segmentation of MRI brain scans using MALP-EM

Daniel Rueckert, Joseph V. Hajnal, Robin Wolz, 2012 .

SEGMENTATION OF SUBCORTICAL STRUCTURES IN BRAIN MRI USING GRAPH-CUTS AND SUBJECT-SPECIFIC APRIORI INFORMATION

Daniel Rueckert, Robin Wolz, Paul Aljabar, 2009 .

Autosegmentation for thoracic radiation treatment planning: A grand challenge at AAPM 2017

Paul Aljabar, Harini Veeraraghavan, Andre Dekker, 2018, Medical physics.

Early growth in brain volume is preserved in the majority of preterm infants

Daniel Rueckert, Paul Aljabar, Latha Srinivasan, 2007, Annals of neurology.

The Effect of Preterm Birth on Thalamic and Cortical Development

Daniel Rueckert, Paul Aljabar, Ioannis S. Gousias, 2011, Cerebral cortex.

Improving automatic delineation for head and neck organs at risk by Deep Learning Contouring.

Paul Aljabar, Charlotte L. Brouwer, Johannes A. Langendijk, 2019, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

Clinical evaluation of atlas and deep learning based automatic contouring for lung cancer.

Paul Aljabar, Andre Dekker, Devis Peressutti, 2017, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

Common Genetic Variants and Risk of Brain Injury After Preterm Birth

Daniel Rueckert, Paul Aljabar, Philippe Froguel, 2014, Pediatrics.