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Engineering and Technology
UK
2026

D-Index & Metrics

Engineering and Technology

D-Index
101
Citations
38025
World Ranking
140
National Ranking
9

Medicine

D-Index
106
Citations
41609
World Ranking
6536
National Ranking
631

Research.com Recognitions

  • 2026 - Research.com Engineering and Technology in United Kingdom Leader Award
  • 2020 - Fellow of the Royal Academy of Engineering (UK)

Overview

Joseph V. Hajnal is affiliated with King's College London in the United Kingdom. Their research primarily focuses on the field of Medicine, with significant contributions in subfields such as Radiology, Nuclear Medicine and Imaging, Pediatrics, Perinatology and Child Health, Cognitive Neuroscience, Epidemiology, and Biomedical Engineering.

The main topics covered in their work include:

  • Fetal and Pediatric Neurological Disorders
  • Advanced MRI Techniques and Applications
  • Neonatal and fetal brain pathology
  • Advanced Neuroimaging Techniques and Applications
  • Functional Brain Connectivity Studies
  • MRI in cancer diagnosis
  • Prenatal Screening and Diagnostics

Joseph V. Hajnal has published extensively in a range of scientific venues, with the most frequent publication outlets being:

  • Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Magnetic Resonance in Medicine
  • arXiv (Cornell University)
  • Medical Image Analysis

Among their recent papers are:

  • "A Novel Ultrasound Robot With Force/Torque Measurement and Control for Safe and Efficient Scanning" (2023) published in IEEE Transactions on Instrumentation and Measurement
  • "The Developing Human Connectome Project: typical and disrupted perinatal functional connectivity" (2021) published in Brain
  • "The developing Human Connectome Project (dHCP) automated resting-state functional processing framework for newborn infants" (2020) published in NeuroImage
  • "The Developing Human Connectome Project Neonatal Data Release" (2022) published in Frontiers in Neuroscience
  • "Development of human white matter pathways in utero over the second and third trimester" (2021) published in Proceedings of the National Academy of Sciences

Throughout their career, Joseph V. Hajnal has frequently collaborated with several co-authors including:

  • Mary Rutherford
  • Jana Hutter
  • A. David Edwards
  • Anthony N. Price
  • Lucilio Cordero-Grande

They have been recognized as a Fellow of the Royal Academy of Engineering in the United Kingdom since 2020.

Best Publications

  • Area V5 of the Human Brain: Evidence from a Combined Study Using Positron Emission Tomography and Magnetic Resonance Imaging

    J. D. G. Watson;R. Myers;R. S. J. Frackowiak;J. V. Hajnal

  • A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction

    Jo Schlemper;Jose Caballero;Joseph V. Hajnal;Anthony N. Price

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

    Paul Aljabar;Rolf A. Heckemann;Alexander Hammers;Joseph V. Hajnal

  • Automatic anatomical brain MRI segmentation combining label propagation and decision fusion.

    Rolf A. Heckemann;Joseph V. Hajnal;Paul Aljabar;Daniel Rueckert

  • Microstructured Magnetic Materials for RF Flux Guides in Magnetic Resonance Imaging

    M. C. K. Wiltshire;J. B. Pendry;I. R. Young;D. J. Larkman

  • Use of multicoil arrays for separation of signal from multiple slices simultaneously excited.

    David J. Larkman;Joseph V. Hajnal;Amy H. Herlihy;Glyn A. Coutts

  • Artifacts due to stimulus correlated motion in functional imaging of the brain

    Joseph V. Hajnal;Ralph Myers;Angela Oatridge;Jane E. Schwieso

  • Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction

    Chen Qin;Jo Schlemper;Jose Caballero;Anthony N. Price

  • The Developing Human Connectome Project: a Minimal Processing Pipeline for Neonatal Cortical Surface Reconstruction

    Antonios Makropoulos;Emma C. Robinson;Emma C. Robinson;Andreas Schuh;Robert Wright

  • Natural history of brain lesions in extremely preterm infants studied with serial magnetic resonance imaging from birth and neurodevelopmental assessment.

    Leigh E. Dyet;Nigel Kennea;Serena J. Counsell;Elia F. Maalouf

  • MR of the brain using fluid-attenuated inversion recovery (FLAIR) pulse sequences.

    B De Coene;J V Hajnal;P Gatehouse;D B Longmore

  • Use of fluid attenuated inversion recovery (FLAIR) pulse sequences in MRI of the brain

    Joseph V. Hajnal;David J. Bryant;Larry Kasuboski;Pradip M. Pattany

  • Reconstruction of fetal brain MRI with intensity matching and complete outlier removal.

    Maria Kuklisova-Murgasova;Gerardine Quaghebeur;Mary A. Rutherford;Joseph V. Hajnal

  • Abnormal Cortical Development after Premature Birth Shown by Altered Allometric Scaling of Brain Growth

    Olga Kapellou;Serena J Counsell;Nigel Kennea;Leigh Dyet

  • Diffusion-weighted imaging of the brain in preterm infants with focal and diffuse white matter abnormality.

    Serena J Counsell;Joanna M Allsop;Michael C Harrison;David J Larkman

  • DeepCut: Object Segmentation From Bounding Box Annotations Using Convolutional Neural Networks

    Martin Rajchl;Matthew C. H. Lee;Ozan Oktay;Konstantinos Kamnitsas

  • Diffeomorphic registration using b-splines

    Daniel Rueckert;Paul Aljabar;Rolf A. Heckemann;Joseph V. Hajnal

  • Automatic Whole Brain MRI Segmentation of the Developing Neonatal Brain

    Antonios Makropoulos;Ioannis S Gousias;Christian Ledig;Paul Aljabar

  • Magnetic resonance imaging of total body fat

    E.L. Thomas;N. Saeed;J.V. Hajnal;A.E. Brynes

  • A registration and interpolation procedure for subvoxel matching of serially acquired MR images.

    Joseph V. Hajnal;Nadeem Saeed;Elaine J. Soar;Angela Oatridge

  • A robust method to estimate the intracranial volume across MRI field strengths (1.5T and 3T)

    Shiva Keihaninejad;Rolf A. Heckemann;Gianlorenzo Fagiolo;Mark R. Symms

Frequent Co-Authors

Daniel Rueckert
Daniel Rueckert Technical University of Munich
Mary A. Rutherford
Mary A. Rutherford King's College London
Serena J. Counsell
Serena J. Counsell King's College London
A. David Edwards
A. David Edwards King's College London
Paul Aljabar
Paul Aljabar King's College London
Graeme M. Bydder
Graeme M. Bydder University of California, San Diego
Derek L. G. Hill
Derek L. G. Hill Panoramic Digital Health
Bernhard Kainz
Bernhard Kainz Imperial College London
Alexander Hammers
Alexander Hammers King's College London
Jonathan O'Muircheartaigh
Jonathan O'Muircheartaigh King's College London

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