World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
60
Citations
13803
World Ranking
2179
National Ranking
147

Research.com Recognitions

  • 2008 - Fellow of the Royal Academy of Engineering (UK)

Overview

J. Alison Noble is affiliated with the University of Oxford in the United Kingdom. Their research spans the fields of Medicine and Computer Science, with a significant focus on Pediatrics, Perinatology and Child Health, as well as Artificial Intelligence and Computer Vision.

Their subfields of study include:

  • Pediatrics, Perinatology and Child Health
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Radiology, Nuclear Medicine and Imaging
  • Surgery

They have contributed to research in a range of main topics, including:

  • Fetal and Pediatric Neurological Disorders
  • Domain Adaptation and Few-Shot Learning
  • Multimodal Machine Learning Applications
  • Neonatal and fetal brain pathology
  • Prenatal Screening and Diagnostics
  • Artificial Intelligence in Healthcare and Education
  • Radiomics and Machine Learning in Medical Imaging

The scientist has authored important papers, among which are the following recent works:

  • "Introduction to artificial intelligence in ultrasound imaging in obstetrics and gynecology" (2020), published in Ultrasound in Obstetrics and Gynecology
  • "Achieving accurate estimates of fetal gestational age and personalised predictions of fetal growth based on data from an international prospective cohort study: a population-based machine learning study" (2020), published in The Lancet Digital Health
  • "Assistive artificial intelligence for ultrasound image interpretation in regional anaesthesia: an external validation study" (2022), published in British Journal of Anaesthesia
  • "Exploring the utility of assistive artificial intelligence for ultrasound scanning in regional anesthesia" (2022), published in Regional Anesthesia & Pain Medicine
  • "Transforming obstetric ultrasound into data science using eye tracking, voice recording, transducer motion and ultrasound video" (2021), published in Scientific Reports

Frequently publishing in venues such as:

  • arXiv (Cornell University)
  • Ultrasound in Obstetrics and Gynecology
  • Lecture notes in computer science
  • Medical Image Analysis
  • Journal of Crohn s and Colitis

J. Alison Noble has collaborated frequently with a group of coauthors, including:

  • Aris T. Papageorghiou
  • Lior Drukker
  • Divyanshu Mishra
  • Pramit Saha
  • Netzahualcoyotl Hernandez-Cruz

Their book publications are mainly with Springer Science+Business Media, comprising works such as:

  • "Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis" (2020)
  • "Medical Image Understanding and Analysis" (2020 and 2021 editions)
  • "Simplifying Medical Ultrasound" (2021 and 2022 editions)

They have been recognized with awards including the Fellow of the Royal Academy of Engineering (UK) in 2008.

Best Publications

  • International standards for fetal growth based on serial ultrasound measurements: the Fetal Growth Longitudinal Study of the INTERGROWTH-21st Project

    Aris T Papageorghiou;Eric O Ohuma;Eric O Ohuma;Douglas G Altman;Tullia Todros

  • Microscopy cell counting and detection with fully convolutional regression networks

    Weidi Xie;J. Alison Noble;Andrew Zisserman

  • Finding corners

    J. Alison Noble

  • Weakly-supervised convolutional neural networks for multimodal image registration.

    Yipeng Hu;Yipeng Hu;Marc Modat;Eli Gibson;Wenqi Li

  • Segmentation of ultrasound B-mode images with intensity inhomogeneity correction

    Guofang Xiao;M. Brady;J.A. Noble;Yongyue Zhang

  • Unified Image and Video Saliency Modeling

    Richard Droste;Jianbo Jiao;J. Alison Noble

  • An adaptive segmentation algorithm for time-of-flight MRA data

    D.L. Wilson;J.A. Noble

  • Learning to detect cells using non-overlapping extremal regions

    Carlos Arteta;Victor Lempitsky;J. Alison Noble;Andrew Zisserman

  • 2D+T acoustic boundary detection in echocardiography.

    Miguel Mulet-Parada;J.Alison Noble

  • Evaluation and Comparison of Current Fetal Ultrasound Image Segmentation Methods for Biometric Measurements: A Grand Challenge

    Sylvia Rueda;Sana Fathima;Caroline L. Knight;Mohammad Yaqub

  • Intensity-based 2-D - 3-D registration of cerebral angiograms

    J.H. Hipwell;G.P. Penney;R.A. McLaughlin;K. Rhode

  • Segmentation of ultrasound images: multiresolution 2D and 3D algorithm based on global and local statistics

    Djamal Boukerroui;Atilla Baskurt;J. Alison Noble;Olivier Basset

  • A shape-space-based approach to tracking myocardial borders and quantifying regional left-ventricular function applied in echocardiography

    G. Jacob;J.A. Noble;C. Behrenbruch;A.D. Kelion

  • A novel ultrasound indentation system for measuring biomechanical properties of in vivo soft tissue.

    Lianghao Han;J.Alison Noble;Michael Burcher

  • Interactive Object Counting

    Carlos Arteta;Victor S. Lempitsky;J. Alison Noble;Andrew Zisserman

  • On the Choice of Band-Pass Quadrature Filters

    Djamal Boukerroui;J. Alison Noble;Michael Brady

  • Random Forest Classification for Automatic Delineation of Myocardium in Real-Time 3D Echocardiography

    Victor Lempitsky;Michael Verhoek;J. Alison Noble;Andrew Blake

  • Registration of Multiview Real-Time 3-D Echocardiographic Sequences

    Unknown

  • Label-driven weakly-supervised learning for multimodal deformarle image registration

    Yipeng Hu;Marc Modat;Eli Gibson;Nooshin Ghavami

  • Ω-Net (Omega-Net): Fully automatic, multi-view cardiac MR detection, orientation, and segmentation with deep neural networks.

    Davis M. Vigneault;Davis M. Vigneault;Davis M. Vigneault;Weidi Xie;Carolyn Y. Ho;David A. Bluemke

  • Imaging techniques for cardiac strain and deformation: comparison of echocardiography, cardiac magnetic resonance and cardiac computed tomography

    Michael Tee;J Alison Noble;David A Bluemke

  • Velocity estimation in ultrasound images: a block matching approach.

    Djamal Boukerroui;Djamal Boukerroui;J. Alison Noble;Michael Brady

  • Statistical 3D Vessel Segmentation Using a Rician Distribution

    Albert C. S. Chung;J. Alison Noble

  • Fully-automated alignment of 3D fetal brain ultrasound to a canonical reference space using multi-task learning.

    Ana I.L. Namburete;Weidi Xie;Mohammad Yaqub;Andrew Zisserman

  • International Standards for Symphysis-Fundal Height Based on Serial Measurements From the Fetal Growth Longitudinal Study of the INTERGROWTH-21st Project: Prospective Cohort Study in Eight Countries

    Aris T Papageorghiou;Eric O Ohuma;Eric O Ohuma;Michael G Gravett;Jane Hirst

  • Local-phase based 3D boundary detection using monogenic signal and its application to real-time 3-D echocardiography images

    Kashif Rajpoot;Vicente Grau;J. Alison Noble

  • A comparison of a similarity-based and a feature-based 2-D-3-D registration method for neurointerventional use

    R.A. McLaughlin;J. Hipwell;D.J. Hawkes;J.A. Noble

Frequent Co-Authors

Aris T. Papageorghiou
Aris T. Papageorghiou University of Oxford
Stephen Kennedy
Stephen Kennedy University of Oxford
Weidi Xie
Weidi Xie University of Oxford
Michael Brady
Michael Brady University of Oxford
Andrew Zisserman
Andrew Zisserman University of Oxford
Fernando C. Barros
Fernando C. Barros Universidade Católica de Pelotas
Albert C. S. Chung
Albert C. S. Chung Hong Kong University of Science and Technology
David A. Bluemke
David A. Bluemke University of Wisconsin–Madison
David J. Hawkes
David J. Hawkes University College London
Tom Vercauteren
Tom Vercauteren King's College London

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