World's Best Scientists 2026 revealed!
Award Badge
Computer Science
UK
2025

D-Index & Metrics

Computer Science

D-Index
104
Citations
55548
World Ranking
302
National Ranking
18

Medicine

D-Index
130
Citations
79585
World Ranking
2451
National Ranking
256

Research.com Recognitions

  • 2025 - Research.com Computer Science in United Kingdom Leader Award
  • 2023 - Research.com Computer Science in United Kingdom Leader Award
  • 2022 - Research.com Computer Science in United Kingdom Leader Award

Overview

Sebastien Ourselin is affiliated with King's College London in the United Kingdom and has a significant body of research in medicine and computer science. Their work spans multiple fields including Radiology, Nuclear Medicine and Imaging; Computer Vision and Pattern Recognition; Artificial Intelligence; Pediatrics, Perinatology and Child Health; and Biomedical Engineering.

The scientist's recent papers illustrate a focus on COVID-19 and medical imaging. Notable publications include:

  • "Attributes and predictors of long COVID" (2021) in Nature Medicine
  • "Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study" (2020) in The Lancet Public Health
  • "Real-time tracking of self-reported symptoms to predict potential COVID-19" (2020) in Nature Medicine
  • "Vaccine side-effects and SARS-CoV-2 infection after vaccination in users of the COVID Symptom Study app in the UK: a prospective observational study" (2021) in The Lancet Infectious Diseases
  • "The Medical Segmentation Decathlon" (2022) in Nature Communications

The scientist collaborates frequently with a range of coauthors, including:

  • Tom Vercauteren
  • M. Jorge Cardoso
  • Marc Modat
  • Claire J. Steves
  • Carole H. Sudre

Publications by Sebastien Ourselin appear regularly in several key venues, such as:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Medical Image Analysis
  • Scientific Reports
  • 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

The core topics addressed by their research include:

  • Fetal and Pediatric Neurological Disorders
  • Radiomics and Machine Learning in Medical Imaging
  • Long-Term Effects of COVID-19
  • COVID-19 Clinical Research Studies
  • Medical Image Segmentation Techniques
  • COVID-19 and Mental Health
  • Advanced Neuroimaging Techniques and Applications

Sebastien Ourselin's academic output reveals a commitment to the intersection of advanced computational methods and medical challenges, particularly in imaging and infectious disease research. The breadth of topics and frequent collaborations highlight a multidisciplinary approach within their scientific career.

Best Publications

  • The future of digital health with federated learning

    Nicola Rieke;Nicola Rieke;Jonny Hancox;Wenqi Li;Fausto Milletari

  • Generalised Dice overlap as a deep learning loss function for highly unbalanced segmentations

    Carole H. Sudre;Carole H. Sudre;Wenqi Li;Tom Vercauteren;Sebastien Ourselin;Sebastien Ourselin

  • Attributes and predictors of long COVID.

    Carole H. Sudre;Carole H. Sudre;Benjamin Murray;Thomas Varsavsky;Mark S. Graham

  • Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study.

    Long H. Nguyen;David A. Drew;Mark S. Graham;Amit D. Joshi

  • Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

    Spyridon Bakas;Mauricio Reyes;Andras Jakab;Stefan Bauer

  • Real-time tracking of self-reported symptoms to predict potential COVID-19.

    Cristina Menni;Ana M. Valdes;Ana M. Valdes;Maxim B. Freidin;Carole H. Sudre

  • Fast free-form deformation using graphics processing units

    Marc Modat;Gerard R. Ridgway;Zeike A. Taylor;Manja Lehmann

  • CA-Net: Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation

    Ran Gu;Guotai Wang;Tao Song;Rui Huang

  • The Medical Segmentation Decathlon

    Michela Antonelli;Annika Reinke;Spyridon Bakas;Keyvan Farahani

  • Vaccine side-effects and SARS-CoV-2 infection after vaccination in users of the COVID Symptom Study app in the UK: a prospective observational study.

    Cristina Menni;Kerstin Kläser;Anna C May;Lorenzo Polidori

  • Interactive Medical Image Segmentation Using Deep Learning With Image-Specific Fine Tuning

    Guotai Wang;Wenqi Li;Maria A. Zuluaga;Rosalind Pratt

  • Reconstructing a 3D structure from serial histological sections

    Sébastien Ourselin;Alexis Roche;Gérard Subsol;Xavier Pennec

  • Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007

    Nicholas Ayache;Sébastien Ourselin;Anthony Maeder

  • Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks.

    Guotai Wang;Guotai Wang;Guotai Wang;Wenqi Li;Wenqi Li;Michael Aertsen;Jan Deprest

  • NiftyNet: a deep-learning platform for medical imaging

    Eli Gibson;Wenqi Li;Carole H. Sudre;Lucas Fidon

  • Presymptomatic cognitive and neuroanatomical changes in genetic frontotemporal dementia in the Genetic Frontotemporal dementia Initiative (GENFI) study: a cross-sectional analysis

    Jonathan D Rohrer;Jennifer M Nicholas;Jennifer M Nicholas;David M Cash;John van Swieten

  • Head size, age and gender adjustment in MRI studies: a necessary nuisance?

    Josephine Barnes;Gerard R. Ridgway;Gerard R. Ridgway;Jonathan W. Bartlett;Susie M. D. Henley

  • Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

    Alexandra L Young;Razvan V Marinescu;Neil P Oxtoby;Martina Bocchetta

  • Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural Networks

    Guotai Wang;Wenqi Li;Sébastien Ourselin;Tom Vercauteren

  • Privacy-Preserving Federated Brain Tumour Segmentation

    Wenqi Li;Fausto Milletarì;Daguang Xu;Nicola Rieke

  • Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge

    K. Murphy;B. van Ginneken;J. M. Reinhardt;S. Kabus

  • Risk factors and disease profile of post-vaccination SARS-CoV-2 infection in UK users of the COVID Symptom Study app: a prospective, community-based, nested, case-control study.

    Michela Antonelli;Rose S Penfold;Jordi Merino;Carole H Sudre

  • Medical Imaging 2012: Image Processing

    David R. Haynor;Sébastien Ourselin

Frequent Co-Authors

Marc Modat
Marc Modat King's College London
Tom Vercauteren
Tom Vercauteren King's College London
Nick C. Fox
Nick C. Fox University College London
Brian Hutton
Brian Hutton Ottawa Hospital
John S. Duncan
John S. Duncan University College London
David Atkinson
David Atkinson University of Liverpool
Simon R. Arridge
Simon R. Arridge University College London
David J. Hawkes
David J. Hawkes University College London
Jan Deprest
Jan Deprest KU Leuven
Jonathan M. Schott
Jonathan M. Schott University College London

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online degrees has become increasingly popular among those looking to enter or advance in computer science careers. Many students now seek affordable online masters programs in areas like computer science, data analytics, or software engineering to boost their credentials without incurring major debt.

For those interested in leadership or research roles, pursuing an online phd leadership can open up opportunities in academic, technical, and managerial positions. These degrees are increasingly accessible via reputable online institutions.

Not everyone starts their journey at the graduate level, however. Some prospective students may opt for one of the easiest associate degree programs online as a fast entry point to the tech workforce. These can be a great way to gain foundational knowledge and skills quickly.

Additionally, those interested in educational leadership within computer science can consider the cheapest online edd programs as a cost-effective route to doctoral-level expertise in education.

Choosing the right online program depends on your career goals, budget, and desired pace of study. With a variety of flexible, affordable, and targeted pathways, there is an option for every aspiring computer science professional.

Best Scientists Citing Sebastien Ourselin

Trending Scientists

Recently Published Articles