World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
60
Citations
24281
World Ranking
3167
National Ranking
188

Overview

Tom Vercauteren is affiliated with King's College London in the United Kingdom. Their work spans several fields of study, primarily Medicine, Computer Science, and Engineering. Within these areas, their research focuses on subfields such as Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Biomedical Engineering, Artificial Intelligence, and Pediatrics, Perinatology and Child Health.

The scientist has contributed extensively to topics including Medical Image Segmentation Techniques, Fetal and Pediatric Neurological Disorders, Photoacoustic and Ultrasonic Imaging, Radiomics and Machine Learning in Medical Imaging, Advanced Neural Network Applications, Domain Adaptation and Few-Shot Learning, and Optical Imaging and Spectroscopy Techniques.

Among recent publications are:

  • MONAI: An open-source framework for deep learning in healthcare (2022, arXiv (Cornell University))
  • MIDeepSeg: Minimally interactive segmentation of unseen objects from medical images using deep learning (2021, Medical Image Analysis)
  • Artificial intelligence and medical education: A global mixed-methods study of medical students' perspectives (2022, Digital Health)
  • Segmentation of vestibular schwannoma from MRI, an open annotated dataset and baseline algorithm (2021, Scientific Data)
  • MONAI Label: A framework for AI-assisted interactive labeling of 3D medical images (2024, Medical Image Analysis)

Frequent co-authors working with Tom Vercauteren include:

  • Sébastien Ourselin
  • Jonathan Shapey
  • Jan Deprest
  • Lucas Fidon
  • Reuben Dorent

The scientist's publications appear regularly in venues such as:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • International Journal of Computer Assisted Radiology and Surgery
  • Medical Image Analysis
  • bioRxiv (Cold Spring Harbor Laboratory)

Best Publications

  • Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration.

    Arno Klein;Jesper L. R. Andersson;Babak A. Ardekani;Babak A. Ardekani;John Ashburner

  • 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

  • Diffeomorphic demons: efficient non-parametric image registration.

    Tom Vercauteren;Xavier Pennec;Aymeric Perchant;Nicholas Ayache

  • 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

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

    Ran Gu;Guotai Wang;Tao Song;Rui Huang

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

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

  • 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

  • Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural Networks

    Guotai Wang;Wenqi Li;Sébastien Ourselin;Tom Vercauteren

  • Non-parametric diffeomorphic image registration with the demons algorithm

    Tom Vercauteren;Xavier Pennec;Aymeric Perchant;Nicholas Ayache

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

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

  • Symmetric Log-Domain Diffeomorphic Registration: A Demons-Based Approach

    Tom Vercauteren;Xavier Pennec;Aymeric Perchant;Nicholas Ayache

  • DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentation

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

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

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

  • Spherical Demons: Fast Diffeomorphic Landmark-Free Surface Registration

    B.T.T. Yeo;M.R. Sabuncu;T. Vercauteren;N. Ayache

  • On the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext Task

    Wenqi Li;Guotai Wang;Lucas Fidon;Sebastien Ourselin

  • An automated framework for localization, segmentation and super-resolution reconstruction of fetal brain MRI.

    Michael Ebner;Michael Ebner;Guotai Wang;Guotai Wang;Guotai Wang;Wenqi Li;Wenqi Li;Michael Aertsen

  • Automatic Brain Tumor Segmentation Based on Cascaded Convolutional Neural Networks With Uncertainty Estimation.

    Guotai Wang;Wenqi Li;Sébastien Ourselin;Tom Vercauteren

  • Decentralized sigma-point information filters for target tracking in collaborative sensor networks

    T. Vercauteren;Xiaodong Wang

  • Robust mosaicing with correction of motion distortions and tissue deformations for in vivo fibered microscopy.

    Tom Vercauteren;Aymeric Perchant;Grégoire Malandain;Xavier Pennec

Frequent Co-Authors

Sebastien Ourselin
Sebastien Ourselin King's College London
Danail Stoyanov
Danail Stoyanov University College London
Nicholas Ayache
Nicholas Ayache French Institute for Research in Computer Science and Automation - INRIA
Marc Modat
Marc Modat King's College London
Adrien E. Desjardins
Adrien E. Desjardins University College London
Dean C. Barratt
Dean C. Barratt University College London
Xavier Pennec
Xavier Pennec French Institute for Research in Computer Science and Automation - INRIA
J. Alison Noble
J. Alison Noble University of Oxford
Matthew J. Clarkson
Matthew J. Clarkson University College London
Grégoire Malandain
Grégoire Malandain French Institute for Research in Computer Science and Automation - INRIA

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 degree options in the USA offers flexibility and diverse pathways for computer science enthusiasts. Several programs cater to varying interests and career goals. If you’re looking to enter the workforce quickly, consider the quickest associates degree programs, which allow you to gain essential technical skills in less time.

For those passionate about tech leadership roles in academia or education, an ed.d educational leadership degree offers a deep dive into educational systems, opening doors to administrative and policy positions.

When selecting an institution, it’s important to choose from the nationally accredited online colleges to ensure program quality and credibility in the job market.

For creative minds attracted to gaming and interactive media, a game design online degree can jumpstart a career in this dynamic and fast-growing industry.

Best Scientists Citing Tom Vercauteren

Trending Scientists