World's Best Scientists 2026 revealed!
Paul Suetens

Paul Suetens

D-Index & Metrics

Computer Science

D-Index
75
Citations
33621
World Ranking
1379
National Ranking
19

Medicine

D-Index
80
Citations
37428
World Ranking
16898
National Ranking
211

Overview

Paul Suetens is a researcher affiliated with KU Leuven in Belgium. Their work spans the intersection of medicine and computer science, with a particular focus on medical imaging and artificial intelligence applications.

Suetens has contributed to several research topics including:

  • COVID-19 diagnosis using AI
  • Radiomics and Machine Learning in Medical Imaging
  • Acute Ischemic Stroke Management
  • AI in cancer detection
  • COVID-19 Clinical Research Studies
  • Stroke Rehabilitation and Recovery
  • Venous Thromboembolism Diagnosis and Management

Their recent publications include the following papers:

  • "Prediction of Stroke Infarct Growth Rates by Baseline Perfusion Imaging," 2021, Stroke
  • "Theoretical analysis and experimental validation of volume bias of soft Dice optimized segmentation maps in the context of inherent uncertainty," 2020, Medical Image Analysis
  • "Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients," 2020, arXiv (Cornell University)
  • "Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients," 2020, Zenodo (CERN European Organization for Nuclear Research)
  • "Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging," 2022, Zenodo (CERN European Organization for Nuclear Research)

Frequent co-authors of Suetens include:

  • David Robben
  • Jeroen Bertels
  • Tom Eelbode
  • Frederik Maes
  • Dirk Vandermeulen

Common venues for their publications demonstrate a blend of clinical and technical domains, including:

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

The main fields of study to which Suetens has contributed are:

  • Medicine
  • Computer Science

Within these fields, subfields include:

  • Radiology, Nuclear Medicine and Imaging
  • Artificial Intelligence
  • Epidemiology
  • Computer Vision and Pattern Recognition
  • Pulmonary and Respiratory Medicine

Best Publications

  • Multimodality image registration by maximization of mutual information

    F. Maes;A. Collignon;D. Vandermeulen;G. Marchal

  • Automated multi-moda lity image registration based on information theory

    Andre M.F. Collignon;Frederik Maes;D. Delaere;Dirk Vandermeulen

  • Automated model-based tissue classification of MR images of the brain

    K. Van Leemput;F. Maes;D. Vandermeulen;P. Suetens

  • Regional Strain and Strain Rate Measurements by Cardiac Ultrasound: Principles, Implementation and Limitations

    Jan D'hooge;A. Heimdal;F. Jamal;Tomasz Kukulski

  • Comparison and Evaluation of Retrospective Intermodality Brain Image Registration Techniques

    West J;Fitzpatrick Jm;Wang My;Dawant Bm

  • Multi-modality image registration by maximization of mutual information

    F. Maes;A. Collignon;D. Vandermeulen;G. Marchal

  • Fundamentals of Medical Imaging

    Paul Suetens

  • Automated model-based bias field correction of MR images of the brain

    K. Van Leemput;F. Maes;D. Vandermeulen;P. Suetens

  • Comparison between effective radiation dose of CBCT and MSCT scanners for dentomaxillofacial applications.

    M. Loubele;R. Bogaerts;E. Van Dijck;R. Pauwels

  • Medical image registration using mutual information

    F. Maes;D. Vandermeulen;P. Suetens

  • Comparative evaluation of multiresolution optimization strategies for multimodality image registration by maximization of mutual information.

    Frederik Maes;Dirk Vandermeulen;Paul Suetens

  • Automated segmentation of multiple sclerosis lesions by model outlier detection

    K. Van Leemput;F. Maes;D. Vandermeulen;A. Colchester

  • An iterative maximum-likelihood polychromatic algorithm for CT

    B. De Man;J. Nuyts;P. Dupont;G. Marchal

  • State-of-the-art on cone beam CT imaging for preoperative planning of implant placement.

    Maria Eugenia Guerrero;Reinhilde Jacobs;Miet Loubele;Filip Schutyser

  • ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI

    Oskar Maier;Bjoern H. Menze;Janina von der Gablentz;Levin Häni

  • A custom template and definitive prosthesis allowing immediate implant loading in the maxilla: a clinical report.

    Daniel van Steenberghe;Ignace Naert;Matts Andersson;Izidor Brajnovic

  • Metal streak artifacts in X-ray computed tomography: a simulation study

    B. De Man;J. Nuyts;P. Dupont;G. Marchal

  • Comparison and evaluation of retrospective intermodality image registration techniques

    Jay B. West;J. Michael Fitzpatrick;Matthew Yang Wang;Benoit M. Dawant

  • 3D Multi-Modality Medical Image Registration Using Feature Space Clustering

    André Collignon;Dirk Vandermeulen;Paul Suetens;Guy Marchal

  • Automated multi-modality image registration based on information theory

    André Collignon;Frederik Maes;Dominique Delaere;Dirk Vandermeulen

  • Multi-modal volume registration by maximization of mutual information

    Frederik Maes;Andre M.F. Collignon;Dirk Vandermeulen;Guy Marchal

  • Clinical relevance of fully automated multimodality image registration by maximization of mutual information

    Frederik Maes;Dirk Vandermeulen;Guy Marchal;Paul Suetens

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 Computer Science in the USA opens the door to a diverse range of online degrees and certifications that boost your career prospects. Many students choose to complement their study with specialized programs in related fields, providing flexibility and value for money.

For those passionate about physics, consider an online theoretical physics degree. This offers a solid foundation in advanced science concepts and can be pursued at your own pace.

If you’re more interested in data and analytics, check out the cheapest data science masters in USA. This can help you enter high-demand roles in data engineering, AI, and machine learning.

For tech enthusiasts considering a broader engineering background, look at the online electrical engineering degree ranking to find reputable programs that align with your goals.

Lastly, kick-start your tech career quickly with easy certifications that pay well. These short-term credentials can provide a salary boost and are perfect for building essential skills in a competitive job market.

Best Scientists Citing Paul Suetens

Trending Scientists

Recently Published Articles