World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
9717
World Ranking
6450
National Ranking
104

Marleen de Bruijne publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Marleen de Bruijne sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 252 publications — 63rd percentile

63% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Marleen de Bruijne D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Marleen de Bruijne sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 47 D-Index — 56th percentile

56% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Marleen de Bruijne is affiliated with Erasmus University Rotterdam in the Netherlands. Their research integrates Medicine and Computer Science, reflecting a multidisciplinary approach that spans multiple subfields and topics.

The primary fields of study for de Bruijne include:

  • Medicine
  • Computer Science

Within these fields, de Bruijne's work focuses on subfields such as:

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

Central topics of their research include:

  • Medical Image Segmentation Techniques
  • Radiomics and Machine Learning in Medical Imaging
  • Lung Cancer Diagnosis and Treatment
  • COVID-19 diagnosis using AI
  • Advanced Neural Network Applications
  • Chronic Obstructive Pulmonary Disease (COPD) Research
  • Cerebrospinal fluid and hydrocephalus

De Bruijne has published extensively, contributing to journals and conferences that intersect medical imaging and computational methods. Frequent publication venues where de Bruijne's work appears include:

  • arXiv (Cornell University)
  • Medical Image Analysis
  • European Radiology
  • Zenodo (CERN European Organization for Nuclear Research)
  • Scientific Reports

Recent significant papers authored or co-authored by de Bruijne's research group illustrate key areas of interest and collaboration:

  • "FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare," 2025, BMJ
  • "Adversarial attack vulnerability of medical image analysis systems: Unexplored factors," 2021, Medical Image Analysis
  • "Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients," 2021, Scientific Reports
  • "An end-to-end approach to segmentation in medical images with CNN and posterior-CRF," 2021, Medical Image Analysis
  • "Determinants of Perivascular Spaces in the General Population," 2022, Neurology

The scientist collaborates frequently with a core group of co-authors, indicating ongoing partnerships in related research areas. Prominent co-authors include:

  • Florian Dubost
  • Harm A.W.M. Tiddens
  • Meike W. Vernooij
  • Robin Camarasa
  • Nicolas Padoy

De Bruijne has contributed to book publications with Springer Science+Business Media, particularly in the "Medical Image Computing and Computer Assisted Intervention - MICCAI 2021" series and "Information Processing in Medical Imaging" (2023). These works are indicative of their ongoing engagement with advancing computational techniques for medical imaging.

Best Publications

  • Not-so-supervised: A survey of semi-supervised, multi-instance, and transfer learning in medical image analysis

    Veronika Cheplygina;Marleen de Bruijne;Josien P.W. Pluim

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

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

  • Quantitative Analysis of Pulmonary Emphysema Using Local Binary Patterns

    Lauge Srensen;Saher B Shaker;Marleen de Bruijne

  • Machine learning approaches in medical image analysis: From detection to diagnosis

    Marleen de Bruijne

  • Extraction of Airways From CT (EXACT'09)

    Pechin Lo;Bram van Ginneken;Joseph M. Reinhardt;Tarunashree Yavarna

  • Transfer Learning Improves Supervised Image Segmentation Across Imaging Protocols

    Annegreet van Opbroek;M. Arfan Ikram;Meike W. Vernooij;Marleen de Bruijne

  • MRBrainS challenge: online evaluation framework for brain image segmentation in 3T MRI scans

    Adriënne M. Mendrik;Koen L. Vincken;Hugo J. Kuijf;Marcel Breeuwer

  • Gray Matter Age Prediction as a Biomarker for Risk of Dementia

    Johnny Wang;Johnny Wang;Maria J. Knol;Aleksei Tiulpin;Florian Dubost

  • 2D–3D shape reconstruction of the distal femur from stereo X-ray imaging using statistical shape models

    N. Baka;B.L. Kaptein;M. de Bruijne;M. de Bruijne;T. van Walsum

  • Adapting Active Shape Models for 3D segmentation of tubular structures in medical images.

    Marleen de Bruijne;Bram van Ginneken;Max A. Viergever;Wiro J. Niessen

  • Semi-supervised Medical Image Segmentation via Learning Consistency Under Transformations

    Gerda Bortsova;Florian Dubost;Laurens Hogeweg;Ioannis Katramados

  • Vessel-guided airway tree segmentation: A voxel classification approach

    Pechin Lo;Jon Sporring;Haseem Ashraf;Jesper Johannes Holst Pedersen

  • Combining Generative and Discriminative Representation Learning for Lung CT Analysis With Convolutional Restricted Boltzmann Machines

    Gijs van Tulder;Marleen de Bruijne

  • Scalable kernels for graphs with continuous attributes

    Aasa Feragen;Niklas Kasenburg;Jens Petersen;Marleen de Bruijne

  • Interactive segmentation of abdominal aortic aneurysms in CTA images

    Marleen de Bruijne;Bram van Ginneken;Max A Viergever;Wiro J Niessen

  • Multi-task Attention-Based Semi-supervised Learning for Medical Image Segmentation

    Shuai Chen;Gerda Bortsova;Antonio García-Uceda Juárez;Gijs van Tulder

  • A texton-based approach for the classification of lung parenchyma in CT images

    Mehrdad J. Gangeh;Lauge Sørensen;Saher B. Shaker;Mohamed S. Kamel

  • Texture-Based Analysis of COPD: A Data-Driven Approach

    L. Sorensen;M. Nielsen;Pechin Lo;H. Ashraf

  • Enlarged perivascular spaces in brain MRI: Automated quantification in four regions

    Florian Dubost;Pinar Yilmaz;Hieab Adams;Gerda Bortsova

  • Cystic fibrosis: Are volumetric ultra-low-dose expiratory CT scans sufficient for monitoring related lung disease?

    Martine Loeve;Maarten H. Lequin;Marleen de Bruijne;Ieneke J. C. Hartmann

  • Adversarial attack vulnerability of medical image analysis systems: Unexplored factors.

    Gerda Bortsova;Cristina González-Gonzalo;Suzanne C. Wetstein;Florian Dubost

  • Quantitative vertebral morphometry using neighbor-conditional shape models

    Marleen de Bruijne;Michael T. Lund;László B. Tankó;Paola C. Pettersen

Frequent Co-Authors

Wiro J. Niessen
Wiro J. Niessen University Medical Center Groningen
Meike W. Vernooij
Meike W. Vernooij Erasmus University Rotterdam
Mads Nielsen
Mads Nielsen University of Copenhagen
M. Arfan Ikram
M. Arfan Ikram Erasmus University Rotterdam
Aad van der Lugt
Aad van der Lugt Erasmus University Rotterdam
Stefan Klein
Stefan Klein Erasmus University Rotterdam
Bram van Ginneken
Bram van Ginneken Radboud University
Max A. Viergever
Max A. Viergever Utrecht University
Max Welling
Max Welling University of Amsterdam
Stephen M. Stick
Stephen M. Stick University of Western Australia

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