World's Best Scientists 2026 revealed!
Frederik Maes

Frederik Maes

D-Index & Metrics

Computer Science

D-Index
60
Citations
26377
World Ranking
3161
National Ranking
29

Frederik Maes 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 Frederik Maes 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: 411 publications — 88th percentile

88% of scientists in this discipline score the same or lower.

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

Frederik Maes 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 Frederik Maes 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: 60 D-Index — 78th percentile

78% of scientists in this discipline score the same or lower.

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

Overview

Frederik Maes is affiliated with KU Leuven in Belgium and has a publication record focused primarily on Medicine, with a particular emphasis on Radiology, Nuclear Medicine and Imaging. Their research spans multiple subfields including Molecular Biology, Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine, and Oncology.

Their work extensively covers topics related to Radiomics and Machine Learning in Medical Imaging, Colorectal Cancer Screening and Detection, Advanced Neural Network Applications, and Advanced Radiotherapy Techniques. Other notable topics in their research portfolio include Muscle Physiology and Disorders, COVID-19 diagnosis using AI, and Advanced MRI Techniques and Applications.

Frederik Maes has contributed publications to a variety of scientific venues, frequently appearing in:

  • Endoscopy
  • Gastrointestinal Endoscopy
  • Radiotherapy and Oncology
  • Neuromuscular Disorders
  • arXiv (Cornell University)

Among the recent published papers linked to Frederik Maes, the following are noteworthy:

  • Optimization for Medical Image Segmentation: Theory and Practice When Evaluating With Dice Score or Jaccard Index (2020), IEEE Transactions on Medical Imaging
  • Lipid availability determines fate of skeletal progenitor cells via SOX9 (2020), Nature
  • Interobserver variability in organ at risk delineation in head and neck cancer (2021), Radiation Oncology
  • Artificial Intelligence Based Patient-Specific Preoperative Planning Algorithm for Total Knee Arthroplasty (2022), Frontiers in Robotics and AI
  • icobrain ms 5.1: Combining unsupervised and supervised approaches for improving the detection of multiple sclerosis lesions (2021), NeuroImage Clinical

Frederik Maes collaborates regularly with several researchers, including:

  • Tom Eelbode
  • Raf Bisschops
  • Pieter Sinonquel
  • Siri Willems
  • Kristl G. Claeys

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

  • 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

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

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

  • 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

  • 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

  • Comparison and evaluation of retrospective intermodality image registration techniques

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

  • Multi-modality image registration by maximization of mutual information

    Frederik Maes;Dirk Vandermeulen;Paul Suetens

  • A unifying framework for partial volume segmentation of brain MR images

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

  • Optimization for Medical Image Segmentation: Theory and Practice When Evaluating With Dice Score or Jaccard Index

    Tom Eelbode;Jeroen Bertels;Maxim Berman;Dirk Vandermeulen

  • Nonrigid Image Registration Using Conditional Mutual Information

    D. Loeckx;P. Slagmolen;F. Maes;D. Vandermeulen

  • A viscous fluid model for multimodal non-rigid image registration using mutual information

    Emiliano D'Agostino;Frederik Maes;Dirk Vandermeulen;Paul Suetens

  • Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory and Practice

    Jeroen Bertels;Tom Eelbode;Maxim Berman;Dirk Vandermeulen

  • Automatic 3-D segmentation of internal structures of the head in MR images using a combination of similarity and free-form transformations. I. Methodology and validation on normal subjects

    B.M. Dawant;S.L. Hartmann;J.-P. Thirion;F. Maes

  • Automatic segmentation and volumetry of multiple sclerosis brain lesions from MR images

    Saurabh Jain;Diana M. Sima;Annemie Ribbens;Melissa Cambron

  • 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

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