World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
48
Citations
11934
World Ranking
6091
National Ranking
126

Christian Barillot 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 Christian Barillot 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: 287 publications — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Christian Barillot 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 Christian Barillot 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: 48 D-Index — 58th percentile

58% of scientists in this discipline score the same or lower.

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

Overview

Christian Barillot is affiliated with the Institut de Recherche en Informatique et Systèmes Aléatoires in France. Their research primarily focuses on Medicine and Neuroscience, with significant contributions to the subfields of Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging, Orthopedics and Sports Medicine, Epidemiology, and Biomedical Engineering.

Their work covers several key topics including Functional Brain Connectivity Studies, Advanced Neuroimaging Techniques and Applications, EEG and Brain-Computer Interfaces, Advanced MRI Techniques and Applications, Bone and Joint Diseases, MRI in cancer diagnosis, as well as Neural dynamics and brain function.

Christian Barillot has authored multiple recent papers, notable among them are:

  • Multiple sclerosis lesions segmentation from multiple experts: The MICCAI 2016 challenge dataset (2021, NeuroImage)
  • A Survey on the Use of Haptic Feedback for Brain-Computer Interfaces and Neurofeedback (2020, Frontiers in Neuroscience)
  • Unsupervised Domain Adaptation With Optimal Transport in Multi-Site Segmentation of Multiple Sclerosis Lesions From MRI Data (2020, Frontiers in Computational Neuroscience)
  • A Multi-Target Motor Imagery Training Using Bimodal EEG-fMRI Neurofeedback: A Pilot Study in Chronic Stroke Patients (2020, Frontiers in Human Neuroscience)
  • Simultaneous EEG-fMRI during a neurofeedback task, a brain imaging dataset for multimodal data integration (2020, Scientific Data)

Frequent coauthors collaborating with Christian Barillot include Élise Bannier, Olivier Commowick, Anne Kerbrat, Jean-Christophe Ferré, and Mathis Fleury.

Their scholarly output has appeared mainly in journals such as Frontiers in Neuroscience, PLoS ONE, arXiv (Cornell University), bioRxiv (Cold Spring Harbor Laboratory), and Zenodo (CERN European Organization for Nuclear Research).

Best Publications

  • An Optimized Blockwise Nonlocal Means Denoising Filter for 3-D Magnetic Resonance Images

    P. Coupe;P. Yger;S. Prima;P. Hellier

  • Comparison and Evaluation of Retrospective Intermodality Brain Image Registration Techniques

    West J;Fitzpatrick Jm;Wang My;Dawant Bm

  • Nonlocal Means-Based Speckle Filtering for Ultrasound Images

    P. Coupe;P. Hellier;C. Kervrann;C. Barillot

  • Interactive display and analysis of 3-D medical images

    R.A. Robb;C. Barillot

  • Comparison and evaluation of retrospective intermodality image registration techniques

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

  • Longitudinal multiple sclerosis lesion segmentation: Resource and challenge.

    Aaron Carass;Snehashis Roy;Amod Jog;Jennifer L. Cuzzocreo

  • Rician Noise Removal by Non-Local Means Filtering for Low Signal-to-Noise Ratio MRI: Applications to DT-MRI

    Nicolas Wiest-Daesslé;Sylvain Prima;Pierrick Coupé;Sean Patrick Morrissey

  • Retrospective evaluation of intersubject brain registration

    P. Hellier;C. Barillot;I. Corouge;B. Gibaud

  • Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure

    Olivier Commowick;Audrey Istace;Michaël Kain;Baptiste Laurent

  • Fast non local means denoising for 3d MR images

    Pierrick Coupé;Pierre Yger;Christian Barillot

  • Segmentation of brain 3D MR images using level sets and dense registration.

    Caroline Baillard;Pierre Hellier;Christian Barillot

  • MRI-Based Automated Computer Classification of Probable AD Versus Normal Controls

    S. Duchesne;A. Caroli;C. Geroldi;C. Barillot

  • Automated extraction and variability analysis of sulcal neuroanatomy

    G. Le Goualher;E. Procyk;D.L. Collins;R. Venugopal

  • Coupling dense and landmark-based approaches for nonrigid registration

    P. Hellier;C. Barillot

  • Hierarchical estimation of a dense deformation field for 3-D robust registration

    P. Hellier;C. Barillot;E. Memin;P. Perez

  • The first MICCAI challenge on PET tumor segmentation.

    Mathieu Hatt;Baptiste Laurent;Anouar Ouahabi;Hadi Fayad

  • Multidimensional ultrasonic imaging for cardiology

    H.A. McCann;J.C. Sharp;T.M. Kinter;C.N. McEwan

  • Impact of Rician Adapted Non-Local Means Filtering on HARDI

    Maxime Descoteaux;Nicolas Wiest-Daesslé;Sylvain Prima;Christian Barillot

  • Bayesian non local means-based speckle filtering

    P. Coupe;P. Hellier;C. Kervrann;C. Barillot

  • 3D wavelet subbands mixing for image denoising

    Pierrick Coupé;Pierre Hellier;Sylvain Prima;Charles Kervrann

  • 17th International Conference on Medical Image Computing and Computer-Assisted Intervention

    Polina Golland;Nobuhiko Hata;Christian Barillot;Joachim Hornegger

Frequent Co-Authors

Olivier Commowick
Olivier Commowick French Institute for Research in Computer Science and Automation - INRIA
Anatole Lécuyer
Anatole Lécuyer French Institute for Research in Computer Science and Automation - INRIA
Pierrick Coupé
Pierrick Coupé University of Bordeaux
Simon K. Warfield
Simon K. Warfield Boston Children's Hospital
Michel Dojat
Michel Dojat French Institute for Research in Computer Science and Automation - INRIA
Jean-Philippe Ranjeva
Jean-Philippe Ranjeva Aix-Marseille University
Emmanuel J. Barbeau
Emmanuel J. Barbeau Centre national de la recherche scientifique, CNRS
Rémi Gribonval
Rémi Gribonval École Normale Supérieure de Lyon
Tristan Glatard
Tristan Glatard Concordia University
D. Louis Collins
D. Louis Collins McGill University

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