World's Best Scientists 2026 revealed!
Gwenole Quellec

Gwenole Quellec

D-Index & Metrics

Computer Science

D-Index
37
Citations
7463
World Ranking
10581
National Ranking
259

Gwenole Quellec 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 Gwenole Quellec 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: 156 publications — 29th percentile

29% of scientists in this discipline score the same or lower.

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

Gwenole Quellec 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 Gwenole Quellec 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: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Overview

Gwenole Quellec is affiliated with Inserm in France and specializes in research that intersects Medicine and Computer Science, with a particular focus on Radiology, Nuclear Medicine and Imaging, Ophthalmology, Artificial Intelligence, Computer Vision and Pattern Recognition, and Health Information Management.

Their research topics predominantly cover Retinal Imaging and Analysis, Retinal Diseases and Treatments, Retinal and Optic Conditions, Glaucoma and retinal disorders, AI applications in cancer detection, COVID-19 diagnosis using AI, and Radiomics and Machine Learning in Medical Imaging.

Several notable recent publications exemplify their contributions to the field. These include:

  • "Retinal Fundus Multi-Disease Image Dataset (RFMiD): A Dataset for Multi-Disease Detection Research," 2021, Data
  • "Automatic detection of rare pathologies in fundus photographs using few-shot learning," 2020, Medical Image Analysis
  • "A review of deep learning-based information fusion techniques for multimodal medical image classification," 2024, Computers in Biology and Medicine
  • "CaDIS: Cataract dataset for surgical RGB-image segmentation," 2021, Medical Image Analysis
  • "ExplAIn: Explanatory artificial intelligence for diabetic retinopathy diagnosis," 2021, Medical Image Analysis

Their work has been published in a variety of venues, with notable frequency in:

  • arXiv (Cornell University) - 19 publications
  • Scientific Reports - 6 publications
  • Medical Image Analysis - 5 publications
  • SSRN Electronic Journal - 4 publications
  • Computers in Biology and Medicine - 3 publications

Frequent co-authors collaborating with Gwenole Quellec include:

  • Mathieu Lamard
  • Béatrice Cochener
  • Pierre-Henri Conze
  • Mostafa El Habib Daho
  • Ramin Tadayoni

Best Publications

  • Retinopathy Online Challenge: Automatic Detection of Microaneurysms in Digital Color Fundus Photographs

    Meindert Niemeijer;Bram van Ginneken;Michael J Cree;Atsushi Mizutani

  • TeleOphta: Machine learning and image processing methods for teleophthalmology

    E. Decencière;G. Cazuguel;G. Cazuguel;X. Zhang;G. Thibault

  • Deep image mining for diabetic retinopathy screening.

    Gwenolé Quellec;Katia Charrière;Yassine Boudi;Béatrice Cochener

  • Automated Analysis of Retinal Images for Detection of Referable Diabetic Retinopathy

    Michael D. Abràmoff;James C. Folk;Dennis P. Han;Jonathan D. Walker

  • Optimal Wavelet Transform for the Detection of Microaneurysms in Retina Photographs

    G. Quellec;M. Lamard;P.M. Josselin;G. Cazuguel

  • Automated early detection of diabetic retinopathy.

    Michael D. Abràmoff;Michael D. Abràmoff;Michael D. Abràmoff;Joseph M. Reinhardt;Stephen R. Russell;Stephen R. Russell;James C. Folk;James C. Folk

  • IDRiD: Diabetic Retinopathy – Segmentation and Grading Challenge

    Prasanna Porwal;Prasanna Porwal;Samiksha Pachade;Manesh Kokare;Girish Deshmukh

  • Exudate detection in color retinal images for mass screening of diabetic retinopathy

    Xiwei Zhang;Guillaume Thibault;Etienne Decencière;Beatriz Marcotegui

  • Wavelet optimization for content-based image retrieval in medical databases.

    Gwénolé Quellec;Gwénolé Quellec;Mathieu Lamard;Mathieu Lamard;Guy Cazuguel;Guy Cazuguel;Béatrice Cochener;Béatrice Cochener

  • Multiple-Instance Learning for Medical Image and Video Analysis

    Gwenole Quellec;Guy Cazuguel;Beatrice Cochener;Mathieu Lamard

  • Three-Dimensional Analysis of Retinal Layer Texture: Identification of Fluid-Filled Regions in SD-OCT of the Macula

    Gwenole Quellec;Kyungmoo Lee;Martin Dolejsi;Mona K Garvin

  • Retinal Fundus Multi-Disease Image Dataset (RFMiD): A Dataset for Multi-Disease Detection Research

    Samiksha Pachade;Prasanna Porwal;Dhanshree Thulkar;Manesh Kokare

  • Validating retinal fundus image analysis algorithms: issues and a proposal.

    Emanuele Trucco;Alfredo Ruggeri;Thomas Karnowski;Luca Giancardo

  • Optimal Filter Framework for Automated, Instantaneous Detection of Lesions in Retinal Images

    Gwénolé Quellec;Stephen R Russell;Michael D Abràmoff

  • A multiple-instance learning framework for diabetic retinopathy screening

    Gwénolé Quellec;Mathieu Lamard;Mathieu Lamard;Michael D. Abràmoff;Etienne Decencière

  • Adaptive Nonseparable Wavelet Transform via Lifting and its Application to Content-Based Image Retrieval

    G. Quellec;M. Lamard;G. Cazuguel;B. Cochener

  • Fast Wavelet-Based Image Characterization for Highly Adaptive Image Retrieval

    G. Quellec;M. Lamard;G. Cazuguel;B. Cochener

  • CATARACTS: Challenge on automatic tool annotation for cataRACT surgery

    Hassan Al Hajj;Mathieu Lamard;Pierre-Henri Conze;Soumali Roychowdhury

  • Automatic detection of rare pathologies in fundus photographs using few-shot learning.

    Gwenolé Quellec;Mathieu Lamard;Pierre-Henri Conze;Pascale Massin

  • Multiple-Instance Learning for Anomaly Detection in Digital Mammography

    Gwenole Quellec;Mathieu Lamard;Michel Cozic;Gouenou Coatrieux

  • Content Based Image Retrieval based on Wavelet Transform coefficients distribution

    M. Lamard;G. Cazuguel;G. Quellec;L. Bekri

  • Iconography : TeleOphta: Machine learning and image processing methods for teleophthalmology

    E Decencière;G Cazuguel;X Zhang;G Thibault

Frequent Co-Authors

Mathieu Lamard
Mathieu Lamard University of Western Brittany
Christian Roux
Christian Roux Institut Mines-Télécom
Michael D. Abràmoff
Michael D. Abràmoff University of Iowa
Gouenou Coatrieux
Gouenou Coatrieux IMT Atlantique
Pascale Massin
Pascale Massin Université Paris Cité
Christian Roux
Christian Roux Université Paris Cité
Meindert Niemeijer
Meindert Niemeijer Digital Diagnostics Inc.
Danail Stoyanov
Danail Stoyanov University College London
Edwin M. Stone
Edwin M. Stone University of Iowa
Todd E. Scheetz
Todd E. Scheetz University of Iowa

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