World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
7823
World Ranking
10565
National Ranking
420

Samuel Kadoury 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 Samuel Kadoury 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: 193 publications — 44th percentile

44% of scientists in this discipline score the same or lower.

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

Samuel Kadoury 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 Samuel Kadoury 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

Samuel Kadoury is affiliated with Polytechnique Montréal in Canada. Their research activities encompass multiple disciplines, primarily focusing on medicine and computer science. They have a significant publication record in specialized subfields including radiology, nuclear medicine and imaging, biomedical engineering, computer vision and pattern recognition, artificial intelligence, and pulmonary and respiratory medicine.

Their research work covers a variety of topics central to advancements in medical imaging and related technologies. These topics include:

  • Radiomics and Machine Learning in Medical Imaging
  • Advanced Radiotherapy Techniques
  • Medical Imaging and Analysis
  • Medical Imaging Techniques and Applications
  • Spectroscopy Techniques in Biomedical and Chemical Research
  • AI in cancer detection
  • Medical Image Segmentation Techniques

Kadoury has contributed to numerous recent papers. Notable publications include:

  • "Deep learning workflow in radiology: a primer", 2020, Insights into Imaging
  • "Deep Learning: An Update for Radiologists", 2021, Radiographics
  • "Overview of Machine Learning: Part 2", 2020, Neuroimaging Clinics of North America
  • "Identification of intraductal carcinoma of the prostate on tissue specimens using Raman micro-spectroscopy: A diagnostic accuracy case-control study with multicohort validation", 2020, PLoS Medicine
  • "Prediction of in-plane organ deformation during free-breathing radiotherapy via discriminative spatial transformer networks", 2020, Medical Image Analysis

Their frequent collaborators include William Le, An Tang, Liset Vázquez Romaguera, Cynthia Ménard, and Emmanuel Montagnon. These collaborations reflect a consistent partnership with researchers actively engaged in overlapping research domains.

Kadoury's research is often published in several leading venues related to medical imaging and computational analysis. The most frequent publication venues include:

  • arXiv (Cornell University)
  • Medical Image Analysis
  • Physics in Medicine and Biology
  • International Journal of Computer Assisted Radiology and Surgery
  • International Journal of Radiation Oncology*Biology*Physics

Best Publications

  • The Liver Tumor Segmentation Benchmark (LiTS)

    Patrick Bilic;Patrick Ferdinand Christ;Eugene Vorontsov;Grzegorz Chlebus

  • The Importance of Skip Connections in Biomedical Image Segmentation

    Michal Drozdzal;Eugene Vorontsov;Gabriel Chartrand;Samuel Kadoury

  • Deep Learning: A Primer for Radiologists

    Gabriel Chartrand;Phillip M Cheng;Eugene Vorontsov;Michal Drozdzal

  • Magnetic Resonance Imaging/Ultrasound Fusion Guided Prostate Biopsy Improves Cancer Detection Following Transrectal Ultrasound Biopsy and Correlates With Multiparametric Magnetic Resonance Imaging

    Peter A. Pinto;Paul H. Chung;Ardeshir R. Rastinehad;Angelo A. Baccala

  • Intravoxel incoherent motion MR imaging for prostate cancer: An evaluation of perfusion fraction and diffusion coefficient derived from different b-value combinations

    Yuxi Pang;Baris Turkbey;Marcelino Bernardo;Jochen Kruecker

  • Learning Normalized Inputs for Iterative Estimation in Medical Image Segmentation

    Michal Drozdzal;Michal Drozdzal;Gabriel Chartrand;Eugene Vorontsov;Mahsa Shakeri

  • Liver segmentation: indications, techniques and future directions.

    Akshat Gotra;Akshat Gotra;Lojan Sivakumaran;Gabriel Chartrand;Kim-Nhien Vu

  • Robust, accurate and fast automatic segmentation of the spinal cord.

    Benjamin De Leener;Samuel Kadoury;Julien Cohen-Adad;Julien Cohen-Adad

  • On orthogonality and learning recurrent networks with long term dependencies

    Eugene Vorontsov;Chiheb Trabelsi;Samuel Kadoury;Chris Pal

  • Multimodality image fusion-guided procedures: technique, accuracy, and applications.

    Nadine Abi-Jaoudeh;Jochen Kruecker;Samuel Kadoury;Hicham Kobeiter

  • Deep learning workflow in radiology: a primer.

    Emmanuel Montagnon;Milena Cerny;Alexandre Cadrin-Chênevert;Vincent Hamilton

  • The Importance of Skip Connections in Biomedical Image Segmentation

    Michal Drozdzal;Eugene Vorontsov;Gabriel Chartrand;Samuel Kadoury

  • Deep Learning: An Update for Radiologists.

    Phillip M Cheng;Emmanuel Montagnon;Rikiya Yamashita;Ian Pan

  • D'Amico risk stratification correlates with degree of suspicion of prostate cancer on multiparametric magnetic resonance imaging.

    Ardeshir R Rastinehad;Angelo A Baccala;Paul H Chung;Juan M Proano

  • Liver lesion segmentation informed by joint liver segmentation

    Eugene Vorontsov;An Tang;Chris Pal;Samuel Kadoury

  • Sub-cortical brain structure segmentation using F-CNN'S

    Mahsa Shaken;Stavros Tsogkas;Enzo Ferrante;Sarah Lippe

  • Deep Learning for Automated Segmentation of Liver Lesions at CT in Patients with Colorectal Cancer Liver Metastases

    Eugene Vorontsov;Milena Cerny;Philippe Régnier;Lisa Di Jorio

  • Real-time FDG PET Guidance during Biopsies and Radiofrequency Ablation Using Multimodality Fusion with Electromagnetic Navigation

    Aradhana M. Venkatesan;Samuel Kadoury;Nadine Abi-Jaoudeh;Elliot B. Levy

  • A versatile 3D reconstruction system of the spine and pelvis for clinical assessment of spinal deformities

    Samuel Kadoury;Farida Cheriet;Catherine Laporte;Hubert Labelle

  • Automatic Segmentation of the Spinal Cord and Spinal Canal Coupled With Vertebral Labeling

    Benjamin De Leener;Julien Cohen-Adad;Samuel Kadoury

  • Convolutional networks for kidney segmentation in contrast-enhanced CT scans

    William E. Thong;Samuel Kadoury;Nicolas Piché;Christopher J. Pal

  • A Novel System for the 3-D Reconstruction of the Human Spine and Rib Cage From Biplanar X-Ray Images

    F. Cheriet;C. Laporte;S. Kadoury;H. Labelle

  • On orthogonality and learning recurrent networks with long term dependencies

    Eugene Vorontsov;Chiheb Trabelsi;Samuel Kadoury;Chris Pal

  • Learning Normalized Inputs for Iterative Estimation in Medical Image Segmentation

    Michal Drozdzal;Gabriel Chartrand;Eugene Vorontsov;Lisa Di Jorio

Frequent Co-Authors

Hubert Labelle
Hubert Labelle University of Montreal
Raman Kashyap
Raman Kashyap Polytechnique Montréal
Nikos Paragios
Nikos Paragios CentraleSupélec
Chris Pal
Chris Pal Polytechnique Montréal
Bradford J. Wood
Bradford J. Wood National Institutes of Health
Sylvain Martel
Sylvain Martel Polytechnique Montréal
Peter A. Pinto
Peter A. Pinto National Institutes of Health
Iasonas Kokkinos
Iasonas Kokkinos University College London
Peter L. Choyke
Peter L. Choyke National Institutes of Health
Baris Turkbey
Baris Turkbey National Institutes of Health

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