World's Best Scientists 2026 revealed!
Hayit Greenspan

Hayit Greenspan

D-Index & Metrics

Computer Science

D-Index
65
Citations
25681
World Ranking
2402
National Ranking
46

Hayit Greenspan 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 Hayit Greenspan 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: 263 publications — 66th percentile

66% of scientists in this discipline score the same or lower.

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

Hayit Greenspan 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 Hayit Greenspan 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: 65 D-Index — 83rd percentile

83% of scientists in this discipline score the same or lower.

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

Overview

Hayit Greenspan is affiliated with Tel Aviv University in Israel and has contributed extensively to research at the intersection of medicine and computer science, with a focus on radiology and artificial intelligence applications in healthcare.

The primary fields of study for Greenspan include Medicine and Computer Science. Their main subfields of expertise cover Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Cardiology and Cardiovascular Medicine, Computer Vision and Pattern Recognition, and Pulmonary and Respiratory Medicine.

The key research topics explored by Greenspan encompass:

  • Radiomics and Machine Learning in Medical Imaging
  • COVID-19 diagnosis using AI
  • AI in cancer detection
  • Artificial Intelligence in Healthcare and Education
  • Domain Adaptation and Few-Shot Learning
  • Venous Thromboembolism Diagnosis and Management
  • Lung Cancer Diagnosis and Treatment

Greenspan has published in a variety of scientific venues, frequently contributing to:

  • arXiv (Cornell University)
  • Scientific Reports
  • npj Digital Medicine
  • 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)
  • European Radiology

Some of the notable recent papers by Greenspan include:

  • "RadImageNet: An Open Radiologic Deep Learning Research Dataset for Effective Transfer Learning," 2022, Radiology Artificial Intelligence
  • "Evaluating White Matter Lesion Segmentations with Refined Sørensen-Dice Analysis," 2020, Scientific Reports
  • "An Adversarial Learning Approach to Medical Image Synthesis for Lesion Detection," 2020, IEEE Journal of Biomedical and Health Informatics
  • "Coronavirus Detection and Analysis on Chest CT with Deep Learning," 2020, arXiv (Cornell University)
  • "AAPM task group report 273: Recommendations on best practices for AI and machine learning for computer-aided diagnosis in medical imaging," 2022, Medical Physics

Hayit Greenspan has collaborated frequently with several coauthors including Noa Cahan, Jacob Goldberger, Eyal Klang, Yiftach Barash, and Eli Konen.

The researcher has also contributed to book publications, notably publishing "Multimodal Learning for Clinical Decision Support" in 2021 through Springer Science+Business Media.

Best Publications

  • Blobworld: image segmentation using expectation-maximization and its application to image querying

    C. Carson;S. Belongie;H. Greenspan;J. Malik

  • Guest Editorial Deep Learning in Medical Imaging: Overview and Future Promise of an Exciting New Technique

    Hayit Greenspan;Bram van Ginneken;Ronald M. Summers

  • GAN-based synthetic medical image augmentation for increased CNN performance in liver lesion classification

    Maayan Frid-Adar;Idit Diamant;Eyal Klang;Michal Amitai

  • A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies With Progress Highlights, and Future Promises

    S. Kevin Zhou;Hayit Greenspan;Christos Davatzikos;James S. Duncan

  • The Liver Tumor Segmentation Benchmark (LiTS)

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

  • Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

    M. Jorge Cardoso;Tal Arbel;Gustavo Carneiro;Tanveer Syeda-Mahmood

  • Synthetic data augmentation using GAN for improved liver lesion classification

    Maayan Frid-Adar;Eyal Klang;Michal Amitai;Jacob Goldberger

  • Color- and texture-based image segmentation using EM and its application to content-based image retrieval

    S. Belongie;C. Carson;H. Greenspan;J. Malik

  • Rapid AI Development Cycle for the Coronavirus (COVID-19) Pandemic: Initial Results for Automated Detection & Patient Monitoring using Deep Learning CT Image Analysis

    Ophir Gozes;Maayan Frid-Adar;Hayit Greenspan;Patrick D. Browning

  • Super-Resolution in Medical Imaging

    Hayit Greenspan

  • Convolutional Neural Networks for Radiologic Images: A Radiologist’s Guide

    Shelly Soffer;Avi Ben-Cohen;Orit Shimon;Michal Marianne Amitai

  • Content-Based Image Retrieval in Radiology: Current Status and Future Directions

    Ceyhun Burak Akgül;Daniel L. Rubin;Sandy Napel;Christopher F. Beaulieu

  • Region-based image querying

    C. Carson;S. Belongie;H. Greenspan;J. Malik

  • Image enhancement by nonlinear extrapolation in frequency space

    H. Greenspan;C.H. Anderson;S. Akber

  • Chest pathology detection using deep learning with non-medical training

    Yaniv Bar;Idit Diamant;Lior Wolf;Sivan Lieberman

  • Deep learning with non-medical training used for chest pathology identification

    Yaniv Bar;Idit Diamant;Lior Wolf;Hayit Greenspan

  • Longitudinal multiple sclerosis lesion segmentation: Resource and challenge.

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

  • MRI inter-slice reconstruction using super-resolution

    H. Greenspan;G. Oz;N. Kiryati;S. Peled

  • Constrained Gaussian mixture model framework for automatic segmentation of MR brain images

    H. Greenspan;A. Ruf;J. Goldberger

  • Overcomplete steerable pyramid filters and rotation invariance

    Unknown

  • An Efficient Image Similarity Measure Based on Approximations of KL-Divergence Between Two Gaussian Mixtures

    Jacob Goldberger;Shiri Gordon;Hayit Greenspan

Frequent Co-Authors

Jacob Goldberger
Jacob Goldberger Bar-Ilan University
Tanveer Syeda-Mahmood
Tanveer Syeda-Mahmood IBM (United States)
Serge Belongie
Serge Belongie University of Copenhagen
Nir Sochen
Nir Sochen Tel Aviv University
Jitendra Malik
Jitendra Malik University of California, Berkeley
Daniel L. Rubin
Daniel L. Rubin Stanford University
Anant Madabhushi
Anant Madabhushi Emory University
Bram van Ginneken
Bram van Ginneken Radboud University
Jerry L. Prince
Jerry L. Prince Johns Hopkins University
Nahum Kiryati
Nahum Kiryati Tel Aviv University

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