World's Best Scientists 2026 revealed!
Nico Karssemeijer

Nico Karssemeijer

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Computer Science
Netherlands
2025

D-Index & Metrics

Computer Science

D-Index
74
Citations
19950
World Ranking
1509
National Ranking
14

Nico Karssemeijer 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 Nico Karssemeijer 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 306 publications — 75th percentile

75% of scientists in this discipline score the same or lower.

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

Nico Karssemeijer 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 Nico Karssemeijer sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 74 D-Index — 90th percentile

90% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Computer Science in Netherlands Leader Award
  • 2022 - Research.com Computer Science in Netherlands Leader Award

Overview

Nico Karssemeijer is affiliated with Radboud University in the Netherlands and has an extensive research portfolio primarily focused on medical imaging, cancer detection, and artificial intelligence applications in healthcare. Their work spans multiple interdisciplinary fields, including medicine and computer science, with a strong emphasis on radiology and oncology.

Their main fields of study include:

  • Medicine
  • Computer Science

Within these broader fields, their research targets several subfields, notably:

  • Radiology, Nuclear Medicine and Imaging
  • Artificial Intelligence
  • Pulmonary and Respiratory Medicine
  • Oncology
  • Pathology and Forensic Medicine

Karssemeijer's published works cover key topics such as:

  • Radiomics and Machine Learning in Medical Imaging
  • AI in cancer detection
  • Digital Radiography and Breast Imaging
  • MRI in cancer diagnosis
  • Global Cancer Incidence and Screening
  • Breast Lesions and Carcinomas
  • Breast Cancer Treatment Studies

Among frequently published venues, the majority of their research appears in journals including:

  • Radiology
  • European Radiology
  • arXiv (Cornell University)
  • Insights into Imaging
  • European Journal of Surgical Oncology

Key recent publications include:

  • "Supplemental Breast MRI for Women with Extremely Dense Breasts: Results of the Second Screening Round of the DENSE Trial" (2021, Radiology)
  • "An Artificial Intelligence-based Mammography Screening Protocol for Breast Cancer: Outcome and Radiologist Workload" (2022, Radiology)
  • "Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case study" (2021, European Radiology)
  • "Interval Cancer Detection Using a Neural Network and Breast Density in Women with Negative Screening Mammograms" (2022, Radiology)
  • "Early Indicators of the Impact of Using AI in Mammography Screening for Breast Cancer" (2024, Radiology)

Karssemeijer regularly collaborates with several researchers, including:

  • Ritse M. Mann
  • Marc B. I. Lobbes
  • Carla H. van Gils
  • Jonas Teuwen
  • Stefanie G. A. Veenhuizen

Their contributions notably address screening protocols, the integration of artificial intelligence for improved diagnostic accuracy, and efforts to optimize radiologist workload in breast cancer detection. This work bridges clinical radiology and advanced computational methods, supporting innovations in early cancer diagnosis and medical imaging technologies.

Best Publications

  • Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer.

    Babak Ehteshami Bejnordi;Mitko Veta;Paul Johannes van Diest;Bram van Ginneken

  • Large scale deep learning for computer aided detection of mammographic lesions

    Thijs Kooi;Geert J. S. Litjens;Bram van Ginneken;Albert Gubern-Mérida

  • Computer-Aided Detection of Prostate Cancer in MRI

    Geert Litjens;Oscar Debats;Jelle Barentsz;Nico Karssemeijer

  • Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring

    Michiel Kallenberg;Kersten Petersen;Mads Nielsen;Andrew Y. Ng

  • Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks

    David Tellez;Maschenka Balkenhol;Irene Otte-Holler;Rob van de Loo

  • Detection of stellate distortions in mammograms

    N. Karssemeijer;G.M. te Brake

  • Automated classification of parenchymal patterns in mammograms

    N Karssemeijer

  • Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation

    Mohsen Ghafoorian;Mohsen Ghafoorian;Alireza Mehrtash;Alireza Mehrtash;Tina Kapur;Nico Karssemeijer

  • Stain Specific Standardization of Whole-Slide Histopathological Images

    Babak Ehteshami Bejnordi;Geert Litjens;Nadya Timofeeva;Irene Otte-Holler

  • Volumetric breast density estimation from full-field digital mammograms

    S. van Engeland;P.R. Snoeren;H. Huisman;C. Boetes

  • Robust breast composition measurement - Volpara™

    Ralph Highnam;Sir Michael Brady;Martin J. Yaffe;Nico Karssemeijer

  • Guest editorial computer-aided diagnosis in medical imaging

    M.L. Giger;N. Karssemeijer;S.G. Armato

  • Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities.

    Mohsen Ghafoorian;Nico Karssemeijer;Tom Heskes;Inge W. M. van Uden

  • Breast Image Analysis for Risk Assessment, Detection, Diagnosis, and Treatment of Cancer

    Maryellen L Giger;Nico Karssemeijer;Julia A Schnabel

  • A novel approach to contrast-enhanced breast magnetic resonance imaging for screening: high-resolution ultrafast dynamic imaging.

    Ritse M. Mann;Roel D. Mus;Jan van Zelst;Christian Geppert

  • A new 2D segmentation method based on dynamic programming applied to computer aided detection in mammography.

    Sheila Timp;Nico Karssemeijer

  • Using deep learning to segment breast and fibroglandular tissue in MRI volumes

    Mehmet Ufuk Dalmış;Geert Litjens;Katharina Holland;Arnaud Setio

  • ADAPTIVE NOISE EQUALIZATION AND RECOGNITION OF MICROCALCIFICATION CLUSTERS IN MAMMOGRAMS

    Nico Karssemeijer

  • Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies.

    Babak Ehteshami Bejnordi;Babak Ehteshami Bejnordi;Maeve Mullooly;Ruth M. Pfeiffer;Shaoqi Fan

  • Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images

    Babak Ehteshami Bejnordi;Guido C. A. Zuidhof;Maschenka Balkenhol;Meyke Hermsen

  • Single and multiscale detection of masses in digital mammograms

    G.M. te Brake;N. Karssemeijer

Frequent Co-Authors

Geert Litjens
Geert Litjens Radboud University
Bram van Ginneken
Bram van Ginneken Radboud University
Mads Nielsen
Mads Nielsen University of Copenhagen
Peter J. F. Lucas
Peter J. F. Lucas University of Twente
David J. Hawkes
David J. Hawkes University College London
Elena Marchiori
Elena Marchiori Radboud University
Tom Heskes
Tom Heskes Radboud University
Boudewijn P. F. Lelieveldt
Boudewijn P. F. Lelieveldt Leiden University Medical Center
Clara I. Sánchez
Clara I. Sánchez University of Amsterdam

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