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62
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143
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Computer Science

D-Index
62
Citations
40902
World Ranking
2818
National Ranking
127

Klaus H. Maier-Hein 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 Klaus H. Maier-Hein 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: 234 publications — 58th percentile

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

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

Klaus H. Maier-Hein 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 Klaus H. Maier-Hein 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: 62 D-Index — 80th percentile

80% 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 Rising Stars Award

Overview

Klaus H. Maier-Hein is affiliated with the German Cancer Research Center in Germany. Their research spans multiple domains within Medicine and Computer Science, with a particular emphasis on medical imaging and artificial intelligence applications in healthcare.

Their work covers significant subfields including Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine, and Biomedical Engineering.

Key topics explored in their publications encompass:

  • Radiomics and Machine Learning in Medical Imaging
  • AI in cancer detection
  • Advanced Neural Network Applications
  • COVID-19 diagnosis using AI
  • Artificial Intelligence in Healthcare and Education
  • Medical Imaging and Analysis
  • Medical Image Segmentation Techniques

Frequent co-authors collaborating with Klaus H. Maier-Hein include:

  • Fabian Isensee
  • Peter Neher
  • Paul F. Jäger
  • Michael Baumgartner
  • Jens Kleesiek

Publication venues with multiple works authored by Klaus H. Maier-Hein are:

  • arXiv (Cornell University)
  • Medical Image Analysis
  • Scientific Reports
  • Zenodo (CERN European Organization for Nuclear Research)
  • Nature Communications

Recent papers include:

  • "The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping", 2020, Radiology
  • "The Medical Segmentation Decathlon", 2022, Nature Communications
  • "The Liver Tumor Segmentation Benchmark (LiTS)", 2022, Medical Image Analysis
  • "CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation", 2020, Medical Image Analysis
  • "MONAI: An open-source framework for deep learning in healthcare", 2022, arXiv (Cornell University)

Klaus H. Maier-Hein has also contributed to several book publications with Springer Nature, including the series "Bildverarbeitung für die Medizin," with editions from 2020 through 2024.

Best Publications

  • Automated Design of Deep Learning Methods for Biomedical Image Segmentation

    Fabian Isensee;Paul F. Jäger;Simon A. A. Kohl;Jens Petersen

  • nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation

    Fabian Isensee;Fabian Isensee;Paul F Jaeger;Simon A A Kohl;Jens Petersen;Jens Petersen

  • The future of digital health with federated learning

    Nicola Rieke;Nicola Rieke;Jonny Hancox;Wenqi Li;Fausto Milletari

  • The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping

    Alex Zwanenburg;Alex Zwanenburg;Martin Vallières;Mahmoud A. Abdalah;Hugo J. W. L. Aerts;Hugo J. W. L. Aerts

  • Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?

    Olivier Bernard;Alain Lalande;Clement Zotti;Frederick Cervenansky

  • Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

    Spyridon Bakas;Mauricio Reyes;Andras Jakab;Stefan Bauer

  • The challenge of mapping the human connectome based on diffusion tractography

    Klaus H. Maier-Hein;Peter F. Neher;Jean-Christophe Houde;Marc-Alexandre Cote

  • CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation.

    A. Emre Kavur;N. Sinem Gezer;Mustafa Barış;Sinem Aslan

  • Automated brain extraction of multisequence MRI using artificial neural networks.

    Fabian Isensee;Marianne Schell;Irada Pflueger;Gianluca Brugnara

  • TractSeg - Fast and accurate white matter tract segmentation

    Jakob Wasserthal;Jakob Wasserthal;Peter F. Neher;Klaus H. Maier-Hein;Klaus H. Maier-Hein

  • Abstract: nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation

    Fabian Isensee;Jens Petersen;Andre Klein;David Zimmerer

  • Deep MRI brain extraction: A 3D convolutional neural network for skull stripping

    Jens Kleesiek;Gregor Urban;Alexander Hubert;Daniel Schwarz

  • ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI

    Oskar Maier;Bjoern H. Menze;Janina von der Gablentz;Levin Häni

  • Brain Tumor Segmentation and Radiomics Survival Prediction: Contribution to the BRATS 2017 Challenge

    Fabian Isensee;Philipp Kickingereder;Wolfgang Wick;Martin Bendszus

  • The Medical Imaging Interaction Toolkit: challenges and advances : 10 years of open-source development.

    Marco Nolden;Sascha Zelzer;Alexander Seitel;Diana Wald

  • Methodological considerations on tract-based spatial statistics (TBSS).

    Michael Bach;Frederik B. Laun;Alexander Leemans;Chantal M. W. Tax

  • The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge.

    Nicholas Heller;Fabian Isensee;Klaus H. Maier-Hein;Xiaoshuai Hou

  • Automated quantitative tumour response assessment of MRI in neuro-oncology with artificial neural networks: a multicentre, retrospective study.

    Philipp Kickingereder;Fabian Isensee;Irada Tursunova;Jens Petersen

  • nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation

    Fabian Isensee;Jens Petersen;Andre Klein;David Zimmerer

  • No New-Net

    Fabian Isensee;Philipp Kickingereder;Wolfgang Wick;Martin Bendszus

Frequent Co-Authors

Heinz-Peter Schlemmer
Heinz-Peter Schlemmer German Cancer Research Center
Martin Bendszus
Martin Bendszus University Hospital Heidelberg
Lena Maier-Hein
Lena Maier-Hein German Cancer Research Center
Wolfgang Wick
Wolfgang Wick German Cancer Research Center
Robert Christian Wolf
Robert Christian Wolf Heidelberg University
Sabine Heiland
Sabine Heiland University Hospital Heidelberg
Jürgen Debus
Jürgen Debus University Hospital Heidelberg
Maxime Descoteaux
Maxime Descoteaux Université de Sherbrooke
Stefanie Speidel
Stefanie Speidel National Center for Tumor Diseases
Bjoern H. Menze
Bjoern H. Menze University of Zurich

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