World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
32
Citations
5961
World Ranking
12973
National Ranking
36

Martin Urschler 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 Martin Urschler 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: 150 publications — 27th percentile

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

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

Martin Urschler 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 Martin Urschler 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: 32 D-Index — 10th percentile

10% of scientists in this discipline score the same or lower.

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

Overview

Martin Urschler is affiliated with the University of Auckland in New Zealand. Their research spans multiple disciplines including medicine, computer science, and engineering.

The main fields of study in Urschler's work include:

  • Medicine
  • Computer Science
  • Engineering

Within these fields, Urschler has contributed to several subfields, notably:

  • Computer Vision and Pattern Recognition
  • Radiology, Nuclear Medicine and Imaging
  • Biomedical Engineering
  • Oral Surgery
  • Artificial Intelligence

Their research covers key topics such as:

  • Dental Radiography and Imaging
  • Medical Imaging and Analysis
  • Forensic Anthropology and Bioarchaeology Studies
  • Radiomics and Machine Learning in Medical Imaging
  • AI in cancer detection
  • Medical Image Segmentation Techniques
  • Advanced X-ray and CT Imaging

Urschler has published in several academic venues, including:

  • arXiv (Cornell University)
  • TUGraz OPEN Library (Graz University of Technology)
  • Medical Image Analysis
  • Journal of Food Measurement & Characterization
  • Bioengineering

Among recent papers authored or coauthored by Urschler are:

  • VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images, 2021, Medical Image Analysis
  • A Framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs, 2021, Medical Image Analysis
  • Generative Adversarial Network based Synthesis for Supervised Medical Image Segmentation, 2020, TUGraz OPEN Library (Graz University of Technology)
  • Wavelength and texture feature selection for hyperspectral imaging: a systematic literature review, 2023, Journal of Food Measurement & Characterization
  • Automated pneumothorax triaging in chest X-rays in the New Zealand population using deep-learning algorithms, 2022, Journal of Medical Imaging and Radiation Oncology

Frequent coauthors in Urschler's body of work include:

  • Darko Štern
  • Christian Payer
  • Franz Thaler
  • Gernot Plank
  • Matthias A. F. Gsell

Best Publications

  • Gland segmentation in colon histology images: The GlaS challenge contest

    Korsuk Sirinukunwattana;Josien P.W. Pluim;Hao Chen;Xiaojuan Qi

  • Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge

    K. Murphy;B. van Ginneken;J. M. Reinhardt;S. Kabus

  • Integrating spatial configuration into heatmap regression based CNNs for landmark localization.

    Christian Payer;Darko Štern;Horst Bischof;Martin Urschler

  • Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge

    Xiahai Zhuang;Lei Li;Christian Payer;Darko Stern

  • VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images

    Anjany Sekuboyina;Malek E. Husseini;Amirhossein Bayat;Maximilian Löffler

  • Saliency driven total variation segmentation

    Michael Donoser;Martin Urschler;Martin Hirzer;Horst Bischof

  • Regressing Heatmaps for Multiple Landmark Localization Using CNNs

    Christian Payer;Darko Štern;Horst Bischof;Martin Urschler

  • Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study

    Rina D. Rudyanto;Sjoerd Kerkstra;Eva M. van Rikxoort;Catalin Fetita

  • A Framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs.

    Karli Gillette;Matthias A.F. Gsell;Anton J. Prassl;Elias Karabelas;Elias Karabelas

  • Multi-label Whole Heart Segmentation Using CNNs and Anatomical Label Configurations

    Christian Payer;Darko Štern;Horst Bischof;Martin Urschler

  • A duality based algorithm for TV-L¹-optical-flow image registration

    Thomas Pock;Martin Urschler;Christopher Zach;Reinhard Beichel

  • A multi-center milestone study of clinical vertebral CT segmentation

    Jianhua Yao;Joseph E. Burns;Daniel Forsberg;Alexander Seitel

  • Segmentation and classification of colon glands with deep convolutional neural networks and total variation regularization

    Philipp Kainz;Philipp Kainz;Michael Pfeiffer;Martin Urschler

  • You Should Use Regression to Detect Cells

    Philipp Kainz;Martin Urschler;Samuel Schulter;Paul Wohlhart

  • Coarse to Fine Vertebrae Localization and Segmentation with SpatialConfiguration-Net and U-Net.

    Christian Payer;Darko Stern;Horst Bischof;Martin Urschler

  • Instance Segmentation and Tracking with Cosine Embeddings and Recurrent Hourglass Networks

    Christian Payer;Darko Štern;Thomas Neff;Horst Bischof

  • Evaluation and comparison of 3D intervertebral disc localization and segmentation methods for 3D T2 MR data: A grand challenge.

    Guoyan Zheng;Chengwen Chu;Daniel L. Belavý;Daniel L. Belavý;Bulat Ibragimov

  • Integrating geometric configuration and appearance information into a unified framework for anatomical landmark localization

    Martin Urschler;Thomas Ebner;Darko Štern

  • Towards Automatic Bone Age Estimation from MRI: Localization of 3D Anatomical Landmarks

    Thomas Ebner;Darko Stern;Rene Donner;Horst Bischof

  • Automatic Age Estimation and Majority Age Classification From Multi-Factorial MRI Data

    Darko Stern;Christian Payer;Nicola Giuliani;Martin Urschler

  • SIFT and shape context for feature-based nonlinear registration of thoracic CT images

    Martin Urschler;Joachim Bauer;Hendrik Ditt;Horst Bischof

  • Vertebrae Localization and Segmentation with SpatialConfiguration-Net and U-Net

    Christian Payer;Darko Stern;Horst Bischof;Martin Urschler

Frequent Co-Authors

Horst Bischof
Horst Bischof Graz University of Technology
Horst Olschewski
Horst Olschewski Medical University of Graz
Thomas Pock
Thomas Pock Graz University of Technology
Michael Pfeiffer
Michael Pfeiffer Bosch Center for Artificial Intelligence
Pheng-Ann Heng
Pheng-Ann Heng Chinese University of Hong Kong
Gabor G. Kovacs
Gabor G. Kovacs University of Toronto
Sebastien Ourselin
Sebastien Ourselin King's College London
Ben Glocker
Ben Glocker Imperial College London
Josien P. W. Pluim
Josien P. W. Pluim Eindhoven University of Technology
Dieter Schmalstieg
Dieter Schmalstieg University of Stuttgart

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