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2025

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D-Index
48
Citations
10203
World Ranking
361
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3

Computer Science

D-Index
43
Citations
8104
World Ranking
7965
National Ranking
22

Michael Riegler 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 Michael Riegler 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: 330 publications — 79th percentile

79% of scientists in this discipline score the same or lower.

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

Michael Riegler 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 Michael Riegler 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: 43 D-Index — 46th percentile

46% 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

Michael Riegler is affiliated with OsloMet - Oslo Metropolitan University in Norway. Their research spans medicine and computer science, with a focus on subfields such as computer vision and pattern recognition, artificial intelligence, radiology, nuclear medicine and imaging, oncology, and public health, environmental and occupational health.

Their main research topics include radiomics and machine learning in medical imaging, colorectal cancer screening and detection, AI in cancer detection, reproductive biology and fertility, anomaly detection techniques and applications, artificial intelligence in healthcare and education, and gastric cancer management and outcomes.

Michael Riegler has published extensively, with frequent contributions to venues such as arXiv (Cornell University), Scientific Reports, IEEE Access, Human Reproduction, and Scientific Data.

  • arXiv (Cornell University)
  • Scientific Reports
  • IEEE Access
  • Human Reproduction
  • Scientific Data

Frequent co-authors include Pål Halvorsen, Steven A. Hicks, Vajira Thambawita, Hugo Lewi Hammer, and Debesh Jha.

  • Pål Halvorsen
  • Steven A. Hicks
  • Vajira Thambawita
  • Hugo Lewi Hammer
  • Debesh Jha

The scientist's recent papers include:

  • On evaluation metrics for medical applications of artificial intelligence, 2022, Scientific Reports
  • HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy, 2020, Scientific Data
  • Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning, 2021, IEEE Access
  • A Comprehensive Study on Colorectal Polyp Segmentation With ResUNet++, Conditional Random Field and Test-Time Augmentation, 2021, IEEE Journal of Biomedical and Health Informatics
  • Metrics reloaded: recommendations for image analysis validation, 2024, Nature Methods

Michael Riegler's work often intersects areas of cancer detection and medical image analysis using AI techniques, with a significant emphasis on colorectal and gastric cancer screening technologies.

Best Publications

  • ResUNet++: An Advanced Architecture for Medical Image Segmentation

    Debesh Jha;Pia H. Smedsrud;Michael A. Riegler;Dag Johansen

  • Kvasir-SEG: A Segmented Polyp Dataset

    Debesh Jha;Pia H. Smedsrud;Michael A. Riegler;Pål Halvorsen

  • DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation

    Debesh Jha;Michael A. Riegler;Dag Johansen;Pal Halvorsen

  • KVASIR: A Multi-Class Image Dataset for Computer Aided Gastrointestinal Disease Detection

    Konstantin Pogorelov;Kristin Ranheim Randel;Carsten Griwodz;Sigrun Losada Eskeland

  • HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy.

    Hanna Borgli;Vajira Thambawita;Pia H Smedsrud;Steven Hicks

  • Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning

    Debesh Jha;Sharib Ali;Nikhil Kumar Tomar;Havard D. Johansen

  • Mental health monitoring with multimodal sensing and machine learning: A survey

    Enrique Garcia-Ceja;Michael Riegler;Tine Nordgreen;Tine Nordgreen;Petter Jakobsen;Petter Jakobsen

  • A Comprehensive Study on Colorectal Polyp Segmentation With ResUNet++, Conditional Random Field and Test-Time Augmentation

    Debesh Jha;Pia H. Smedsrud;Dag Johansen;Thomas de Lange

  • Kvasir-Capsule, a video capsule endoscopy dataset.

    Pia H Smedsrud;Vajira Thambawita;Steven A Hicks;Henrik Gjestang

  • FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation.

    Nikhil Kumar Tomar;Debesh Jha;Michael A. Riegler;Håvard D. Johansen

  • Tiling in Interactive Panoramic Video: Approaches and Evaluation

    Vamsidhar Reddy Gaddam;Michael Riegler;Ragnhild Eg;Carsten Griwodz

  • Verifying Multimedia Use at MediaEval 2015

    Christina Boididou;Katerina Andreadou;Symeon Papadopoulos;Duc-Tien Dang-Nguyen

  • Natural disasters detection in social media and satellite imagery: a survey

    Naina Said;Kashif Ahmad;Michael Riegler;Konstantin Pogorelov

  • Impact of Image Resolution on Deep Learning Performance in Endoscopy Image Classification: An Experimental Study Using a Large Dataset of Endoscopic Images

    Vajira Thambawita;Inga Strümke;Steven A. Hicks;Pål Halvorsen

  • DDANet: Dual Decoder Attention Network for Automatic Polyp Segmentation

    Nikhil Kumar Tomar;Debesh Jha;Sharib Ali;Håvard D. Johansen

  • SinGAN-Seg: Synthetic Training Data Generation for Medical Image Segmentation

    Vajira Thambawita;Pegah Salehi;Sajad Amouei Sheshkal;Steven Alexander Hicks

  • ChaLearn Joint Contest on Multimedia Challenges Beyond Visual Analysis: An overview

    Hugo Jair Escalante;Victor Ponce-Lopez;Jun Wan;Michael A. Riegler

  • Comparing approaches to interactive lifelog search at the lifelog search challenge (LSC2018)

    Cathal Gurrin;Klaus Schoeffmann;Hideo Joho;Andreas Leibetseder

  • Depresjon: a motor activity database of depression episodes in unipolar and bipolar patients

    Enrique Garcia-Ceja;Michael Riegler;Petter Jakobsen;Jim Tørresen

  • ImageCLEF 2019: Multimedia Retrieval in Medicine, Lifelogging, Security and Nature

    Bogdan Ionescu;Henning Müller;Renaud Péteri;Yashin Dicente Cid

  • ResUNet++: An Advanced Architecture for Medical Image Segmentation

    Debesh Jha;Pia H. Smedsrud;Michael A. Riegler;Dag Johansen

  • DeepFake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine.

    Vajira Thambawita;Jonas L. Isaksen;Steven A. Hicks;Jonas Ghouse

  • Comparative validation of multi-instance instrument segmentation in endoscopy: Results of the ROBUST-MIS 2019 challenge

    Tobias Roß;Annika Reinke;Peter M. Full;Martin Wagner

  • Meta-learning with implicit gradients in a few-shot setting for medical image segmentation

    Unknown

  • Overview of ImageCLEF 2018: Challenges, Datasets and Evaluation

    Bogdan Ionescu;Henning Müller;Mauricio Villegas;Alba Garcia Seco de Herrera

  • Nerthus: A Bowel Preparation Quality Video Dataset

    Konstantin Pogorelov;Kristin Ranheim Randel;Thomas de Lange;Sigrun Losada Eskeland

  • On evaluation metrics for medical applications of artificial intelligence

    Steven A. Hicks;Inga Strümke;Vajira Thambawita;Malek Hammou

  • Verifying Multimedia Use at MediaEval 2016.

    Christina Boididou;Symeon Papadopoulos;Duc-Tien Dang-Nguyen;Giulia Boato

  • Kvasir-Instrument: Diagnostic and therapeutic tool segmentation dataset in gastrointestinal endoscopy

    Debesh Jha;Sharib Ali;Krister Emanuelsen;Steven A. Hicks

Frequent Co-Authors

Pål Halvorsen
Pål Halvorsen OsloMet – Oslo Metropolitan University
Dag Johansen
Dag Johansen University of Tromsø - The Arctic University of Norway
Carsten Griwodz
Carsten Griwodz University of Oslo
Cathal Gurrin
Cathal Gurrin Dublin City University
Martha Larson
Martha Larson Radboud University
Concetto Spampinato
Concetto Spampinato University of Catania
Jim Torresen
Jim Torresen University of Oslo
Ole Bernt Fasmer
Ole Bernt Fasmer University of Bergen
Henning Müller
Henning Müller University of Applied Sciences and Arts Western Switzerland
Niels Grarup
Niels Grarup University of Copenhagen

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