World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
8131
World Ranking
7574
National Ranking
452

Jens Rittscher 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 Jens Rittscher 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: 188 publications — 42nd percentile

42% of scientists in this discipline score the same or lower.

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

Jens Rittscher 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 Jens Rittscher 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: 44 D-Index — 48th percentile

48% of scientists in this discipline score the same or lower.

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

Overview

Jens Rittscher is affiliated with the University of Oxford in the United Kingdom. The scientific work focuses primarily on fields such as Medicine, Biochemistry, Genetics and Molecular Biology, and Computer Science. Subfields of study include Oncology, Artificial Intelligence, Molecular Biology, Radiology, Nuclear Medicine and Imaging, as well as Computer Vision and Pattern Recognition.

The research topics frequently covered include AI in cancer detection, Colorectal Cancer Screening and Detection, Radiomics and Machine Learning in Medical Imaging, Cell Image Analysis Techniques, Myeloproliferative Neoplasms: Diagnosis and Treatment, Digital Imaging for Blood Diseases, and Acute Myeloid Leukemia Research.

Recent significant publications authored or co-authored by Jens Rittscher are:

  • Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning (2021) published in IEEE Access
  • Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning (2020) published in Gut
  • FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation (2022) published in IEEE Transactions on Neural Networks and Learning Systems
  • Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy (2021) published in Medical Image Analysis
  • A deep learning framework for quality assessment and restoration in video endoscopy (2020) published in Medical Image Analysis

Frequently collaborating co-authors include Sharib Ali, Korsuk Sirinukunwattana, Clare Verrill, James E. East, and Alan Aberdeen.

Prominent publication venues in which Jens Rittscher often publishes include arXiv (Cornell University), bioRxiv (Cold Spring Harbor Laboratory), Medical Image Analysis, Blood, and Zenodo (CERN European Organization for Nuclear Research).

Best Publications

  • Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue

    Michael J. Gerdes;Christopher J. Sevinsky;Anup Sood;Sudeshna Adak

  • Shape and Appearance Context Modeling

    Xiaogang Wang;G. Doretto;T. Sebastian;J. Rittscher

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

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

  • A Probabilistic Background Model for Tracking

    Jens Rittscher;Jien Kato;Sébastien Joga;Andrew Blake

  • A multi-objective supplier selection model under stochastic demand conditions

    Zhiying Liao;Jens Rittscher

  • Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning

    Korsuk Sirinukunwattana;Enric Domingo;Susan D Richman;Keara L Redmond

  • Learning and classification of complex dynamics

    B. North;A. Blake;M. Isard;J. Rittscher

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

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

  • Appearance-based person reidentification in camera networks: problem overview and current approaches

    Gianfranco Doretto;Thomas Sebastian;Peter H. Tu;Jens Rittscher

  • Spatio-temporal cell cycle phase analysis using level sets and fast marching methods.

    Dirk R. Padfield;Dirk R. Padfield;Jens Rittscher;Nick Thomas;Badrinath Roysam

  • Simultaneous estimation of segmentation and shape

    J. Rittscher;P.H. Tu;N. Krahnstoever

  • Coupled minimum-cost flow cell tracking for high-throughput quantitative analysis

    Dirk R. Padfield;Dirk R. Padfield;Jens Rittscher;Badrinath Roysam

  • Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy.

    Sharib Ali;Mariia Dmitrieva;Noha M. Ghatwary;Sophia Bano

  • An HMM-based segmentation method for traffic monitoring movies

    J. Kato;T. Watanabe;S. Joga;J. Rittscher

  • Surveillance systems and methods

    Timothy Patrick Kelliher;Jens Rittscher;Peter Henry Tu;Kevin Chean

  • Detecting and counting people in surveillance applications

    X. Liu;P.H. Tu;J. Rittscher;A. Perera

  • Precision immunoprofiling by image analysis and artificial intelligence.

    Viktor H. Koelzer;Korsuk Sirinukunwattana;Jens Rittscher;Jens Rittscher;Kirsten D. Mertz

  • Integration of supplier selection, procurement lot sizing and carrier selection under dynamic demand conditions

    Zhiying Liao;Jens Rittscher

  • A deep learning framework for quality assessment and restoration in video endoscopy.

    Sharib Ali;Felix Zhou;Adam Bailey;Barbara Braden

  • An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy

    Sharib Ali;Felix Zhou;Barbara Braden;Adam Bailey

  • System and method for automatic person counting and detection of specific events

    Jens Rittscher;Peter Henry Tu;Nils Oliver Krahnstoever;Amitha Perera

Frequent Co-Authors

Peter Henry Tu
Peter Henry Tu General Electric (United States)
Andrew Blake
Andrew Blake University of Cambridge
Raghu Machiraju
Raghu Machiraju The Ohio State University
Xiaoming Liu
Xiaoming Liu University of North Carolina at Chapel Hill
Gustavo Leone
Gustavo Leone Medical University of South Carolina
Emad A. Rakha
Emad A. Rakha University of Nottingham
Badrinath Roysam
Badrinath Roysam University of Houston
Xin Lu
Xin Lu University of Oxford
Ian Tomlinson
Ian Tomlinson University of Oxford
Daniel St Johnston
Daniel St Johnston University of Cambridge

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