World's Best Scientists 2026 revealed!
Mattias P. Heinrich

Mattias P. Heinrich

D-Index & Metrics

Computer Science

D-Index
37
Citations
13495
World Ranking
10453
National Ranking
524

Mattias P. Heinrich 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 Mattias P. Heinrich 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: 214 publications — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Mattias P. Heinrich 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 Mattias P. Heinrich 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: 37 D-Index — 27th percentile

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

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

Overview

Mattias P. Heinrich is affiliated with the University of Lübeck in Germany. Their research spans multiple disciplines primarily focused on the intersection of medicine, computer science, and engineering.

The main fields of their work include:

  • Medicine
  • Computer Science
  • Engineering

Within these fields, Heinrich's work covers several subfields, such as:

  • Computer Vision and Pattern Recognition
  • Radiology, Nuclear Medicine and Imaging
  • Biomedical Engineering
  • Artificial Intelligence
  • Computational Mechanics

Their research topics reflect an emphasis on medical imaging and machine learning applications, including:

  • Medical Image Segmentation Techniques
  • Advanced Neural Network Applications
  • Medical Imaging and Analysis
  • Radiomics and Machine Learning in Medical Imaging
  • Medical Imaging Techniques and Applications
  • COVID-19 diagnosis using AI
  • 3D Shape Modeling and Analysis

Recent published papers authored or co-authored by Mattias P. Heinrich include:

  • "Non-invasive diagnosis of deep vein thrombosis from ultrasound imaging with machine learning," 2021, npj Digital Medicine
  • "GraphRegNet: Deep Graph Regularisation Networks on Sparse Keypoints for Dense Registration of 3D Lung CTs," 2021, IEEE Transactions on Medical Imaging
  • "Attention-augmented U-Net (AA-U-Net) for semantic segmentation," 2022, Signal Image and Video Processing
  • "Weakly-supervised learning of multi-modal features for regularised iterative descent in 3D image registration," 2020, Medical Image Analysis
  • "Dynamic deformable attention network (DDANet) for COVID-19 lesions semantic segmentation," 2021, Journal of Biomedical Informatics

Frequent co-authors collaborating with Heinrich include:

  • Lasse Hansen
  • Alexander Bigalke
  • Hanna Siebert
  • Christoph Großbröhmer
  • Ron Keuth

Their scientific contributions have been published regularly in various venues, with notable frequent publications including:

  • arXiv (Cornell University)
  • International Journal of Computer Assisted Radiology and Surgery
  • Sensors
  • Zenodo (CERN European Organization for Nuclear Research)
  • IEEE Transactions on Medical Imaging

In addition to articles, Heinrich has contributed to book publications, including a volume published by Springer Science+Business Media titled "Segmentation, Classification, and Registration of Multi-modality Medical Imaging Data" (2021).

Best Publications

  • Attention U-Net: Learning Where to Look for the Pancreas

    Ozan Oktay;Jo Schlemper;Loïc Le Folgoc;Matthew C. H. Lee

  • Attention gated networks: Learning to leverage salient regions in medical images.

    Jo Schlemper;Ozan Oktay;Michiel Schaap;Mattias P. Heinrich

  • Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and Segmentation

    Ozan Oktay;Enzo Ferrante;Konstantinos Kamnitsas;Mattias Heinrich

  • MIND: Modality independent neighbourhood descriptor for multi-modal deformable registration

    Mattias P. Heinrich;Mark Jenkinson;Manav Bhushan;Tahreema Matin

  • 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

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

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

  • MRF-Based Deformable Registration and Ventilation Estimation of Lung CT

    H. P. Heinrich;M. Jenkinson;M. Brady;J. A. Schnabel

  • Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation

    Ozan Oktay;Enzo Ferrante;Konstantinos Kamnitsas;Mattias Heinrich

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

    Xiahai Zhuang;Lei Li;Christian Payer;Darko Stern

  • Non-local shape descriptor: a new similarity metric for deformable multi-modal registration

    Mattias P. Heinrich;Mark Jenkinson;Manav Bhushan;Tahreema Matin

  • Evaluating fibre orientation dispersion in white matter: Comparison of diffusion MRI, histology and polarized light imaging.

    Jeroen Mollink;Jeroen Mollink;Michiel Kleinnijenhuis;Anne-Marie van Cappellen van Walsum;Stamatios N. Sotiropoulos;Stamatios N. Sotiropoulos

  • Towards Realtime Multimodal Fusion for Image-Guided Interventions Using Self-similarities.

    Mattias Paul Heinrich;Mark Jenkinson;Bartlomiej W. Papież;Sir Michael Brady

  • Cloud-Based Evaluation of Anatomical Structure Segmentation and Landmark Detection Algorithms: VISCERAL Anatomy Benchmarks

    Oscar Jimenez-del-Toro;Henning Muller;Markus Krenn;Katharina Gruenberg

  • ISLES 2016 and 2017-Benchmarking Ischemic Stroke Lesion Outcome Prediction Based on Multispectral MRI.

    Stefan Winzeck;Arsany Hakim;Richard McKinley;José A. A. D. S. R. Pinto

  • Evaluation of Six Registration Methods for the Human Abdomen on Clinically Acquired CT

    Zhoubing Xu;Christopher P. Lee;Mattias P. Heinrich;Marc Modat

  • Estimation of Large Motion in Lung CT by Integrating Regularized Keypoint Correspondences into Dense Deformable Registration

    Jan Ruhaak;Thomas Polzin;Stefan Heldmann;Ivor J. A. Simpson

  • An implicit sliding-motion preserving regularisation via bilateral filtering for deformable image registration

    Bartłomiej W. Papież;Mattias P. Heinrich;Jérome Fehrenbach;Laurent Risser

  • Deformable image registration by combining uncertainty estimates from supervoxel belief propagation

    Mattias P. Heinrich;Ivor J.A. Simpson;BartŁomiej W. Papież;Sir Michael Brady

  • Stratified Decision Forests for Accurate Anatomical Landmark Localization in Cardiac Images

    Ozan Oktay;Wenjia Bai;Ricardo Guerrero;Martin Rajchl

  • Residual U-Net Convolutional Neural Network Architecture for Low-Dose CT Denoising

    Mattias P. Heinrich;Maik Stille;Thorsten M. Buzug

  • Non-invasive diagnosis of deep vein thrombosis from ultrasound imaging with machine learning.

    Bernhard Kainz;Mattias P. Heinrich;Antonios Makropoulos;Jonas Oppenheimer

  • OBELISK-Net: Fewer layers to solve 3D multi-organ segmentation with sparse deformable convolutions.

    Mattias P. Heinrich;Ozan Oktay;Nassim Bouteldja

Frequent Co-Authors

Julia A. Schnabel
Julia A. Schnabel King's College London
Heinz Handels
Heinz Handels University of Lübeck
Ozan Oktay
Ozan Oktay Imperial College London
Mark Jenkinson
Mark Jenkinson University of Oxford
Bennett A. Landman
Bennett A. Landman Vanderbilt University
Ben Glocker
Ben Glocker Imperial College London
Daniel Rueckert
Daniel Rueckert Technical University of Munich
Bernhard Kainz
Bernhard Kainz Imperial College London
Sebastien Ourselin
Sebastien Ourselin King's College London
Marc Modat
Marc Modat King's College London

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