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Ewert Bengtsson

Ewert Bengtsson

Ewert Bengtsson 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 Ewert Bengtsson 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+

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

Ewert Bengtsson 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 Ewert Bengtsson 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+

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

Research.com Recognitions

  • 2015 - IEEE Fellow For contributions to quantitative microscopy and biomedical image analysis

Overview

Ewert Bengtsson is a researcher affiliated with Uppsala University in Sweden focusing on applications of artificial intelligence within medicine, particularly in cancer diagnosis and medical imaging. Their work extensively covers AI in cancer detection and the usage of radiomics and machine learning techniques for medical image analysis, with a special emphasis on prostate cancer diagnosis and treatment.

The scientist's research spans multiple disciplines, including Medicine and Computer Science. Specific subfields of study engaged by Bengtsson include Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, and Pulmonary and Respiratory Medicine.

Recent academic contributions by Bengtsson include the following publications:

  • AI-based prostate analysis system trained without human supervision to predict patient outcome from tissue samples, 2022, Journal of Pathology Informatics
  • Difficulties and Recommendations for AI-Based Prediction of Prostate Cancer Aggressiveness in Digital Pathology, 2023, Medical Research Archives
  • Robust, credible, and interpretable AI-based histopathological prostate cancer grading, 2024, bioRxiv (Cold Spring Harbor Laboratory)
  • A systematic analysis of the impact of data variation on AI-based histopathological grading of prostate cancer, 2025, Medical Image Analysis

Bengtsson frequently collaborates with other researchers including Peter Walhagen, Maximilian Lennartz, Stefan Bonn, Guido Sauter, and Christer Busch. Their work has appeared in multiple publication venues such as the Journal of Pathology Informatics, Medical Research Archives, bioRxiv, and Medical Image Analysis.

Their research topics are consistently centered around:

  • AI in cancer detection
  • Radiomics and Machine Learning in Medical Imaging
  • Prostate Cancer Diagnosis and Treatment

In recognition of their contributions, Ewert Bengtsson was awarded the IEEE Fellow distinction in 2015 for work in quantitative microscopy and biomedical image analysis.

Best Publications

  • Combining intensity, edge and shape information for 2D and 3D segmentation of cell nuclei in tissue sections.

    Carolina Wählby;Ida-Maria Sintorn;Fredrik Erlandsson;Gunilla Borgefors

  • A Feature Set for Cytometry on Digitized Microscopic Images

    Karsten Rodenacker;Ewert Bengtsson

  • Algorithms for cytoplasm segmentation of fluorescence labelled cells.

    Carolina Wählby;Joakim Lindblad;Mikael Vondrus;Ewert Bengtsson

  • Screening for Cervical Cancer Using Automated Analysis of PAP-Smears

    Ewert Bengtsson;Patrik Malm

  • Cardiac glycosides and breast cancer.

    B. Stenkvist;E. Bengtsson;O. Eriksson;J. Holmquist

  • Computerized Nuclear Morphometry as an Objective Method for Characterizing Human Cancer Cell Populations

    Björn Stenkvist;Sighild Westman-Naeser;Jan Holmquist;Bo Nordin

  • Robust Cell Image Segmentation Methods

    Ewert Bengtsson;Carolina Wählby;Joakim Lindblad

  • Sequential immunofluorescence staining and image analysis for detection of large numbers of antigens in individual cell nuclei.

    Carolina Wählby;Fredrik Erlandsson;Ewert Bengtsson;Anders Zetterberg

  • Image analysis for automatic segmentation of cytoplasms and classification of Rac1 activation.

    Joakim Lindblad;Carolina Wählby;Ewert Bengtsson;Alla Zaltsman

  • Predicting breast cancer recurrence.

    Björn Stenkvist;Ewert Bengtsson;Ewert Bengtsson;Bengt Dahlqvist;Bengt Dahlqvist;Gunnar Eklund

  • Blind Color Decomposition of Histological Images

    Milan Gavrilovic;J. C. Azar;J. Lindblad;C. Wahlby

  • Principal component analysis of dynamic positron emission tomography images.

    F Pedersen;M Bergström;E Bengtsson;B Långström

  • CBA—an atlas-based software tool used to facilitate the interpretation of neuroimaging data

    Lennart Thurfjell;Lennart Thurfjell;Christian Bohm;Ewert Bengtsson

  • Noise correlation in PET, CT, SPECT and PET/CT data evaluated using autocorrelation function: a phantom study on data, reconstructed using FBP and OSEM

    Pasha Razifar;Mattias Sandström;Harald Schnieder;Bengt Långström

  • A new method for segmentation of colour images applied to immunohistochemically stained cell nuclei

    Petter Ranefall;Lars Egevad;Bo Nordin;Ewert Bengtsson

  • Image analysis based grading of bladder carcinoma. Comparison of object, texture and graph based methods and their reproducibility

    Heung‐Kook Choi;Torsten Jarkrans;Ewert Bengtsson;Janos Vasko

  • A new three-dimensional connected components labeling algorithm with simultaneous object feature extraction capability

    Lennart Thurfjell;Ewert Bengtsson;Bo Nordin

  • A Comparison of Methods for Estimation of Intensity Non-Uniformities in 2D and 3D Microscope Images of Fluorescence Stained Cells

    Joakim Lindblad;Ewert Bengtsson

  • Computer analysis of cervical cells. Automatic feature extraction and classification.

    Jan Holmquist;Ewert Bengtsson;Olle Eriksson;Bo Nordin

  • Computerized cell image analysis: past, present, and future

    Ewert Bengtsson

Frequent Co-Authors

Olle Eriksson
Olle Eriksson Uppsala University
Anders Björkman
Anders Björkman Karolinska Institute
Anders Zetterberg
Anders Zetterberg Karolinska Institute
Stuart Crozier
Stuart Crozier University of Queensland
Mats Nilsson
Mats Nilsson Swedish University of Agricultural Sciences
Mats Wahlgren
Mats Wahlgren Karolinska Institute
Kim H. Esbensen
Kim H. Esbensen Geological Survey of Denmark and Greenland
Hans Forssberg
Hans Forssberg Karolinska Institute
Elna-Marie Larsson
Elna-Marie Larsson Uppsala University
Ulf Gyllensten
Ulf Gyllensten Uppsala University

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