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Ivana Išgum
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Computer Science
Netherlands
2025

D-Index & Metrics

Computer Science

D-Index
52
Citations
14842
World Ranking
4994
National Ranking
72

Ivana Išgum 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 Ivana Išgum 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: 165 publications — 33rd percentile

33% of scientists in this discipline score the same or lower.

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

Ivana Išgum 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 Ivana Išgum 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: 52 D-Index — 65th percentile

65% 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 Computer Science in Netherlands Leader Award
  • 2022 - Research.com Computer Science in Netherlands Leader Award

Overview

Ivana Išgum is affiliated with the University of Amsterdam in the Netherlands and has a research focus largely centered on medical imaging, particularly in cardiology and radiology. Their work integrates advanced imaging techniques and machine learning applications to enhance diagnostic capabilities and risk stratification in cardiovascular diseases.

The primary fields of study covered by Ivana Išgum include Medicine, with a strong specialization in Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine, Biomedical Engineering, Surgery, and Pulmonary and Respiratory Medicine. These subfields reflect a multidisciplinary approach combining clinical and technological perspectives.

The main research topics addressed by Ivana Išgum encompass:

  • Cardiac Imaging and Diagnostics
  • Advanced X-ray and CT Imaging
  • Radiomics and Machine Learning in Medical Imaging
  • Coronary Interventions and Diagnostics
  • Medical Imaging Techniques and Applications
  • Medical Image Segmentation Techniques
  • Cardiovascular Function and Risk Factors

Ivana Išgum has contributed to multiple recent papers including:

  • Deep Learning for Automatic Calcium Scoring in CT: Validation Using Multiple Cardiac CT and Chest CT Protocols (2020), published in Radiology
  • Automated Assessment of COVID-19 Reporting and Data System and Chest CT Severity Scores in Patients Suspected of Having COVID-19 Using Artificial Intelligence (2020), published in Radiology
  • Multi-ancestry genome-wide study identifies effector genes and druggable pathways for coronary artery calcification (2023), published in Nature Genetics
  • Artificial Intelligence in Cardiovascular Imaging for Risk Stratification in Coronary Artery Disease (2021), published in Radiology Cardiothoracic Imaging
  • Clinical quantitative coronary artery stenosis and coronary atherosclerosis imaging: a Consensus Statement from the Quantitative Cardiovascular Imaging Study Group (2023), published in Nature Reviews Cardiology

Frequent collaborators include Bob D. de Vos, Sanne G. M. van Velzen, R. Nils Planken, Tim Leiner, and Bram van Ginneken, reflecting a network of co-authorship in cardiovascular imaging and biomedical research.

Ivana Išgum's publications are predominantly found in venues such as arXiv (Cornell University), Scientific Reports, Journal of Medical Imaging, Medical Image Analysis, and Journal of the American College of Cardiology. This distribution indicates engagement with both preprint repositories and peer-reviewed journals specializing in medical imaging and cardiovascular research.

Best Publications

  • Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?

    Olivier Bernard;Alain Lalande;Clement Zotti;Frederick Cervenansky

  • Generative Adversarial Networks for Noise Reduction in Low-Dose CT

    Jelmer M. Wolterink;Tim Leiner;Max A. Viergever;Ivana Isgum

  • Automatic Segmentation of MR Brain Images With a Convolutional Neural Network

    Pim Moeskops;Max A. Viergever;Adrienne M. Mendrik;Linda S. de Vries

  • A deep learning framework for unsupervised affine and deformable image registration

    Bob D. de Vos;Floris F. Berendsen;Max A. Viergever;Hessam Sokooti

  • Deep MR to CT synthesis using unpaired data

    Jelmer M. Wolterink;Anna M. Dinkla;Mark H. F. Savenije;Peter R. Seevinck

  • End-to-End Unsupervised Deformable Image Registration with a Convolutional Neural Network

    Bob D. de Vos;Floris F. Berendsen;Max A. Viergever;Marius Staring

  • Multi-Atlas-Based Segmentation With Local Decision Fusion—Application to Cardiac and Aortic Segmentation in CT Scans

    I. Isgum;M. Staring;A. Rutten;M. Prokop

  • Nonrigid image registration using multi-scale 3D convolutional neural networks

    Hessam Sokooti;Bob D. de Vos;Floris F. Berendsen;Boudewijn P. F. Lelieveldt;Boudewijn P. F. Lelieveldt

  • State-of-the-Art Deep Learning in Cardiovascular Image Analysis

    Geert Litjens;Francesco Ciompi;Jelmer M. Wolterink;Bob D. de Vos

  • Deep learning for multi-task medical image segmentation in multiple modalities

    Pim Moeskops;Pim Moeskops;Jelmer M. Wolterink;Bas H. M. van der Velden;Kenneth G. A. Gilhuijs

  • A Recurrent CNN for Automatic Detection and Classification of Coronary Artery Plaque and Stenosis in Coronary CT Angiography

    Majd Zreik;Robbert W. van Hamersvelt;Jelmer M. Wolterink;Tim Leiner

  • Automatic coronary artery calcium scoring in cardiac CT angiography using paired convolutional neural networks.

    Jelmer M. Wolterink;Tim Leiner;Bob D. de Vos;Robbert W. van Hamersvelt

  • Machine learning in cardiovascular magnetic resonance: basic concepts and applications

    Tim Leiner;Daniel Rueckert;Avan Suinesiaputra;Bettina Baeßler

  • Automatic Calcium Scoring in Low-Dose Chest CT Using Deep Neural Networks With Dilated Convolutions

    Nikolas Lessmann;Bram van Ginneken;Majd Zreik;Pim A. de Jong

  • Iterative fully convolutional neural networks for automatic vertebra segmentation and identification

    Nikolas Lessmann;Bram van Ginneken;Pim A. de Jong;Ivana Išgum

  • Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis

    Majd Zreik;Nikolas Lessmann;Robbert W. van Hamersvelt;Jelmer M. Wolterink

  • Adaptive local multi-atlas segmentation : Application to the heart and the caudate nucleus

    Eva M. van Rikxoort;Ivana Isgum;Yulia Arzhaeva;Marius Staring

  • Coronary artery centerline extraction in cardiac CT angiography using a CNN-based orientation classifier

    Jelmer M. Wolterink;Robbert W. van Hamersvelt;Max A. Viergever;Tim Leiner

  • Automatic Coronary Calcium Scoring in Low-Dose Chest Computed Tomography

    I. Isgum;M. Prokop;M. Niemeijer;M. A. Viergever

  • MR-Only Brain Radiation Therapy: Dosimetric Evaluation of Synthetic CTs Generated by a Dilated Convolutional Neural Network

    Anna M. Dinkla;Jelmer M. Wolterink;Matteo Maspero;Mark H.F. Savenije

  • Automated Assessment of COVID-19 Reporting and Data System and Chest CT Severity Scores in Patients Suspected of Having COVID-19 Using Artificial Intelligence

    Nikolas Lessmann;Clara I. Sánchez;Ludo Beenen;Luuk H. Boulogne

Frequent Co-Authors

Max A. Viergever
Max A. Viergever Utrecht University
Tim Leiner
Tim Leiner Utrecht University
Bram van Ginneken
Bram van Ginneken Radboud University
Mathias Prokop
Mathias Prokop Radboud University
Floris Groenendaal
Floris Groenendaal Utrecht University
Willem P.Th.M. Mali
Willem P.Th.M. Mali Utrecht University
Linda S. de Vries
Linda S. de Vries Utrecht University
Matthijs Oudkerk
Matthijs Oudkerk University of Groningen
Harry J. de Koning
Harry J. de Koning Erasmus University Rotterdam
Marius Staring
Marius Staring Leiden University Medical Center

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Best Scientists Citing Ivana Išgum

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Technical University of Munich

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King's College London

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Ge Wang

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Publications: 36

Ronald M. Summers

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National Institutes of Health

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Publications: 31

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Matthijs Oudkerk

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Publications: 30

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Josien P. W. Pluim

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Publications: 30

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