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Computer Science

D-Index
47
Citations
9717
World Ranking
6449
National Ranking
104

Overview

Marleen de Bruijne is affiliated with Erasmus University Rotterdam in the Netherlands. Their research integrates Medicine and Computer Science, reflecting a multidisciplinary approach that spans multiple subfields and topics.

The primary fields of study for de Bruijne include:

  • Medicine
  • Computer Science

Within these fields, de Bruijne's work focuses on subfields such as:

  • Radiology, Nuclear Medicine and Imaging
  • Pulmonary and Respiratory Medicine
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Biomedical Engineering

Central topics of their research include:

  • Medical Image Segmentation Techniques
  • Radiomics and Machine Learning in Medical Imaging
  • Lung Cancer Diagnosis and Treatment
  • COVID-19 diagnosis using AI
  • Advanced Neural Network Applications
  • Chronic Obstructive Pulmonary Disease (COPD) Research
  • Cerebrospinal fluid and hydrocephalus

De Bruijne has published extensively, contributing to journals and conferences that intersect medical imaging and computational methods. Frequent publication venues where de Bruijne's work appears include:

  • arXiv (Cornell University)
  • Medical Image Analysis
  • European Radiology
  • Zenodo (CERN European Organization for Nuclear Research)
  • Scientific Reports

Recent significant papers authored or co-authored by de Bruijne's research group illustrate key areas of interest and collaboration:

  • "FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare," 2025, BMJ
  • "Adversarial attack vulnerability of medical image analysis systems: Unexplored factors," 2021, Medical Image Analysis
  • "Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients," 2021, Scientific Reports
  • "An end-to-end approach to segmentation in medical images with CNN and posterior-CRF," 2021, Medical Image Analysis
  • "Determinants of Perivascular Spaces in the General Population," 2022, Neurology

The scientist collaborates frequently with a core group of co-authors, indicating ongoing partnerships in related research areas. Prominent co-authors include:

  • Florian Dubost
  • Harm A.W.M. Tiddens
  • Meike W. Vernooij
  • Robin Camarasa
  • Nicolas Padoy

De Bruijne has contributed to book publications with Springer Science+Business Media, particularly in the "Medical Image Computing and Computer Assisted Intervention - MICCAI 2021" series and "Information Processing in Medical Imaging" (2023). These works are indicative of their ongoing engagement with advancing computational techniques for medical imaging.

Best Publications

  • Not-so-supervised: A survey of semi-supervised, multi-instance, and transfer learning in medical image analysis

    Veronika Cheplygina;Marleen de Bruijne;Josien P.W. Pluim

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

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

  • Quantitative Analysis of Pulmonary Emphysema Using Local Binary Patterns

    Lauge Srensen;Saher B Shaker;Marleen de Bruijne

  • Machine learning approaches in medical image analysis: From detection to diagnosis

    Marleen de Bruijne

  • Extraction of Airways From CT (EXACT'09)

    Pechin Lo;Bram van Ginneken;Joseph M. Reinhardt;Tarunashree Yavarna

  • Transfer Learning Improves Supervised Image Segmentation Across Imaging Protocols

    Annegreet van Opbroek;M. Arfan Ikram;Meike W. Vernooij;Marleen de Bruijne

  • MRBrainS challenge: online evaluation framework for brain image segmentation in 3T MRI scans

    Adriënne M. Mendrik;Koen L. Vincken;Hugo J. Kuijf;Marcel Breeuwer

  • Gray Matter Age Prediction as a Biomarker for Risk of Dementia

    Johnny Wang;Johnny Wang;Maria J. Knol;Aleksei Tiulpin;Florian Dubost

  • 2D–3D shape reconstruction of the distal femur from stereo X-ray imaging using statistical shape models

    N. Baka;B.L. Kaptein;M. de Bruijne;M. de Bruijne;T. van Walsum

  • Adapting Active Shape Models for 3D segmentation of tubular structures in medical images.

    Marleen de Bruijne;Bram van Ginneken;Max A. Viergever;Wiro J. Niessen

  • Semi-supervised Medical Image Segmentation via Learning Consistency Under Transformations

    Gerda Bortsova;Florian Dubost;Laurens Hogeweg;Ioannis Katramados

  • Vessel-guided airway tree segmentation: A voxel classification approach

    Pechin Lo;Jon Sporring;Haseem Ashraf;Jesper Johannes Holst Pedersen

  • Combining Generative and Discriminative Representation Learning for Lung CT Analysis With Convolutional Restricted Boltzmann Machines

    Gijs van Tulder;Marleen de Bruijne

  • Scalable kernels for graphs with continuous attributes

    Aasa Feragen;Niklas Kasenburg;Jens Petersen;Marleen de Bruijne

  • Interactive segmentation of abdominal aortic aneurysms in CTA images

    Marleen de Bruijne;Bram van Ginneken;Max A Viergever;Wiro J Niessen

  • Multi-task Attention-Based Semi-supervised Learning for Medical Image Segmentation

    Shuai Chen;Gerda Bortsova;Antonio García-Uceda Juárez;Gijs van Tulder

  • A texton-based approach for the classification of lung parenchyma in CT images

    Mehrdad J. Gangeh;Lauge Sørensen;Saher B. Shaker;Mohamed S. Kamel

  • Texture-Based Analysis of COPD: A Data-Driven Approach

    L. Sorensen;M. Nielsen;Pechin Lo;H. Ashraf

  • Enlarged perivascular spaces in brain MRI: Automated quantification in four regions

    Florian Dubost;Pinar Yilmaz;Hieab Adams;Gerda Bortsova

  • Cystic fibrosis: Are volumetric ultra-low-dose expiratory CT scans sufficient for monitoring related lung disease?

    Martine Loeve;Maarten H. Lequin;Marleen de Bruijne;Ieneke J. C. Hartmann

  • Adversarial attack vulnerability of medical image analysis systems: Unexplored factors.

    Gerda Bortsova;Cristina González-Gonzalo;Suzanne C. Wetstein;Florian Dubost

  • Quantitative vertebral morphometry using neighbor-conditional shape models

    Marleen de Bruijne;Michael T. Lund;László B. Tankó;Paola C. Pettersen

Frequent Co-Authors

Wiro J. Niessen
Wiro J. Niessen Erasmus University Rotterdam
Meike W. Vernooij
Meike W. Vernooij Erasmus University Rotterdam
Mads Nielsen
Mads Nielsen University of Copenhagen
Stefan Klein
Stefan Klein Erasmus University Rotterdam
Bram van Ginneken
Bram van Ginneken Radboud University
Max A. Viergever
Max A. Viergever Utrecht University
Max Welling
Max Welling University of Amsterdam
Stephen M. Stick
Stephen M. Stick University of Western Australia
David M. J. Tax
David M. J. Tax Delft University of Technology
Monique M.B. Breteler
Monique M.B. Breteler German Center for Neurodegenerative Diseases

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