Esther E. Bron, PhD
Neuroimage analysis & Machine learning
Key publications
- K. Mouheb et al. Automatic Extraction of Structured Information from Brain MRI Reports Using an Open-Weight Large Language Model, European Radiology, 2026
- M.F. van Haaften et al. Atrophy Patterns across Dementia Etiologies assessed by MRI-based Clustering of a Memory Clinic Population, Neurology Open Access, 2026
- P. Mateus* et al. Multi-Cohort Federated Learning Shows Synergy in Mortality Prediction for MRI-Based and Metabolomics-Based Age Scores, Journal of Healthcare Informatics Research , 2025
- E.E. Bron et al. Cross-Cohort Generalizability of Deep and Conventional Machine Learning for MRI-based Diagnosis and Prediction of Alzheimer’s Disease , NeuroImage: Clinical, 2021
Dr. Esther Bron’s mission is to translate artificial intelligence (AI) to clinical practice, so future patients can be diagnosed and treated based on knowledge gained from previous patients. Therefore, she develops with her team novel image analysis and prediction methodology for neurodegenerative diseases and strongly collaborates with clinicians and clinical researchers to validate these methods for clinical application.
Dr. Esther Bron leads the research line ‘Neuroimage analysis and Machine learning’ at the department of Radiology & Nuclear Medicine of Erasmus MC – University Medical Center Rotterdam , the Netherlands. In 2011, Esther completed her master’s degree in medical physics at VU Amsterdam (cum laude). She defended her doctoral thesis in 2016 at the Erasmus University Rotterdam, which focused on the development and validation of advanced image analysis techniques for computer-aided diagnosis of dementia. Since then, Esther has successfully built her research line and has been appointed associate professor in 2025. Esther is also Image Data Coordinator at Health-RI since 2022.
Research projects
Dr. Esther Bron is PI in several multicenter projects (CVON Heart Brain Connection, ImProVas, Parelsnoer), and coordinator of the Image & Data Science Platform. She won the Young eScientist Award 2018 by the Netherlands eScience Center and was finalist for the Young Outstanding Researcher Award 2020 by Alzheimer Nederland. Recent research outcomes of Esther Brons team include development of DEBM – a novel disease progression model, which is currently being evaluated in several neurodegenerative diseases (i.e. Alzheimer’s disease, frontotemporal dementia, Creutzfeldt-Jacob’s disease, multiple sclerosis). In addition, the team developed neural network approaches for cross-sectional and longitudinal white matter tract segmentation. Esther (co-)organized two international grand challenges for the objective comparison of algorithms for AD diagnosis (CADDementia challenge) and prediction (TADPOLE challenge).
International collaborations
Dr. Esther Bron collaborates with clinicians, companies, and several national and international research groups. A major partner is the Progression Of Neurodegenerative Disease (POND) group at University College London, with whom she organized the TADPOLE challenge which evaluates which data, processing pipelines, and predictive models provide the best estimates of future AD progression. In 2018, Esther won the Young eScientist Award which led to a collaboration with the Netherlands eScience Center and several international research teams (e.g. National University of Singapore, Tecnologico de Monterrey) on the TADPOLE-SHARE project.
Health-RI
Esther also works for Health-RI as the Imaging Data Coordinator, part of the Architecture team. The mission of Health-RI data is to achieve better health for citizens and patients by reusing health data with an integrated health data infrastructure for research and innovation. Esther is setting up the Imaging Data working group to integrate the infrastructure for finding, getting and using Imaging Data with the eight Health-RI nodes in the Netherlands.
PhD degree
Esther obtained her PhD degree on March 9 2016 with her thesis entitled Advanced MRI Analysis for Computer-Aided Diagnosis of Dementia. In her PhD research under supervision of Prof. W.J. Niessen, dr. S. Klein and dr. M. Smits, she developed and improved multiple methods for computer-aided diagnosis of dementia. As part of this, she organized the CADDementia challenge which compared image-based diagnosis algorithms. In the CADDementia workshop at the MICCAI 2014 conference, she presented the results of this challenge. With this project, Esther was nominated for the Dutch Data Prize 2014 and won a Best Scientific Paper Presentation Award at the European Congress of Radiology in 2015.
Contact
Department of Radiology & Nuclear Medicine
Office Na2506
P.O. Box 2040
3000 CA Rotterdam, NL
Awards
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European Conference on Radiology"Certificate of Merit" by the ECR 2026 Scientific Exhibition Jury
Mouheb, K. et al., Poster #20313 titled “The impact of feature-level cohort differences on the generalizability of foundation models in Alzheimer's disease classification”.
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Alzheimer's & Dementia (Wiley)Top 10% of most-viewed papers published by the journal in 2023
Venkatrahavan, V. et al., A discriminative event‐based model for subtype diagnosis of sporadic Creutzfeldt‐Jakob disease using brain MRI
More information -
Erasmus MC - AI AcceleratorThird prize poster competition for federated learning work
Jing Yu – Federated BrainAge estimation from MRI: a proof of concept
More information -
Erasmus MCErasmus MC Fellowship 2022
More information -
OSIPI-ISMRMWinner ASL challenge 2022
Iris pipeline is most accurate perfusion MRI quantification software
More information
In the press
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Wanted: test for reliable and rapid diagnosis of frontotemporal dementia
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Spotlight on the Population Imaging Node’s contribution to EUCAIM
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Image data services interview at the Population Imaging Flagship Node Rotterdam
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Interview Bo Li "Collaboration ensures that I can do effective research"
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Talentprijs: Young Outstanding Researcher Award
Publications
3. Book Chapters
- V. Venkatraghavan, S.R. van der Voort, D. Bos, M. Smits, F. Barkhof, W.J. Niessen, S. Klein*, E.E. Bron*, Computer-aided diagnosis and prediction in brain disorders, Machine Learning for Brain Disorders, 2022
4. Registers
- M.F. van Haaften, P.T. Nguyen Ho, M.W. Vernooij, E.E. Bron, Cross-cohort generalizability of neuroimaging based machine learning methods for Alzheimer’s disease and mild cognitive impairment: a systematic review, PROSPERO International prospective register of systematic reviews, 2023
5. Conference Proceedings
- E.E. Bron, M. Smits, J.C. van Swieten, W.J. Niessen and S. Klein, Proc MICCAI workshop Challenge on Computer-Aided Diagnosis of Dementia Based on Structural MRI Data, 2014
Team
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Esther Bron, PhD
Assistant Professor
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Hyunho Mo, PhD
Postdoctoral researcher
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Bo Li
PhD Candidate / Postdoctoral researcher
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Wenjie Kang
PhD Candidate
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Myrthe van Haaften
PhD Candidate
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Kaouther Mouheb
PhD Candidate
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Sterre de Jonge
PhD Candidate
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Jing Yu
Affiliated PhD Candidate
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Alexander Harms
Research Software Engineer
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Mahlet Birhanu
Research Software Engineer
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Julien Triacca
MSc Engineering, ENSEEIHT Toulouse
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Antoine Manenti
MSc Engineering, ENSEEIHT Toulouse
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Interested in joining?
Former team members
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Nathalie Koorn
MSc Biomedical Engineering, TU Delft (2024)
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Beatriz Domingos
BSc Biomedical Engineering & Biophysics, Univ of Lisbon (2024)
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Joana Dias de Oliveira Coelho
BSc Biomedical Engineering & Biophysics, Univ of Lisbon (2024)
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Sönke van Loh
MSc Electrical Engineering, U Twente (2023)
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Claudia Chinea Hammecher
MSc Biomedical Engineering, TU Delft (2023)
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Myrthe van Haaften
MSc Technical Medicine, EMC/TU Delft/LUMC (2022)
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Karina Hoefnagel
BSc Psychobiology, Universiteit van Amsterdam (2022)
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Dalia Aljawaheri
MSc Nanobiology, TU Delft (2021)
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Vikram Venkatraghavan
Postdoctoral researcher / PhD candidate (2021)
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Diede Wijnbergen
MSc Technical Medicine, EMC/TU Delft/LUMC (2021)
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Lotte Mulder
MSc Biomedical Engineering, TU Delft (2021)
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Liselot Goris
MSc Biomedical Engineering, U Twente (2021)
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Niels de Bruin
MSc Computer Science, TU Delft (2020)
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Thomas Michelotti
MSc Econometrics, EUR (2020)
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Savine Martens
MSc Biomedical Engineering, TU Delft (2020)
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Theodoros Theodoridis
MSc Medical Natural Sciences, VU (2019)
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Marloes Adank
MSc Biomedical Engineering, TU Delft (2019)
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Jara Linders
MSc Brain & Cognitive Sciences, UvA (2019)
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Leontine Ham
MSc Medical Natural Sciences, VU (2018)
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Thomas Michaud
MSc, ENSEEIHT Toulouse (2018)
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Sara Laros
BSc Medical Natural Sciences, VU (2018)
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Jim Smit
BSc Clinical Technology, EMC/TU Delft/LUMC (2017)
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Sandrine Lacomme
MSc, ENSEEIHT Toulouse (2013)
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Ines Merida
MSc, Polytech Marseille (2012)