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 Dr. 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. Dr. Bron (co-)organized two international grand challenges for the objective comparison of algorithms for AD diagnosis (CADDementia challenge) and prediction (TADPOLE challenge).

International collaborations

Dr. 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, Dr. Bron 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.

PhD degree

Dr. Bron 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.


Erasmus MC - University Medical Center Rotterdam

Department of Radiology & Nuclear Medicine
Office Na2502
P.O. Box 2040
3000 CA Rotterdam, NL


1. Journal Papers

2. Conference Papers

3. Conference Proceedings

4. Conference Abstracts

  • E.E. Bron, S. Klein, J.M. Papma, L.C. Jiskoot, V. Venkatraghavan, J. Linders, P. Aalten, P.P. de Deyn, G.J. Biessels, J.A.H.R. Claassen, H.A.M. Middelkoop, M. Smits, W.J. Niessen, J.C. van Swieten, W.M. van der Flier, I. Ramakers, A. van der Lugt, External Validation of MRI-based Machine Learning in Alzheimer’s disease: the Parelsnoer biobank, Europe Biobank Week, 2020
  • V. Wottschel, I. Dekker, M. Schoonheim, V. Venkatraghavan, A. Eijlers, I. Brouwer, E. Bron, S. Klein, M. Wattjes, J. Geurts, B. Uitdehaag, N. Oxtoby, D. Alexander, H. Vrenken, J. Killestein, F. Barkhof, Event-based modelling of multimodal biomarkers in multiple sclerosis, CompAge, 2020
  • V. Venkatraghavan, S. Klein, L. Fani, L.S. Ham, H. Vrooman, M.K. Ikram, W.J. Niessen, E.E. Bron, Analyzing the effect of APOE on Alzheimer's disease progression using an event-based model for stratified populations, CompAge, 2020
  • E.J. Vinke*, V. Venkatraghavan*, E.E. Bron, W.J. Niessen, M.A. Ikram, S. Klein, M.W. Vernooij, Predicting the incidence of Alzheimer's disease in the general elderly population using event-based modelling, CompAge, 2020
  • E.E. Bron, V. Venkatraghavan, J. Linders, W.J. Niessen, and S. Klein, Deep versus Conventional Machine Learning for MRI-based diagnosis and prediction of Alzheimer’s disease, Alzheimer’s Association International Conference (AAIC), 2020

5. Invited Lectures

  • E.E. Bron, Dementia: brain imaging, machine learning and open science, Dutch Society of Pattern Recognition (NVPHBV) - Virtual Meeting Series Fall 2020: Advances in Medical Deep Learning, Nijmegen/NL, 17-11-2020
  • E.E. Bron, AI for Dementia Diagnosis: Imaging, Generalizability and Open Science, International Symposium on Artificial Intelligence for Prevention & Intervention in Dementia Care (AIDEM), 2nd Krems Dementia Conference, Vienna/AT, 17-11-2020
  • E.E. Bron, Dementia: brain imaging, machine learning and open science, Research Seminar Graduate Program in Computer Science, Tecnológico de Monterrey, Monterrey/MX, 16-10-2020
  • E.E. Bron, J. de Bresser, Brain MRI analysis in the Heart-Brain Connection study , Consortium Meeting Heart-Brain Connection Crossroads, NL, 24-09-2020
  • E.E. Bron, AI and imaging for disease prediction in dementia, Innovation for Health, Rotterdam/NL, 13-02-2020


  • Esther Bron, PhD

    Assistant Professor

  • Vikram Venkatraghavan

    Postdoctoral researcher / PhD candidate

  • Bo Li

    Postdoctoral researcher / PhD candidate

  • Lotte Mulder

    MSc Biomedical Engineering, TU Delft

  • Niels de Bruin

    MSc Computer Science, TU Delft

  • Diede Wijnbergen

    MSc Technical Medicine, EMC/TU Delft/LUMC

Former team members

  • Thomas Michelotti

    MSc Econometrics, EUR (2020)

  • Savine Martens

    MSc Biomedical Engineering, TU Delft (2020)

  • Theodoros Theodoridis

    MSc Medical Natural Sciences, VU (2019)

  • Marloes Adank

    MSc Biomedical Engineering, TU Delft (2019)

  • Jara Linders

    MSc Brain & Cognitive Sciences, UvA (2019)

  • Leontine Ham

    MSc Medical Natural Sciences, VU (2018)

  • Thomas Michaud

    MSc, ENSEEIHT Toulouse (2018)

  • Sara Laros

    BSc Medical Natural Sciences, VU (2018)

  • Jim Smit

    BSc Clinical Technology, EMC/TU Delft/LUMC (2017)

  • Sandrine Lacomme

    MSc, ENSEEIHT Toulouse (2013)

  • Ines Merida

    MSc, Polytech Marseille (2012)