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 assistant professor in 2020. Esther is also Image Data Coordinator at Health-RI since 2022.
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).
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.
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.
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.
Iris pipeline is most accurate perfusion MRI quantification software
1st prize Ventricle prediction, 3rd prize Diagnosis
PhD Candidate / Postdoctoral researcher
Affiliated PhD Candidate
Research Software Engineer
Research Software Engineer
MSc Electrical Engineering, U Twente
MSc Biomedical Engineering, TU Delft
MSc Biomedical Engineering, TU Delft (2023)
MSc Technical Medicine, EMC/TU Delft/LUMC (2022)
BSc Psychobiology, Universiteit van Amsterdam (2022)
MSc Nanobiology, TU Delft (2021)
Postdoctoral researcher / PhD candidate (2021)
MSc Technical Medicine, EMC/TU Delft/LUMC (2021)
MSc Biomedical Engineering, TU Delft (2021)
MSc Biomedical Engineering, U Twente (2021)
MSc Computer Science, TU Delft (2020)
MSc Econometrics, EUR (2020)
MSc Biomedical Engineering, TU Delft (2020)
MSc Medical Natural Sciences, VU (2019)
MSc Biomedical Engineering, TU Delft (2019)
MSc Brain & Cognitive Sciences, UvA (2019)
MSc Medical Natural Sciences, VU (2018)
MSc, ENSEEIHT Toulouse (2018)
BSc Medical Natural Sciences, VU (2018)
BSc Clinical Technology, EMC/TU Delft/LUMC (2017)
MSc, ENSEEIHT Toulouse (2013)
MSc, Polytech Marseille (2012)