dr. E. Thibeau-Sutre (Elina)


About Me

I obtained my PhD in 2021 at Paris Brain Institute with a thesis entitled Reproducible and interpretable deep learning for the diagnosis, prognosis and subtyping of Alzheimer’s disease from neuroimaging data. Another main output of my PhD is the contributions to two Python libraries:

My research interests are in deep learning for medical image analysis, in particular the study of their validity and robustness and their application to neurological problems.

I fully support my peers working on climate science, which is why I joined University Rebellion and Scientist Rebellion.


Thibeau-Sutre, E. , Alblas, D., Buurman, S. , Brune, C. , & Wolterink, J. M. (Accepted/In press). Uncertainty-based quality assurance of carotid artery segmentation. In Uncertainty for Safe Utilization of Machine Learning in Medical Imaging (UNSURE)
Thibeau-Sutre, E. , Wolterink, J. M., Colliot, O., & Burgos, N. (2023). How Can Data Augmentation Improve Attribution Maps for Disease Subtype Explainability? In O. Colliot, & I. Isgum (Eds.), SPIE Medical Imaging 2023: Image Processing [1246424] SPIE. https://doi.org/10.1117/12.2653809
Thibeau-Sutre, E., Díaz, M., Hassanaly, R., Routier, A., Dormont, D., Colliot, O., & Burgos, N. (2022). ClinicaDL: An open-source deep learning software for reproducible neuroimaging processing. Computer methods and programs in biomedicine, 220, [106818]. https://doi.org/10.1016/j.cmpb.2022.106818
Thibeau-Sutre, E., Couvy-Duchesne, B., Dormont, D., Colliot, O., & Burgos, N. (2022). MRI field strength predicts Alzheimer's disease: a case example of bias in the ADNI data set. In MRI field strength predicts Alzheimer's disease: a case example of bias in the ADNI data set https://doi.org/10.1109/ISBI52829.2022.9761504
Other Contributions

    Journal papers:

    1. Wen*, J., Thibeau-Sutre*, E., Díaz-Melo, M., Samper-González, J., Routier,A., Bottani, S., Dormont, D., Durrleman, S., Burgos, N. and Colliot, O.,“Convolutional Neural Networks for Classification of Alzheimer’s Disease: Overview and Reproducible Evaluation”, Medical Image Analysis, 63, 101694 (2020) doi:10.1016/j.media.2020.101694hal-02562504 (*: joint first authorship)
    2. Couvy-Duchesne*, B., Faouzi*, J., Martin*, B., Thibeau-Sutre*, E., Wild*, A., Ansart, M., Durrleman, S., Dormont, D., Burgos, N. and Colliot, O., “Ensemble Learning of Convolutional Neural Network, Support Vector Machine, and Best Linear Unbiased Predictor for Brain Age Prediction: ARAMIS Contribution to the Predictive Analytics Competition 2019 Challenge”, Frontiers in Psychiatry, 11 (2020) doi:10.3389/fpsyt.2020.593336hal-03136463 (*: joint first authorship)
    3. Burgos*, N., Bottani*, S., Faouzi*, J., Thibeau-Sutre*, E. and Colliot, O., “Deep learning for brain disorders: from data processing to disease treatment”, Briefings in Bioinformatics, 22(2), 1560–1576 (2021) doi:10.1093/bib/bbaa310hal-03070554 (*: joint first authorship)
    4. Chadebec, C., Thibeau-Sutre,E., Burgos, N. and Allassonnière, S., “Data augmentation on neuroimaging data with variational autoencoders”, IEEE Transactions on Pattern Analysis and Machine Intelligence (2022) 10.1109/TPAMI.2022.3185773arXiv: 2105.00026

    Journal papers linked to software contributions:

    1. Routier, A., Burgos, N., Guillon, J., Samper-González, J., Wen, J. and Bottani, S.,Marcoux, A., Bacci, M., Fontanella, S., Jacquemont, T., Wild, A., Gori, P., Guyot,A., Lu, P., Díaz, M., Thibeau-Sutre, E., Moreau, T., Teichmann, M., Habert, M.-O., Durrleman, S. and Colliot, O., “Clinica: an open source software platform forreproducible clinical neuroscience studies”, Frontiers in Neuroinformatics, 15 (2021) doi:10.3389/fninf.2021.689675hal-02308126
    2. Thibeau-Sutre*, E., Díaz*, M., Hassanaly, R., Routier, A., Didier, D., Colliot, O.,Burgos, N., “ClinicaDL: an open-source deep learning software for reproducibleneuroimaging processing”, Computer Methods and Programs in Biomedicine (20220 10.1016/j.cmpb.2022.106818hal-03351976 (*: joint first authorship)

    Peer-reviewed conference proceedings:

    1. Thibeau-Sutre, E., Colliot, O., Dormont, D. and Burgos, N., “Visualization approach to assess the robustness of neural networks for medical image classification”, SPIE Medical Imaging, 11313, 113131J, 2020 doi:10.1117/12.2548952hal-02370532
    2. Thibeau-Sutre, E., Couvy-Duchesne, B., Dormont, D., Colliot, O. and Burgos, N., “MRI Field Strength Predicts Alzheimer’s Disease: a Case Example of Bias in the ADNI Data Set”, ISBI - International Symposium on Biomedical Imaging, 2022 doi:10.1109/ISBI52829.2022.9761504hal-03542213
    3. Thibeau-Sutre, E., Wolterink, J., Dormont, D., Colliot, O. and Burgos, N., “How can data augmentation improve attribution maps for disease subtype explainability?”, SPIE Medical Imaging, 2023 hal-0396673

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    Courses Academic Year  2023/2024

    Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.

    Courses Academic Year  2022/2023

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    Visiting Address

    University of Twente
    Faculty of Electrical Engineering, Mathematics and Computer Science
    Zilverling (building no. 11), room 2067
    Hallenweg 19
    7522NH  Enschede
    The Netherlands

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    Mailing Address

    University of Twente
    Faculty of Electrical Engineering, Mathematics and Computer Science
    Zilverling  2067
    P.O. Box 217
    7500 AE Enschede
    The Netherlands