dr. E. Thibeau-Sutre (Elina)

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.2020.101694 – hal-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.2020.593336 – hal-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/bbaa310 – hal-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.2022.3185773 – arXiv: 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.2021.689675 – hal-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.2022.106818 – hal-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:10.1117/12.2548952 – hal-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/ISBI52829.2022.9761504 – hal-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