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23

Elina Thibeau-Sutre - PhD


I am a postdoc in the Mathematics of Imaging & AI (MIA) team at the University of Twente.

I recently obtained my PhD at Paris Brain Institute in December 2021 with a thesis Reproducible and interpretable deep learning for the diagnosis, prognosis and subtyping of Alzheimer’s disease from neuroimaging data. My research interests include deep learning application to medical imaging data, with a focus on the interpretability and reproducibility of deep learning methods.


Theses1 document

  • Elina Thibeau-Sutre. Reproducible and interpretable deep learning for the diagnosis, prognosis and subtyping of Alzheimer’s disease from neuroimaging data. Medical Imaging. Sorbonne Université, 2021. English. ⟨NNT : 2021SORUS495⟩. ⟨tel-03500490v2⟩

Journal articles6 documents

  • Elina Thibeau-Sutre, Mauricio Diaz, Ravi Hassanaly, Alexandre M Routier, Didier Dormont, et al.. ClinicaDL: an open-source deep learning software for reproducible neuroimaging processing. Computer Methods and Programs in Biomedicine, Elsevier, 2022, 220, pp.106818. ⟨10.1016/j.cmpb.2022.106818⟩. ⟨hal-03351976v2⟩
  • Ninon Burgos, Simona Bottani, Johann Faouzi, Elina Thibeau-Sutre, Olivier Colliot. Deep learning for brain disorders: from data processing to disease treatment. Briefings in Bioinformatics, Oxford University Press (OUP), 2021, 22 (2), pp.1560-1576. ⟨10.1093/bib/bbaa310⟩. ⟨hal-03070554⟩
  • Alexandre Routier, Ninon Burgos, Mauricio Díaz, Michael Bacci, Simona Bottani, et al.. Clinica: an open source software platform for reproducible clinical neuroscience studies. Frontiers in Neuroinformatics, Frontiers, 2021, 15, pp.689675. ⟨10.3389/fninf.2021.689675⟩. ⟨hal-02308126v4⟩
  • Manon Ansart, Stéphane Epelbaum, Giulia Bassignana, Alexandre Bône, Simona Bottani, et al.. Predicting the Progression of Mild Cognitive Impairment Using Machine Learning: A Systematic, Quantitative and Critical Review. Medical Image Analysis, Elsevier, 2021, 67, pp.101848. ⟨10.1016/j.media.2020.101848⟩. ⟨hal-02337815v2⟩
  • Baptiste Couvy-Duchesne, Johann Faouzi, Benoît Martin, Elina Thibeau-Sutre, Adam Wild, et al.. 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, Frontiers, 2020, 11, ⟨10.3389/fpsyt.2020.593336⟩. ⟨hal-03136463⟩
  • Junhao Wen, Elina Thibeau-Sutre, Mauricio Diaz-Melo, Jorge Samper-González, Alexandre Routier, et al.. Convolutional Neural Networks for Classification of Alzheimer's Disease: Overview and Reproducible Evaluation. Medical Image Analysis, Elsevier, 2020, 63, pp.101694. ⟨10.1016/j.media.2020.101694⟩. ⟨hal-02562504v2⟩

Conference papers9 documents

  • Omar El Rifai, Mauricio Diaz Melo, Ravi Hassanaly, Matthieu Joulot, Alexandre M Routier, et al.. Advances in the Clinica software platform for clinical neuroimaging studies. OHBM 2022 - Annual meeting of the Organization for Human Brain Mapping, Jun 2022, Glasgow, United Kingdom. ⟨hal-03728243⟩
  • Simona Bottani, Elina Thibeau-Sutre, Aurélien Maire, Sebastian Ströer, Didier Dormont, et al.. Homogenization of brain MRI from a clinical data warehouse using contrast-enhanced to non-contrast-enhanced image translation with U-Net derived models. SPIE Medical Imaging 2022: Image Processing, Feb 2022, San Diego, United States. pp.576-582, ⟨10.1117/12.2608565⟩. ⟨hal-03478798⟩
  • Elina Thibeau-Sutre, Baptiste Couvy-Duchesne, Didier Dormont, Olivier Colliot, Ninon Burgos. MRI field strength predicts Alzheimer's disease: a case example of bias in the ADNI data set. ISBI 2022 - International Symposium on Biomedical Imaging, Mar 2022, Kolkata, India. ⟨10.1109/ISBI52829.2022.9761504⟩. ⟨hal-03542213⟩
  • Etienne Maheux, Juliette Ortholand, Colin Birkenbihl, Elina Thibeau-Sutre, Meemansa Sood, et al.. Forecast Alzheimer's disease progression to better select patients for clinical trials. ISCB 2021: 42nd Conference of the International Society for Clinical Biostatistics, Jul 2021, Online, France. ⟨hal-03483237⟩
  • Omar El-Rifai, Mauricio Diaz Melo, Ravi Hassanaly, Matthieu Joulot, Alexandre M Routier, et al.. Clinica: an open-source software platform for reproducible clinical neuroscience studies. MRI Together 2021 - A global workshop on Open Science and Reproducible MR Research, Dec 2021, Online, France. ⟨hal-03513920⟩
  • Elina Thibeau-Sutre, Olivier Colliot, Didier Dormont, Ninon Burgos. Visualization approach to assess the robustness of neural networks for medical image classification. SPIE Medical Imaging 2020, Feb 2020, Houston, United States. ⟨10.1117/12.2548952⟩. ⟨hal-02370532v3⟩
  • Alexandre Routier, Arnaud Marcoux, Mauricio Diaz Melo, Jorge Samper-González, Adam Wild, et al.. New longitudinal and deep learning pipelines in the Clinica software platform. OHBM 2020 - Annual meeting of the Organization for Human Brain Mapping, Jun 2020, Montreal / Virtual, Canada. ⟨hal-02549242⟩
  • Junhao Wen​, Elina Thibeau--Sutre​, Jorge Samper-González​, Alexandre M Routier, Simona Bottani​, et al.. How serious is data leakage in deep learning studies on Alzheimer's disease classification?. 2019 OHBM Annual meeting - Organization for Human Brain Mapping, Jun 2019, Rome, Italy. ⟨hal-02105133v2⟩
  • Alexandre Routier, Arnaud Marcoux, Mauricio Diaz Melo, Jérémy Guillon, Jorge Samper-González, et al.. New advances in the Clinica software platform for clinical neuroimaging studies. OHBM 2019 - Annual Meeting on Organization for Human Brain Mapping, Jun 2019, Roma, Italy. ⟨10.1016/j.neuroimage.2011.09.015⟩. ⟨hal-02132147v2⟩

Poster communications4 documents

  • Elina Thibeau-Sutre, Mauricio Diaz, Ravi Hassanaly, Alexandre M Routier, Didier Dormont, et al.. ClinicaDL: an open-source deep learning software for reproducible neuroimaging processing. 3IA Doctoral Workshop, Nov 2021, Toulouse, France. ⟨hal-03423072v2⟩
  • Elina Thibeau-Sutre, Olivier Colliot, Didier Dormont, Ninon Burgos. Visualization approach to assess the robustness of neural networks for medical image classification. ICM days 2019, Jan 2020, Louan, France. ⟨hal-03365775⟩
  • Elina Thibeau-Sutre, Olivier Colliot, Didier Dormont, Ninon Burgos. Identification of unlabeled latent subtypes with saliency maps. ICM welcome days, Oct 2020, Paris (online), France. ⟨hal-03365788⟩
  • Junhao Wen, Elina Thibeau-Sutre, Jorge Samper-Gonzalez, Alexandre M Routier, Simona Bottani, et al.. How serious is data leakage in deep learning studies on Alzheimer’s disease classification?. Organization for Human Brain Mapping (OHBM), Jun 2019, Roma, Italy. ⟨hal-03365742⟩

Book sections1 document

  • Elina Thibeau-Sutre, Sasha Collin, Ninon Burgos, Olivier Colliot. Interpretability of Machine Learning Methods Applied to Neuroimaging. Olivier Colliot. Machine Learning for Brain Disorders, Springer, In press. ⟨hal-03615163⟩

Preprints, Working Papers, ...2 documents

  • Clément Chadebec, Elina Thibeau-Sutre, Ninon Burgos, Stéphanie Allassonnière. Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder. 2021. ⟨hal-03214093⟩
  • Simona Bottani, Elina Thibeau-Sutre, Aurelien Maire, Sebastian Stroër, Didier Dormont, et al.. Homogenization of brain MRI from a clinical data warehouse using contrast-enhanced to non-contrast-enhanced image translation. 2021. ⟨hal-03497645⟩