About me
I am a CNRS researcher at the Paris Brain Institute, co-head of the ARAMIS Lab and a fellow of PR[AI]RIE, the PaRis Artificial Intelligence Research InstitutE. I completed my PhD in 2016 at University College London in the Centre for Medical Image Computing under the supervision of Sébastien Ourselin. In 2019, I received the ERCIM Cor Baayen Young Researcher Award.
My research focuses on the processing and analysis of medical images, on the use of images to guide diagnosis, and on the application of these methods to the clinic. In particular, I have contributed to: i) anomaly detection using both traditional image processing techniques and deep generative models, ii) the translation of machine learning approaches for quality control and computer-aided diagnosis into clinical practice, iii) reproducible medical image processing and computer-aided diagnosis with machine learning, and iv) the development of open-source software. These efforts aim to enhance the reliability and scalability of research in clinical neuroscience and support practical advancements in medical imaging.
You can check my CV here.
Representative publications
- Hassanaly, R., Brianceau, C., Solal, M., Colliot, O., and Burgos, N.: Evaluation of Pseudo-Healthy Image Reconstruction for Anomaly Detection with Deep Generative Models: Application to Brain FDG PET. Machine Learning for Biomedical Imaging, 2(Special Issue for Generative Models): 611–656, 2024. doi:10.59275/j.melba.2024-b87a Available on HAL
- Loizillon, S., Bottani, S., Maire, A., Ströer, S., Dormont, D., Colliot, O., and Burgos, N.: Automatic Motion Artefact Detection in Brain T1-Weighted Magnetic Resonance Images from a Clinical Data Warehouse Using Synthetic Data. Medical Image Analysis, 93: 103073, 2024. doi:10.1016/j.media.2023.103073 Available on HAL
- Loizillon, S., Colliot, O., Chougar, L., Stroer, S., Jacob, Y., Maire, A., Dormont, D., and Burgos, N.: Semi-Supervised Domain Adaptation for Automatic Quality Control of FLAIR MRIs in a Clinical Data Warehouse. In Domain Adaptation and Representation Transfer, LNCS, 14293: 84–93, 2024. doi:10.1007/978-3-031-45857-6_9 Available on HAL
- Bottani, S., Burgos, N., Maire, A., Saracino, D., Ströer, S., Dormont, D., and Colliot, O.: Evaluation of MRI-Based Machine Learning Approaches for Computer-Aided Diagnosis of Dementia in a Clinical Data Warehouse. Medical Image Analysis, 89: 102903, 2023. doi:10.1016/j.media.2023.102903 Available on HAL
- Bottani, S., Burgos, N., Maire, A., Wild, A., Ströer, S., Dormont, D., and Colliot, O.: Automatic Quality Control of Brain T1-Weighted Magnetic Resonance Images for a Clinical Data Warehouse. Medical Image Analysis, 75:102219, 2022. doi:10.1016/j.media.2021.102219 Available on HAL
- Thibeau-Sutre, E., Díaz, M., Hassanaly, R., Routier, A., Dormont, D., Colliot, O., and Burgos, N.: ClinicaDL: An Open-Source Deep Learning Software for Reproducible Neuroimaging Processing. Computer Methods and Programs in Biomedicine, 220: 106818, 2022. doi:10.1016/j.cmpb.2022.106818 Available on HAL
- Routier, A., Burgos, N., Díaz, M., Bacci, M., Bottani, S., El-Rifai, O., Fontanella, S., Gori, P., Guillon, J., Guyot, A., Hassanaly, R., Jacquemont, T., Lu, P., Marcoux, A., Moreau, T., Samper-González, J., Teichmann, M., Thibeau-Sutre, E., Vaillant, G., Wen, J., Wild, A., Habert, M.-O., Durrleman, S., and Colliot, O.: Clinica: An Open-Source Software Platform for Reproducible Clinical Neuroscience Studies. Frontiers in Neuroinformatics, 15: 39, 2021. doi:10.3389/fninf.2021.689675 Available on HAL
- Burgos, N., Cardoso, M.J., Samper-González, J., Habert, M.-O., Durrleman, S., Ourselin, S., and Colliot, O.: Anomaly Detection for the Individual Analysis of Brain PET Images. Journal of Medical Imaging, 8(2): 024003, 2021. doi:10.1117/1.JMI.8.2.024003 Available on HAL