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Ninon Burgos

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    • Ongoing research projects
      • Deep generative models for the detection of anomalies in brain PET images
      • Machine learning to exploit neuroimages in clinical data warehouses
    • Past research projects
      • PhD – Atlas-based methods for image synthesis
      • Postdoc – Joint segmentation and image synthesis
      • Postdoc – Individual analysis of PET images for the diagnosis of dementia
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  • ARAMIS Lab
09/11/2023

2023.11.09 – Advanced Imaging Techniques in Neuroradiology – Essentials of machine learning

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2023.11.09 – Advanced Imaging Techniques in Neuroradiology – Essentials of machine learning

Latest publications
  • Latent maximum-a-posteriori approach to improve pseudo-healthy reconstruction quality
  • Study of the quality of clinical routine T1w and FLAIR brain MRI scans in a clinical data warehouse
  • Beyond Tool Development: Building the Nipoppy Pipeline Store, Ecosystem and Community
  • ClinicaDL v2: an open-source Python library for reproducible deep learning in neuroimaging
  • Benchmarking skull-stripping methods for integration in Clinica
  • Pseudo-healthy FDG PET synthesis: Revisiting a registration and fusion approach with deep learning
  • Comparing Volumetric Consistency of Longitudinal Preprocessing: A Multi-Cohort Test-Retest Study
  • Integrating Clinica into Nipoppy to Facilitate Reproducible Large-Scale Neuroimaging Studies
  • Mitigating the reconstruction-detection trade-off in VAE-based unsupervised anomaly detection
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