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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
15/01/2025

2025.01.15_CV_Ninon_Burgos

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2025.01.15_CV_Ninon_Burgos

Latest publications
  • Study of the quality of clinical routine T1w and FLAIR brain MRI scans in a clinical data warehouse
  • Latent maximum-a-posteriori approach to improve pseudo-healthy reconstruction quality
  • ClinicaDL v2: an open-source Python library for reproducible deep learning in neuroimaging
  • Comparing Volumetric Consistency of Longitudinal Preprocessing: A Multi-Cohort Test-Retest Study
  • Mitigating the reconstruction-detection trade-off in VAE-based unsupervised anomaly detection
  • Mitiger le compromis entre détection et qualité de reconstruction en détection d'anomalies non-supervisée à partir de VAE
  • Étude de la qualité des IRM T1 et FLAIR de routine clinique au sein d'un entrepôt de données de santé de l'AP-HP
  • Comparing Longitudinal Preprocessing Pipelines for Brain Volume Consistency in T1-Weighted MRI Test-Retest Scans
  • Assessing the Efficacy of Artefact Synthesis and Transfer Learning for Quality Control in Clinical 3D FLAIR Brain MRI
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