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Ninon Burgos

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  • Research projects
    • 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
  • Publications
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  • ARAMIS Lab
24/03/2023

PRD – Robust Anomaly Detection in Multimodal Neuroimaging

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PRD – Robust Anomaly Detection in Multimodal Neuroimaging

Latest publications
  • Comparing Longitudinal Preprocessing Pipelines for Brain Volume Consistency in T1-Weighted MRI Test-Retest Scans
  • Unsupervised anomaly detection in brain FDG PET with deep generative models: An experimental analysis of model variability and mitigation strategies
  • Benchmarking 3D generative autoencoders for pseudo-healthy reconstruction of brain 18F-fluorodeoxyglucose positron emission tomography
  • Unsupervised anomaly detection using Bayesian flow networks: application to brain FDG pet in the context of Alzheimer’s disease
  • Automatic quality control of brain 3D FLAIR MRIs for a clinical data warehouse
  • Simulation d'artefacts pour le contrôle automatique de la qualité d'IRM cérébrales FLAIR en routine clinique
  • Reproducibility in medical image computing: what is it and how is it assessed?
  • Confidence intervals uncovered: Are we ready for real-world medical imaging AI?
  • Detecting Brain Anomalies in Clinical Routine with the β-VAE: Feasibility Study on Age-Related White Matter Hyperintensities
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