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Ninon Burgos

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  • Home
  • 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
  • Software
  • ARAMIS Lab

Author: Ninon

13/11/2017 Uncategorized

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Latest publications
  • Leveraging healthy population variability in deep learning unsupervised anomaly detection in brain FDG PET
  • Evaluation of pseudo-healthy image reconstruction for anomaly detection with deep generative models: Application to brain FDG PET
  • A2V: A Semi-Supervised Domain Adaptation Framework for Brain Vessel Segmentation via Two-Phase Training Angiography-to-Venography Translation
  • Unsupervised anomaly detection in 3D brain FDG PET: A benchmark of 17 VAE-based approaches
  • Semi-supervised Domain Adaptation for Automatic Quality Control of FLAIR MRIs in a Clinical Data Warehouse
  • Evaluation of MRI-based machine learning approaches for computer-aided diagnosis of dementia in a clinical data warehouse
  • From Nipype to Pydra: a Clinica story
  • Operationalizing the centiloid scale for [18 F]florbetapir PET studies on PET/MRI
  • Simulation-based evaluation framework for deep learning unsupervised anomaly detection on brain FDG PET
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