Skip to content

Ninon Burgos

Google Scholar ● HAL ● Publons ● LinkedIn ● ResearchGate ● Zotero

  • 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

Hello world!

Welcome to WordPress. This is your first post. Edit or delete it, then start writing!

Continue reading
Latest publications
  • Automatic quality control of brain 3D FLAIR MRIs for a clinical data warehouse
  • 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
  • Automated MRI Quality Assessment of Brain T1-weighted MRI in Clinical Data Warehouses: A Transfer Learning Approach Relying on Artefact Simulation
  • Automatic motion artefact detection in brain T1-weighted magnetic resonance images from a clinical data warehouse using synthetic data
  • Clinica, an open-source software to facilitate neuroimaging studies
  • Contrast-enhanced to non-contrast-enhanced image translation to exploit a clinical data warehouse of T1-weighted brain MRI
  • The intriguing effect of frequency disentangled learning on medical image segmentation
WordPress Theme: Maxwell by ThemeZee.