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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
Software
ARAMIS Lab
29/09/2022
2022.09.29_CV_ninon_burgos
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Ninon
Latest publications
Automatic motion artefact detection in brain T1-weighted magnetic resonance images from a clinical data warehouse using synthetic data
Contrast-enhanced to non-contrast-enhanced image translation to exploit a clinical data warehouse of T1-weighted brain MRI
Recent advances in the open-source ClinicaDL software for reproducible neuroimaging with deep learning
Leveraging healthy population variability in deep learning unsupervised anomaly detection in brain FDG PET
Generating PET-derived maps of myelin content from clinical MRI using curricular discriminator training in generative adversarial networks
Pseudo-healthy image reconstruction with variational autoencoders for anomaly detection: A benchmark on 3D 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