translational radiomics

The Translational Radiomics group develops innovative methods for biomedical image analysis.  

Activities

A specific focus is on leveraging the richness of data available in preclinical systems to train Deep Learning models and fine tune these models for clinical applications using Transfer Learning approaches. 

Olivier
Keunen

Projects & clinical trials

Department of Cancer Research Translational Radiomics Cancer
In Vivo Imaging Platform
Department of Cancer Research Translational Radiomics In Vivo Imaging
Optimization of image acquisition protocols in Magnetic resonance Imaging (MRI) in oncology and neurology applications
Department of Cancer Research Translational Radiomics Cancer
Jury member for Doctoral thesis of Stefania Chounta, University Paris-Saclay
Department of Cancer Research Translational Radiomics Cancer
Multimodal Imaging of Physiologic Changes Induced by Anti-Angiogenic Therapy in Glioblastoma
Department of Cancer Research Brain Imaging & Neuro Epidemiology Translational Radiomics
Radiomics for the differential diagnosis of radio-necrosis vs. progression after stereotactic radiotherapy of oligometastasis
Department of Cancer Research Translational Radiomics NORLUX Neuro-Oncology Laboratory
Pseudo PET imaging of brain tumor hypoxia

Research projects

Some of the group’s research projects include: 

  • Systematic improvement of medical images quality using AutoEncoders 
  • Deep molecular imaging using multi-parametric MRI 
  • Automatic detection of seizures in videos of epileptic rats 
  • Brain tumors segmentation using Federated Learning 

Illustations:

Fig 1 – Auto-encoders for MRI quality improvement 

Fig2 – Deep MRI hypoxia imaging 
Fig3 – Rat epilepsy modeling 
Fig 4 – Brain tumor segmentation 

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