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
Keunen
Projects & clinical trials
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:
Featured team members
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Selma
Boudissa Research Engineer -
Georgia
Kanli Research Engineer -
Olivier
Keunen Group Leader -
Daniele
Perlo Postdoctoral Fellow
Scientific publications
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Immune cell identity behind the Ktrans mapping of mouse glioblastoma – 21/06/2023
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Molecular Identity Changes of Tumor-Associated Macrophages and Microglia After Magnetic Resonance Imaging–Guided Focused Ultrasound–Induced Blood–Brain Barrier Opening in a Mouse Glioblastoma Model – 01/01/2023
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Author Correction – 26/01/2023
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Federated learning enables big data for rare cancer boundary detection – 05/12/2022
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Deciphering Human Glioblastoma Invasion Using a Developmental Mature Rat Brain Organoid Model – 15/11/2022
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The BET Protein Inhibitor JQ1 Decreases Hypoxia and Improves the Therapeutic Benefit of Anti-PD-1 in a High-Risk Neuroblastoma Mouse Model – 06/09/2022
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Federated Learning Enables Big Data for Rare Cancer Boundary Detection – 22/04/2022
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Molecular Identity Changes of Tumor-Associated Macrophages and Microglia after MRgFUS induced BBB Opening in a Mouse Glioblastoma Model – 15/03/2022
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Exploiting Liver CT scans in Colorectal Carcinoma genomics mutation classification – 01/01/2022
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Relationship between Metabolically Unhealthy Obesity and Visceral Adipose Tissue in Youth – 01/12/2021
