1 citations · 2 across the 5 of their papers we have counts for
6 papers
Active MRI Acquisition with Diffusion Guided Bayesian Experimental Design
Jacopo Iollo, Geoffroy Oudoumanessah, Carole Lartizien +2
A key challenge in maximizing the benefits of Magnetic Resonance Imaging (MRI) in clinical settings is to accelerate acquisition times without significantly degrading image quality…
Scalable magnetic resonance fingerprinting: Incremental inference of high dimensional elliptical mixtures from large data volumes
Geoffroy Oudoumanessah, Thomas Coudert, Carole Lartizien +3
Magnetic Resonance Fingerprinting (MRF) is an emerging technology with the potential to revolutionize radiology and medical diagnostics. In comparison to traditional magnetic reson…
Cluster globally, Reduce locally: Scalable efficient dictionary compression for magnetic resonance fingerprinting
Geoffroy Oudoumanessah, Thomas Coudert, Luc Meyer +4
With the rapid advancements in medical data acquisition and production, increasingly richer representations exist to characterize medical information. However, such large-scale dat…
Fast, accurate and lightweight sequential simulation-based inference using Gaussian locally linear mappings
Henrik Häggström, Pedro L. C. Rodrigues, Geoffroy Oudoumanessah +2
Bayesian inference for complex models with an intractable likelihood can be tackled using algorithms performing many calls to computer simulators. These approaches are collectively…
Towards frugal unsupervised detection of subtle abnormalities in medical imaging
Geoffroy Oudoumanessah, Carole Lartizien, Michel Dojat +1
Anomaly detection in medical imaging is a challenging task in contexts where abnormalities are not annotated. This problem can be addressed through unsupervised anomaly detection (…
Brain subtle anomaly detection based on auto-encoders latent space analysis : application to de novo parkinson patients
Nicolas Pinon, Geoffroy Oudoumanessah, Robin Trombetta +3
Neural network-based anomaly detection remains challenging in clinical applications with little or no supervised information and subtle anomalies such as hardly visible brain lesio…