[Master Internship] Scalable unsupervised subtle anomaly detection from longitudinal MR imaging data: Application to Parkinson’s disease
Description
Key words: Statistical and deep learning, Longitudinal analysis, Clustering, Mixed effect model, variational autoencoders, Biomarkers.
Theme / Domain / Context: The main topics of this proposal are in statistical learning and big longitudinal data.
Skills required: computer science, applied mathematics, interest for statistics applied to medical data.
Contact: florence.forbes@inria.fr, carole.lartizien@creatis.insa-lyon.fr,
Michel.Dojat@inserm.fr
Main location: CREATIS Lyon – MYRIAD team, INRIA Grenoble, Statify team
https://team.inria.fr/statify/ , GIN https://neurosciences.univ-grenoble-alpes.fr/fr
