Search Results for author:
Found 3 papers, 2 papers with code
Evaluation of pseudo-healthy image reconstruction for anomaly detection with deep generative models: Application to brain FDG PET
Over the past years, pseudo-healthy reconstruction for unsupervised anomaly detection has gained in popularity.
Leveraging healthy population variability in deep learning unsupervised anomaly detection in brain FDG PET
Unsupervised anomaly detection is a popular approach for the analysis of neuroimaging data as it allows to identify a wide variety of anomalies from unlabelled data.
Clinica: an open source software platform for reproducible clinical neuroscience studies
It relies on the brain imaging data structure (BIDS) for the organization of raw neuroimaging datasets and on established tools written by the community to build its pipelines.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
