8 citations · 11 across the 2 of their papers we have counts for
2 papers
eess.IV2024★ 8 cited
Evaluation of pseudo-healthy image reconstruction for anomaly detection with deep generative models: Application to brain FDG PET
Ravi Hassanaly, Camille Brianceau, Maëlys Solal +2
Over the past years, pseudo-healthy reconstruction for unsupervised anomaly detection has gained in popularity. This approach has the great advantage of not requiring tedious pixel…
eess.IV2023★ 3 cited
Leveraging healthy population variability in deep learning unsupervised anomaly detection in brain FDG PET
Maëlys Solal, Ravi Hassanaly, Ninon Burgos
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. It relies on b…