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- Latent maximum-a-posteriori approach to improve pseudo-healthy reconstruction quality
- Study of the quality of clinical routine T1w and FLAIR brain MRI scans in a clinical data warehouse
- Beyond Tool Development: Building the Nipoppy Pipeline Store, Ecosystem and Community
- ClinicaDL v2: an open-source Python library for reproducible deep learning in neuroimaging
- Benchmarking skull-stripping methods for integration in Clinica
- Pseudo-healthy FDG PET synthesis: Revisiting a registration and fusion approach with deep learning
- Comparing Volumetric Consistency of Longitudinal Preprocessing: A Multi-Cohort Test-Retest Study
- Integrating Clinica into Nipoppy to Facilitate Reproducible Large-Scale Neuroimaging Studies
- Mitigating the reconstruction-detection trade-off in VAE-based unsupervised anomaly detection