77 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Camille Maumet2 profiles5 · h 17
- Élisa Fromont3 profiles5 · h 21
- Elodie Germani5 · h 3
- E. Bannier2 profiles4 · h 24
- Stéphanie Leplaideur2 profiles4 · h 2
- Youwan Mahé2 profiles4 · h 2
- B. Combès3 · h 14
- E. Caruyer3 · h 20
- Francesca Galassi3 · h 3
- Pierre Maurel2 profiles3 · h 3
- A. Kerbrat2 · h 20
- C. Barillot2 · h 48
- Institut de Recherche en Informatique et Systèmes AléatoiresFR10 papers
- Université de RennesFR9 papers
- Centre National de la Recherche ScientifiqueFR7 papers
- InsermFR7 papers
- Institut national de recherche en sciences et technologies du numériqueFR5 papers
- Centre Hospitalier Universitaire de RennesFR4 papers
- King's College LondonGB4 papers
- McGill UniversityCA3 papers
- Polytechnique MontréalCA3 papers
- University of OxfordGB3 papers
- Boston Children's HospitalUS2 papers
- CEA Paris-SaclayFR2 papers
4 papers · 1 filter
StrokeSeg2: Stroke Lesion Segmentation in Clinical Research Workflows
Youwan Mahé, Axel Plessis, Stéphanie Leplaideur +3
Deep learning frameworks like nnU-Net achieve state-of-theart brain lesion segmentation performance but remain difficult to deploy in clinical research environments due to, among o…
Stroke Lesion Segmentation in Clinical Workflows: A Modular, Lightweight, and Deployment-Ready Tool
Yann Kerverdo, Florent Leray, Youwan Mahé +2
Deep learning frameworks such as nnU-Net achieve state-of-the-art performance in brain lesion segmentation but remain difficult to deploy clinically due to heavy dependencies and m…
Unsupervised Deep Generative Models for Anomaly Detection in Neuroimaging: A Systematic Scoping Review
Youwan Mahé, Elise Bannier, Stéphanie Leplaideur +2
Unsupervised anomaly detection (UAD) based on deep generative modelling has been increasingly explored for identifying pathological brain abnormalities without requiring voxel-leve…
Biomedical image analysis competitions: The state of current participation practice
Matthias Eisenmann, Annika Reinke, Vivienn Weru +352
The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known abou…