11 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Laboratoire d’Imagerie BiomédicaleFR2 papers
- Myriad (Germany)DE2 papers
- Centre de Recherche en Acquisition et Traitement de l'Image pour la SantéFR1 paper
- Centre de Recherche en Neurosciences de LyonFR1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- City College of New YorkUS1 paper
- City University of New YorkUS1 paper
- HCL Technologies (India)IN1 paper
- Hospices Civils de LyonFR1 paper
- InsermFR1 paper
- Institut de MyologieFR1 paper
- Institut National de la StatistiqueMG1 paper
4 papers · 1 filter
Whole-brain radiomics for clustered federated personalization in brain tumor segmentation
Matthis Manthe, Stefan Duffner, Carole Lartizien
Federated learning and its application to medical image segmentation have recently become a popular research topic. This training paradigm suffers from statistical heterogeneity be…
Anomaly detection in image or latent space of patch-based auto-encoders for industrial image analysis
Nicolas Pinon, Robin Trombetta, Carole Lartizien
We study several methods for detecting anomalies in color images, constructed on patch-based auto-encoders. Wecompare the performance of three types of methods based, first, on the…
One-Class SVM on siamese neural network latent space for Unsupervised Anomaly Detection on brain MRI White Matter Hyperintensities
Nicolas Pinon, Robin Trombetta, Carole Lartizien
Anomaly detection remains a challenging task in neuroimaging when little to no supervision is available and when lesions can be very small or with subtle contrast. Patch-based repr…
Brain subtle anomaly detection based on auto-encoders latent space analysis : application to de novo parkinson patients
Nicolas Pinon, Geoffroy Oudoumanessah, Robin Trombetta +3
Neural network-based anomaly detection remains challenging in clinical applications with little or no supervised information and subtle anomalies such as hardly visible brain lesio…