2 citations · 3 across the 5 of their papers we have counts for
6 papers
OTLesMix: Wasserstein Barycenter and Optimal Transport Map for Synthetic Lesion Generation with Diverse Shapes and Locations
Robin Trombetta, Carole Lartizien
The development of deep learning over the past decade has revolutionized medical imaging segmentation, allowing the extraction of precise descriptors from large volumes to characte…
Learning local and global prototypes with optimal transport for unsupervised anomaly detection and localization
Robin Trombetta, Carole Lartizien
Unsupervised anomaly detection aims to detect defective parts of a sample by having access, during training, to a set of normal, i.e. defect-free, data. It has many applications in…
OCSVM-Guided Representation Learning for Unsupervised Anomaly Detection
Nicolas Pinon, Robin Trombetta, Carole Lartizien
Unsupervised anomaly detection (UAD) aims to detect anomalies without labeled data, a necessity in many machine learning applications where anomalous samples are rare or not availa…
GAN-based synthetic FDG PET images from T1 brain MRI can serve to improve performance of deep unsupervised anomaly detection models
Daria Zotova, Nicolas Pinon, Robin Trombetta +3
Background and Objective. Research in the cross-modal medical image translation domain has been very productive over the past few years in tackling the scarce availability of large…
Weakly supervised deep learning model with size constraint for prostate cancer detection in multiparametric MRI and generalization to unseen domains
Robin Trombetta, Olivier Rouvière, Carole Lartizien
Fully supervised deep models have shown promising performance for many medical segmentation tasks. Still, the deployment of these tools in clinics is limited by the very timeconsum…
Time CNN and Graph Convolution Network for Epileptic Spike Detection in MEG Data
Pauline Mouches, Thibaut Dejean, Julien Jung +3
Magnetoencephalography (MEG) recordings of patients with epilepsy exhibit spikes, a typical biomarker of the pathology. Detecting those spikes allows accurate localization of brain…