13 citations · 25 across the 13 of their papers we have counts for
9 papers · 1 filter
Towards frugal unsupervised detection of subtle abnormalities in medical imaging
Geoffroy Oudoumanessah, Carole Lartizien, Michel Dojat +1
Anomaly detection in medical imaging is a challenging task in contexts where abnormalities are not annotated. This problem can be addressed through unsupervised anomaly detection (…
Anisotropic Hybrid Networks for liver tumor segmentation with uncertainty quantification
Benjamin Lambert, Pauline Roca, Florence Forbes +2
The burden of liver tumors is important, ranking as the fourth leading cause of cancer mortality. In case of hepatocellular carcinoma (HCC), the delineation of liver and tumor on c…
TriadNet: Sampling-free predictive intervals for lesional volume in 3D brain MR images
Benjamin Lambert, Florence Forbes, Senan Doyle +1
The volume of a brain lesion (e.g. infarct or tumor) is a powerful indicator of patient prognosis and can be used to guide the therapeutic strategy. Lesional volume estimation is u…
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…
Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis
Benjamin Lambert, Florence Forbes, Alan Tucholka +3
The full acceptance of Deep Learning (DL) models in the clinical field is rather low with respect to the quantity of high-performing solutions reported in the literature. Particula…
Beyond Voxel Prediction Uncertainty: Identifying brain lesions you can trust
Benjamin Lambert, Florence Forbes, Senan Doyle +2
Deep neural networks have become the gold-standard approach for the automated segmentation of 3D medical images. Their full acceptance by clinicians remains however hampered by the…