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09/04/2023
Towards frugal unsupervised detection of subtle abnormalities in medical imaging
Anomaly detection in medical imaging is a challenging task in contexts w...
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08/23/2023
Anisotropic Hybrid Networks for liver tumor segmentation with uncertainty quantification
The burden of liver tumors is important, ranking as the fourth leading c...
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07/28/2023
Multi-layer Aggregation as a key to feature-based OOD detection
Deep Learning models are easily disturbed by variations in the input ima...
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07/28/2023
TriadNet: Sampling-free predictive intervals for lesional volume in 3D brain MR images
The volume of a brain lesion (e.g. infarct or tumor) is a powerful indic...
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05/31/2023
Graph-based methods coupled with specific distributional distances for adversarial attack detection
Artificial neural networks are prone to being fooled by carefully pertur...
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02/27/2023
Brain subtle anomaly detection based on auto-encoders latent space analysis : application to de novo parkinson patients
Neural network-based anomaly detection remains challenging in clinical a...
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11/10/2022
Improving Uncertainty-based Out-of-Distribution Detection for Medical Image Segmentation
Deep Learning models are easily disturbed by variations in the input ima...
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10/05/2022
Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis
The full acceptance of Deep Learning (DL) models in the clinical field i...
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09/22/2022
Beyond Voxel Prediction Uncertainty: Identifying brain lesions you can trust
Deep neural networks have become the gold-standard approach for the auto...
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09/14/2021
ImUnity: a generalizable VAE-GAN solution for multicenter MR image harmonization
ImUnity is an original deep-learning model designed for efficient and fl...
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01/26/2021
