Anomaly detection in medical imaging is a challenging task in contexts w...
The burden of liver tumors is important, ranking as the fourth leading c...
Deep Learning models are easily disturbed by variations in the input ima...
The volume of a brain lesion (e.g. infarct or tumor) is a powerful indic...
LiDAR (Light Detection and Ranging) has become an essential part of the
...
Neural network-based anomaly detection remains challenging in clinical
a...
Deep Learning models are easily disturbed by variations in the input ima...
The full acceptance of Deep Learning (DL) models in the clinical field i...
Deep neural networks have become the gold-standard approach for the auto...
Model selection, via penalized likelihood type criteria, is a standard t...
Mixture of experts (MoE) is a popular class of models in statistics and
...
Automatic segmentation of brain abnormalities is challenging, as they va...
This paper addresses the issue of matching rigid and articulated shapes
...
The problem of multimodal clustering arises whenever the data are gather...
Approximate Bayesian computation (ABC) has become an essential part of t...
Data clustering has received a lot of attention and numerous methods,
al...
Hyper-spectral data can be analyzed to recover physical properties at la...
In this work we address the problem of approximating high-dimensional da...