Search Results for author:
Found 5 papers, 1 papers with code
AIforCOVID: predicting the clinical outcomes in patients with COVID-19 applying AI to chest-X-rays. An Italian multicentre study
Exhaustive evaluation shows promising performance both in 10-fold and leave-one-centre-out cross-validation, implying that clinical data and images have the potential to provide useful information for the management of patients and hospital resources.
Weakly Supervised Geodesic Segmentation of Egyptian Mummy CT Scans
We aim at digitally unwrapping the mummy and identify different segments such as body, bandages and jewelry.
Scanner Invariant Multiple Sclerosis Lesion Segmentation from MRI
This paper presents a simple and effective generalization method for magnetic resonance imaging (MRI) segmentation when data is collected from multiple MRI scanning sites and as a consequence is affected by (site-)domain shifts.
Multi-branch Convolutional Neural Network for Multiple Sclerosis Lesion Segmentation
Our method is based on a deep end-to-end 2D convolutional neural network (CNN) for slice-based segmentation of 3D volumetric data.
Modeling Retinal Ganglion Cell Population Activity with Restricted Boltzmann Machines
The idea was to figure out if binary latent states encode the regularities associated to different visual stimuli, as modes in the joint distribution.
