14 citations · 14 across the 2 of their papers we have counts for
3 papers · 1 filter
Fighting the scanner effect in brain MRI segmentation with a progressive level-of-detail network trained on multi-site data
Michele Svanera, Mattia Savardi, Alberto Signoroni +2
Many clinical and research studies of the human brain require an accurate structural MRI segmentation. While traditional atlas-based methods can be applied to volumes from any acqu…
BS-Net: learning COVID-19 pneumonia severity on a large Chest X-Ray dataset
Alberto Signoroni, Mattia Savardi, Sergio Benini +8
In this work we design an end-to-end deep learning architecture for predicting, on Chest X-rays images (CXR), a multi-regional score conveying the degree of lung compromise in COVI…
CEREBRUM: a fast and fully-volumetric Convolutional Encoder-decodeR for weakly-supervised sEgmentation of BRain strUctures from out-of-the-scanner MRI
Dennis Bontempi, Sergio Benini, Alberto Signoroni +2
Many functional and structural neuroimaging studies call for accurate morphometric segmentation of different brain structures starting from image intensity values of MRI scans. Cur…