BS-Net: learning COVID-19 pneumonia severity on a large Chest X-Ray dataset

2 code implementations • 8 Jun 2020 • Alberto Signoroni, Mattia Savardi, Sergio Benini, Nicola Adami, Riccardo Leonardi, Paolo Gibellini, Filippo Vaccher, Marco Ravanelli, Andrea Borghesi, Roberto Maroldi, Davide Farina

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 COVID-19 patients.

Weakly-supervised Learning