221 citations · 507 across the 42 of their papers we have counts for
6 papers · 1 filter
UniToBrain dataset: a Brain Perfusion Dataset
Daniele Perlo, Enzo Tartaglione, Umberto Gava +3
The CT perfusion (CTP) is a medical exam for measuring the passage of a bolus of contrast solution through the brain on a pixel-by-pixel basis. The objective is to draw "perfusion…
Dysplasia grading of colorectal polyps through CNN analysis of WSI
Daniele Perlo, Enzo Tartaglione, Luca Bertero +2
Colorectal cancer is a leading cause of cancer death for both men and women. For this reason, histopathological characterization of colorectal polyps is the major instrument for th…
UniToPatho, a labeled histopathological dataset for colorectal polyps classification and adenoma dysplasia grading
Carlo Alberto Barbano, Daniele Perlo, Enzo Tartaglione +4
Histopathological characterization of colorectal polyps allows to tailor patients' management and follow up with the ultimate aim of avoiding or promptly detecting an invasive carc…
A two-step explainable approach for COVID-19 computer-aided diagnosis from chest x-ray images
Carlo Alberto Barbano, Enzo Tartaglione, Claudio Berzovini +2
Early screening of patients is a critical issue in order to assess immediate and fast responses against the spread of COVID-19. The use of nasopharyngeal swabs has been considered…
Neural Network-derived perfusion maps: a Model-free approach to computed tomography perfusion in patients with acute ischemic stroke
Umberto A. Gava, Federico D'Agata, Enzo Tartaglione +5
Purpose: In this study we investigate whether a Convolutional Neural Network (CNN) can generate clinically relevant parametric maps from CT perfusion data in a clinical setting of…
Unveiling COVID-19 from Chest X-ray with deep learning: a hurdles race with small data
Enzo Tartaglione, Carlo Alberto Barbano, Claudio Berzovini +2
The possibility to use widespread and simple chest X-ray (CXR) imaging for early screening of COVID-19 patients is attracting much interest from both the clinical and the AI commun…