156 citations · 187 across the 7 of their papers we have counts for
4 papers · 1 filter
Automated detection and quantification of COVID-19 airspace disease on chest radiographs: A novel approach achieving radiologist-level performance using a CNN trained on digital reconstructed radiographs (DRRs) from CT-based ground-truth
Eduardo Mortani Barbosa, Warren B. Gefter, Rochelle Yang +13
Purpose: To leverage volumetric quantification of airspace disease (AD) derived from a superior modality (CT) serving as ground truth, projected onto digitally reconstructed radiog…
Machine Learning Automatically Detects COVID-19 using Chest CTs in a Large Multicenter Cohort
Eduardo Jose Mortani Barbosa, Bogdan Georgescu, Shikha Chaganti +15
Objectives: To investigate machine-learning classifiers and interpretable models using chest CT for detection of COVID-19 and differentiation from other pneumonias, ILD and normal…
3D Tomographic Pattern Synthesis for Enhancing the Quantification of COVID-19
Siqi Liu, Bogdan Georgescu, Zhoubing Xu +10
The Coronavirus Disease (COVID-19) has affected 1.8 million people and resulted in more than 110,000 deaths as of April 12, 2020. Several studies have shown that tomographic patter…
Automated Quantification of CT Patterns Associated with COVID-19 from Chest CT
Shikha Chaganti, Abishek Balachandran, Guillaume Chabin +17
Purpose: To present a method that automatically segments and quantifies abnormal CT patterns commonly present in coronavirus disease 2019 (COVID-19), namely ground glass opacities…