26 citations · 89 across the 8 of their papers we have counts for
5 papers · 1 filter
Quantifying and Leveraging Predictive Uncertainty for Medical Image Assessment
Florin C. Ghesu, Bogdan Georgescu, Awais Mansoor +11
The interpretation of medical images is a challenging task, often complicated by the presence of artifacts, occlusions, limited contrast and more. Most notable is the case of chest…
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…
No Surprises: Training Robust Lung Nodule Detection for Low-Dose CT Scans by Augmenting with Adversarial Attacks
Siqi Liu, Arnaud Arindra Adiyoso Setio, Florin C. Ghesu +4
Detecting malignant pulmonary nodules at an early stage can allow medical interventions which may increase the survival rate of lung cancer patients. Using computer vision techniqu…