26 citations · 31 across the 4 of their papers we have counts for
6 papers
Self-supervised Learning from 100 Million Medical Images
Florin C. Ghesu, Bogdan Georgescu, Awais Mansoor +8
Building accurate and robust artificial intelligence systems for medical image assessment requires not only the research and design of advanced deep learning models but also the cr…
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…
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…
Communal Domain Learning for Registration in Drifted Image Spaces
Awais Mansoor, Marius George Linguraru
Designing a registration framework for images that do not share the same probability distribution is a major challenge in modern image analytics yet trivial task for the human visu…
Region Proposal Networks with Contextual Selective Attention for Real-Time Organ Detection
Awais Mansoor, Antonio R. Porras, Marius George Linguraru
State-of-the-art methods for object detection use region proposal networks (RPN) to hypothesize object location. These networks simultaneously predicts object bounding boxes and \e…
A Generic Approach to Lung Field Segmentation from Chest Radiographs using Deep Space and Shape Learning
Awais Mansoor, Juan J. Cerrolaza, Geovanny Perez +4
Computer-aided diagnosis (CAD) techniques for lung field segmentation from chest radiographs (CXR) have been proposed for adult cohorts, but rarely for pediatric subjects. Statisti…