20 citations · 37 across the 3 of their papers we have counts for
5 papers
Quantifying and Leveraging Classification Uncertainty for Chest Radiograph Assessment
Florin C. Ghesu, Bogdan Georgescu, Eli Gibson +6
The interpretation of chest radiographs is an essential task for the detection of thoracic diseases and abnormalities. However, it is a challenging problem with high inter-rater va…
Multi-task Learning for Chest X-ray Abnormality Classification on Noisy Labels
Sebastian Guendel, Florin C. Ghesu, Sasa Grbic +4
Chest X-ray (CXR) is the most common X-ray examination performed in daily clinical practice for the diagnosis of various heart and lung abnormalities. The large amount of data to b…
Automatic Liver Segmentation Using an Adversarial Image-to-Image Network
Dong Yang, Daguang Xu, S. Kevin Zhou +5
Automatic liver segmentation in 3D medical images is essential in many clinical applications, such as pathological diagnosis of hepatic diseases, surgical planning, and postoperati…
Shaping the Future through Innovations: From Medical Imaging to Precision Medicine
Dorin Comaniciu, Klaus Engel, Bogdan Georgescu +1
Medical images constitute a source of information essential for disease diagnosis, treatment and follow-up. In addition, due to its patient-specific nature, imaging information rep…
A Self-Taught Artificial Agent for Multi-Physics Computational Model Personalization
Dominik Neumann, Tommaso Mansi, Lucian Itu +10
Personalization is the process of fitting a model to patient data, a critical step towards application of multi-physics computational models in clinical practice. Designing robust…