189 citations · 588 across the 44 of their papers we have counts for
16 papers · 1 filter
Propagation and Attribution of Uncertainty in Medical Imaging Pipelines
Leonhard F. Feiner, Martin J. Menten, Kerstin Hammernik +5
Uncertainty estimation, which provides a means of building explainable neural networks for medical imaging applications, have mostly been studied for single deep learning models th…
MAD: Modality Agnostic Distance Measure for Image Registration
Vasiliki Sideri-Lampretsa, Veronika A. Zimmer, Huaqi Qiu +2
Multi-modal image registration is a crucial pre-processing step in many medical applications. However, it is a challenging task due to the complex intensity relationships between d…
Anatomy-Driven Pathology Detection on Chest X-rays
Philip Müller, Felix Meissen, Johannes Brandt +2
Pathology detection and delineation enables the automatic interpretation of medical scans such as chest X-rays while providing a high level of explainability to support radiologist…
Interactive and Explainable Region-guided Radiology Report Generation
Tim Tanida, Philip Müller, Georgios Kaissis +1
The automatic generation of radiology reports has the potential to assist radiologists in the time-consuming task of report writing. Existing methods generate the full report from…
Robust Detection Outcome: A Metric for Pathology Detection in Medical Images
Felix Meissen, Philip Müller, Georgios Kaissis +1
Detection of pathologies is a fundamental task in medical imaging and the evaluation of algorithms that can perform this task automatically is crucial. However, current object dete…
Unsupervised Pathology Detection: A Deep Dive Into the State of the Art
Ioannis Lagogiannis, Felix Meissen, Georgios Kaissis +1
Deep unsupervised approaches are gathering increased attention for applications such as pathology detection and segmentation in medical images since they promise to alleviate the n…