28 citations · 31 across the 11 of their papers we have counts for
5 papers · 1 filter
SEMPAI: a Self-Enhancing Multi-Photon Artificial Intelligence for prior-informed assessment of muscle function and pathology
Alexander Mühlberg, Paul Ritter, Simon Langer +11
Deep learning (DL) shows notable success in biomedical studies. However, most DL algorithms work as a black box, exclude biomedical experts, and need extensive data. We introduce t…
DeepTechnome: Mitigating Unknown Bias in Deep Learning Based Assessment of CT Images
Simon Langer, Oliver Taubmann, Felix Denzinger +2
Reliably detecting diseases using relevant biological information is crucial for real-world applicability of deep learning techniques in medical imaging. We debias deep learning mo…
Building Brains: Subvolume Recombination for Data Augmentation in Large Vessel Occlusion Detection
Florian Thamm, Oliver Taubmann, Markus Jürgens +5
Ischemic strokes are often caused by large vessel occlusions (LVOs), which can be visualized and diagnosed with Computed Tomography Angiography scans. As time is brain, a fast, acc…
An Algorithm for the Labeling and Interactive Visualization of the Cerebrovascular System of Ischemic Strokes
Florian Thamm, Markus Jürgens, Oliver Taubmann +4
During the diagnosis of ischemic strokes, the Circle of Willis and its surrounding vessels are the arteries of interest. Their visualization in case of an acute stroke is often ena…
CAD-RADS Scoring using Deep Learning and Task-Specific Centerline Labeling
Felix Denzinger, Michael Wels, Oliver Taubmann +8
With coronary artery disease (CAD) persisting to be one of the leading causes of death worldwide, interest in supporting physicians with algorithms to speed up and improve diagnosi…