12 citations · 28 across the 8 of their papers we have counts for
8 papers
Generation of Anonymous Chest Radiographs Using Latent Diffusion Models for Training Thoracic Abnormality Classification Systems
Kai Packhäuser, Lukas Folle, Florian Thamm +1
The availability of large-scale chest X-ray datasets is a requirement for developing well-performing deep learning-based algorithms in thoracic abnormality detection and classifica…
Deep Learning-based Anonymization of Chest Radiographs: A Utility-preserving Measure for Patient Privacy
Kai Packhäuser, Sebastian Gündel, Florian Thamm +2
Robust and reliable anonymization of chest radiographs constitutes an essential step before publishing large datasets of such for research purposes. The conventional anonymization…
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…
Segmentation of the Carotid Lumen and Vessel Wall using Deep Learning and Location Priors
Florian Thamm, Felix Denzinger, Leonhard Rist +3
In this report we want to present our method and results for the Carotid Artery Vessel Wall Segmentation Challenge. We propose an image-based pipeline utilizing the U-Net architect…
Detection of Large Vessel Occlusions using Deep Learning by Deforming Vessel Tree Segmentations
Florian Thamm, Oliver Taubmann, Markus Jürgens +2
Computed Tomography Angiography is a key modality providing insights into the cerebrovascular vessel tree that are crucial for the diagnosis and treatment of ischemic strokes, in p…
Magnetic Resonance Fingerprinting Reconstruction Using Recurrent Neural Networks
Elisabeth Hoppe, Florian Thamm, Gregor Körzdörfer +6
Magnetic Resonance Fingerprinting (MRF) is an imaging technique acquiring unique time signals for different tissues. Although the acquisition is highly accelerated, the reconstruct…
RinQ Fingerprinting: Recurrence-informed Quantile Networks for Magnetic Resonance Fingerprinting
Elisabeth Hoppe, Florian Thamm, Gregor Körzdörfer +6
Recently, Magnetic Resonance Fingerprinting (MRF) was proposed as a quantitative imaging technique for the simultaneous acquisition of tissue parameters such as relaxation times $T…