147 citations · 160 across the 3 of their papers we have counts for
3 papers
Incorporating Anatomical Awareness for Enhanced Generalizability and Progression Prediction in Deep Learning-Based Radiographic Sacroiliitis Detection
Felix J. Dorfner, Janis L. Vahldiek, Leonhard Donle +15
Purpose: To examine whether incorporating anatomical awareness into a deep learning model can improve generalizability and enable prediction of disease progression. Methods: This r…
3D U-Net for segmentation of COVID-19 associated pulmonary infiltrates using transfer learning: State-of-the-art results on affordable hardware
Keno K. Bressem, Stefan M. Niehues, Bernd Hamm +3
Segmentation of pulmonary infiltrates can help assess severity of COVID-19, but manual segmentation is labor and time-intensive. Using neural networks to segment pulmonary infiltra…
Comparing Different Deep Learning Architectures for Classification of Chest Radiographs
Keno K. Bressem, Lisa Adams, Christoph Erxleben +3
Chest radiographs are among the most frequently acquired images in radiology and are often the subject of computer vision research. However, most of the models used to classify che…