3D U-Net for segmentation of COVID-19 associated pulmonary infiltrates using transfer learning: State-of-the-art results on affordable hardware

no code implementations • 25 Jan 2021 • Keno K. Bressem, Stefan M. Niehues, Bernd Hamm, Marcus R. Makowski, Janis L. Vahldiek, Lisa C. Adams

Our model performed comparable to previously published 3D U-Net architectures, achieving a mean Dice score of 0. 679 on the tuning dataset, 0. 648 on the Coronacases dataset and 0. 405 on the MosMed dataset.

Computed Tomography (CT) Segmentation +1

Comparing Different Deep Learning Architectures for Classification of Chest Radiographs

no code implementations • 20 Feb 2020 • Keno K. Bressem, Lisa Adams, Christoph Erxleben, Bernd Hamm, Stefan Niehues, Janis Vahldiek

Chest radiographs are among the most frequently acquired images in radiology and are often the subject of computer vision research.

Classification Deep Learning +1