Impact of Single-Energy Metal Artifact Reduction on CT image quality in patients with dental hardware. - Stefan Markus Niehues; Janis Lucas Vahldiek; Daniel Tröltzsch; Bernd Hamm; Seyd Shnayien (Comput. Biol. Medicine, 2018)

Comparing Different Deep Learning Architectures for Classification of Chest Radiographs. - Keno K. Bressem; Lisa Adams; Christoph Erxleben; Bernd Hamm; Stefan Markus Niehues; Janis Lucas Vahldiek (CoRR, 2020)

Highly accurate classification of chest radiographic reports using a deep learning natural language model pre-trained on 3.8 million text reports. - Keno K. Bressem; Lisa C. Adams; Robert A. Gaudin; Daniel Tröltzsch; Bernd Hamm; Marcus R. Makowski; Chan-Yong Schüle; Janis Lucas Vahldiek; Stefan Markus Niehues (Bioinform., 2021)

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 Markus Niehues; Bernd Hamm; Marcus R. Makowski; Janis Lucas Vahldiek; Lisa C. Adams (CoRR, 2021)

Dual center validation of deep learning for automated multi-label segmentation of thoracic anatomy in bedside chest radiographs. - Felix Busch; Lina Xu; Dmitry Sushko; Matthias Weidlich 002; Daniel Truhn; Gustav Müller-Franzes; Maurice M. Heimer; Stefan Markus Niehues; Marcus R. Makowski; Markus Hinsche; Janis Lucas Vahldiek; Hugo J. W. L. Aerts; et al. (Comput. Methods Programs Biomed., 2023)

Incorporating Anatomical Awareness for Enhanced Generalizability and Progression Prediction in Deep Learning-Based Radiographic Sacroiliitis Detection. - Felix J. Dorfner; Janis Lucas Vahldiek; Leonhard Donle; Andrei Zhukov; Lina Xu; Hartmut Häntze; Marcus R. Makowski; Hugo J. W. L. Aerts; Fabian Proft; Valeria Rios Rodriguez; Judith Rademacher; Mikhail Protopopov; et al. (CoRR, 2024)