Dr. Kenneth Chen
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kenneth.chen@donau-uni.ac.at
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+43 2732 893-5438
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To contact form
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Campus Krems, Tract D, 2nd Floor, 2.08
- University for Continuing Education Krems
- Center for Regenerative Medicine
- Dr.-Karl-Dorrek-Straße 30
- 3500 Krems
- Austria
Projects (Extract Research Database)
Running projects
Artificial intelligence in orthopedic radiography analysis
Duration: 01/03/2022–28/02/2025
Principle investigator for the project (University for Continuing Education Krems): Stefan Nehrer
Funding: Bundesländer (inkl. deren Stiftungen und Einrichtungen)
Publications (Extract Research Database)
Chen, K.; Stotter, C.; Lepenik, C.; Klestil, T.; Salzlechner, C.; Nehrer, S.; (2024). Frontal plane mechanical leg alignment estimation from knee x-rays using deep learning. Osteoarthritis and Cartilage Open, 100551: https://doi.org/10.1016/j.ocarto.2024.100551
Chen, K.; Stotter, Ch.; Klestil, T.; Mitterer, J.; Lepenik, Ch.; Nehrer, S. (2024). Fully Automated Measurement of Cobb Angles in Coronal Plane Spine Radiographs. J. Clin Med, 2024, 13(14), 4122: https://doi.org/10.3390/jcm13144122
Stotter, C.; Klestil, T.; Chen, C.; Hummer, A.; Salzlechner, C.; Angele, P.; Nehrer, S. (2023). Artificial intelligence-based analyses of varus leg alignment and after high tibial osteot-omy show high accuracy and reproducibility. KSSTA, 2023: 10.1007/s00167-023-07644-0
Stotter, Ch.; Klestil, T.; Röder, Ch.; Reuter, P.; Chen, K.; Emprechtinger, R.; Hummer, A.; Salzlechner, Ch.; DiFranco, M.; Nehrer, S. (2023). Deep Learning for Fully Automated Radiographic Measurements of the Pelvis and Hip. Diagnostics (Basel), 29; 13(3): 497
