Publications in 2023

  1. Leveraging Jupyter on Maxwell HPC: joyful, visual and green computing: Frank Schlünzen et al., Digital total - Poster, doi: https://www.conferences.uni-hamburg.de/event/387/contributions/1492/attachments/612/1137/Digital-Maxwell.pdf
  2. On the material dependency of peri-implant morphology and stability in healing bone: Stefan Bruns et al., Bioactive Materials, doi: 10.1016/j.bioactmat.2023.05.006
  3. Artificial intelligence for synchrotron-radiation tomography: Julian P. Moosmann et al., Proc. SPIE PC12655, Emerging Topics in Artificial Intelligence (ETAI) 2023, PC1265502, doi: 10.1117/12.2675628

Publications in 2022

  1. CrossMoDA 2021 challenge: Benchmark of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation: Reuben Dorent et al., Medical Image Analysis, doi: 10.1016/j.media.2022.102628
  2. Verbesserung des 2D U-Nets für die 3D Mikrotomographie mit Synchrotronstrahlung mittels Multi-Axes Fusing: Ivo M. Baltruschat et al., Bildverarbeitung für die Medizin, doi: 10.1007/978-3-658-36932-3_28
  3. An active learning approach for the interactive and guided segmentation of tomography data: Bashir Kazimi et al., SPIE Optical Engineering + Applications, doi: 10.1117/12.2637973
  4. Reconstruction, processing and analysis of tomography data at the Hereon beamlines P05/P07 at PETRA III (Conference Presentation): Julian P. Moosmann et al., SPIE Optical Engineering + Applications, doi: 10.1117/12.2637973
  5. Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning: A.Hering et al., , doi: 10.48550/arXiv.2112.04489

Publications in 2021

  1. Scaling the U-net: segmentation of biodegradable bone implants in high-resolution synchrotron radiation microtomograms: Ivo M. Baltruschat et al., Sci Rep, doi: 10.1038/s41598-021-03542-y
  2. Multi-modal Unsupervised Domain Adaptation for Deformable Registration Based on Maximum Classifier Discrepancy: Christian N. Kruse et al., Bildverarbeitung für die Medizin, doi: 10.1007/978-3-658-33198-6_47

Publications in 2020

  1. Unsupervised learning of multimodal image registration using domain adaptation with projected Earth Mover’s discrepancies: M.P.Heinrich et al., , doi:

Closely related and derived Publications

  1. Multiscale morphological analysis of bone microarchitecture around Mg-10Gd implants: Sandra Sefa et al., Bioactive Materials, doi: 10.1016/j.bioactmat.2023.07.017
  2. Development of a Bioreactor-Coupled Flow-Cell Setup for 3D In Situ Nanotomography of Mg Alloy Biodegradation: Jan Reimers et al., ACS Appl. Mater. Interfaces, doi: 10.1021/acsami.3c04054
  3. Detailing the influence of PEO-coated biodegradable Mg-based implants on the lacuno-canalicular network in sheep bone: A pilot study: Jonathan Espiritu et al., Bioactive Materials, doi: https://doi.org/10.1016/j.bioactmat.2023.02.018
  4. Utilizing Computational Modelling to Bridge the Gap between In Vivo and In Vitro Degradation Rates for Mg-xGd Implants: Tamadur Al Baraghtheh et al., CMD, doi: https://doi.org/10.3390/cmd4020014
  5. In vitro and in vivo degradation behavior of Mg-0.45Zn-0.45Ca (ZX00) screws for orthopedic applications: Diana C. Martinez et al., Bioactive Materials, doi: 10.1016/j.bioactmat.2023.05.004
  6. Degradation behavior and osseointegration of Mg-Zn-Ca screws in different bone regions of growing sheep—a pilot study: R Marek et al., , doi: 10.1093/rb/rbac077
  7. In silico studies of magnesium-based implants: A review of the current stage and challenges: Tamadur Albaraghtheh et al., Journal of Magnesium and Alloys, doi: https://doi.org/10.1016/j.jma.2022.09.029
  8. Combining peridynamic and finite element simulations to capture the corrosion of degradable bone implants and to predict their residual strength: Alexander Hermann et al., International Journal of Mechanical Sciences, doi: https://doi.org/10.1016/j.ijmecsci.2022.107143
  9. The Comparability of In Vitro and In Vivo Experiments for Degradable Mg Implants: Regine Willumeit-Römer et al., null, doi: https://doi.org/10.1007/978-3-030-92533-8_3
  10. Implant degradation of low-alloyed Mg–Zn–Ca in osteoporotic, old and juvenile rats: Nicole G. Sommer et al., Acta Biomaterialia, doi: https://doi.org/10.1016/j.actbio.2022.05.041
  11. Oxygen-sensitive nanoparticles reveal the spatiotemporal dynamics of oxygen reduction during magnesium implant biodegradation: Berit Zeller-Plumhoff et al., npj Mater Degrad, doi: https://doi.org/10.1038/s41529-022-00302-9
  12. Assessing the long-term in vivo degradation behavior of magnesium alloys - a high resolution synchrotron radiation micro computed tomography study: Sandra Sefa et al., Front. Biomater. Sci., doi: 10.3389/fbiom.2022.925471
  13. Machine learning denoising of high-resolution X-ray nanotomography data: Silja Flenner et al., J Synchrotron Radiat, doi: 10.1107/S1600577521011139
  14. Artifacts suppression in biomedical images using a guided filter: Inna Bukreeva et al., Thirteenth International Conference on Machine Vision, doi: 10.1117/12.2587571
  15. Computational modelling of magnesium degradation in simulated body fluid under physiological conditions: Berit Zeller-Plumhoff et al., Journal of Magnesium and Alloys, doi: https://doi.org/10.1016/j.jma.2021.11.014
  16. Evaluating Design Choices for Deep Learning Registration Networks: Hanna Siebert et al., Bildverarbeitung für die Medizin, doi: 10.1007/978-3-658-33198-6_26
  17. Multimodal ex vivo methods reveal that Gd-rich corrosion byproducts remain at the implant site of biodegradable Mg-Gd screws: Niccolò Peruzzi et al., Acta Biomaterialia, doi: 10.1016/j.actbio.2021.09.047
  18. Assessing the microstructure and in vitro degradation behavior of Mg-xGd screw implants using µCT: Diana Krüger et al., Journal of Magnesium and Alloys, doi: 10.1016/j.jma.2021.07.029
  19. High-resolution ex vivo analysis of the degradation and osseointegration of Mg-xGd implant screws in 3D: Diana Krüger et al., Bioactive Materials, doi: 10.1016/j.bioactmat.2021.10.041