Applications

  1. convexAdam: Fast and accurate optimisation for registration with little learning
  2. deepreg: Medical image registration using deep learning
  3. histology: pseudo-histology synthesis training from corresponding micro-CT slices on manually registered samples
  4. napari: fast, interactive, multi-dimensional image viewer for Python
  5. registration-autofuse: data-driven fusion strategy for deformable image registration
  6. SAM, SAM++ and Cross-SAM: match arbitrary anatomical landmarks between two radiological images (e.g. CT, MR, X-ray, etc.)
  7. voxelmorph: general purpose library for learning-based tools for alignment/registration and modelling with deformations

Publications

  1. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. Unsupervised learning of multimodal image registration using domain adaptation with projected Earth Mover’s discrepancies: M.P.Heinrich et al., , doi: