%Aigaion2 BibTeX export from HES SO Valais Publications
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@ARTICLE{,
    author = {Hansen, Lasse and Wachinger, Christian and Wodzinski, Marek and M{\"{u}}ller, Henning and Brudfors, Mikael and Wells, William M. and Carass, Aaron and Dorent, Reuben and Hering, Alessa and Heinrich, Mattias},
  keywords = {(Bio-) Medical Image Registration, Data Challenges},
     month = dec,
     title = {Learn2Reg 2024: New Benchmark Datasets Driving Progress on New Challenges},
   journal = {Melba},
    volume = {Volume 3},
      year = {2025},
     pages = {775-791},
       doi = {https://doi.org/10.59275/j.melba.2025-gc8c},
  abstract = {Medical image registration is critical for clinical applications, and fair benchmarking of different methods is essential
for monitoring ongoing progress in the field. To date, the Learn2Reg 2020-2023 challenges have released several
complementary datasets and established metrics for evaluations. Building on this foundation, the 2024 edition expands
the challenge’s scope to cover a wider range of registration scenarios, particularly in terms of modality diversity and task
complexity, by introducing three new tasks, including large-scale multi-modal registration and unsupervised inter-subject
brain registration, as well as the first microscopy-focused benchmark within Learn2Reg. The new datasets also inspired
new method developments, including invertibility constraints, pyramid features, keypoints alignment and instance
optimisation}
}