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@ARTICLE{Wang:302844,
      author       = {Y. Wang and E. Lombardo and A. Thummerer and T. Blöcker
                      and Y. Fan and Y. Zhao and C. I. Papadopoulou and C.
                      Hurkmans and R. H. N. Tijssen and P. A. W. Görts and S. U.
                      Tetar and D. Cusumano and M. P. Intven and P. Borman and M.
                      Riboldi and D. Dudáš and H. Byrne and L. Placidi and M.
                      Fusella and M. Jameson and M. Palacios and P. Cobussen and
                      T. Finazzi and C. J. A. Haasbeek and P. Keall and C. Kurz
                      and G. Landry$^*$ and M. Maspero},
      title        = {{T}rack{RAD}2025 challenge dataset: real-time tumor
                      tracking for {MRI}-guided radiotherapy.},
      journal      = {Medical physics},
      volume       = {52},
      number       = {7},
      issn         = {0094-2405},
      address      = {Hoboken, NJ},
      publisher    = {Wiley},
      reportid     = {DKFZ-2025-01384},
      pages        = {e17964},
      year         = {2025},
      abstract     = {Magnetic resonance imaging (MRI) to visualize anatomical
                      motion is becoming increasingly important when treating
                      cancer patients with radiotherapy. Hybrid MRI-linear
                      accelerator (MRI-linac) systems allow real-time motion
                      management during irradiation. This paper presents a
                      multi-institutional real-time MRI time series dataset from
                      different MRI-linac vendors. The dataset is designed to
                      support developing and evaluating real-time tumor
                      localization (tracking) algorithms for MRI-guided
                      radiotherapy within the TrackRAD2025 challenge (
                      https://trackrad2025.grand-challenge.org/).The dataset
                      consists of sagittal 2D cine MRIs (20-20543 frames per scan)
                      in 585 patients from six centers (3 Dutch, 1 German, 1
                      Australian, and 1 Chinese). Tumors in the thorax, abdomen,
                      and pelvis acquired on two commercially available MRI-linacs
                      (0.35 T and 1.5 T) were included. For 108 cases, irradiation
                      targets or tracking surrogates were manually segmented on
                      each temporal frame. The dataset was randomly split into a
                      public training set of 527 cases (477 unlabeled and 50
                      labeled) and a private testing set of 58 cases (all
                      labeled).The data is publicly available under the
                      TrackRAD2025 collection: https://doi.org/10.57967/hf/4539.
                      Both the images and segmentations for each patient are
                      available in metadata format.This novel clinical dataset
                      will enable the development and evaluation of real-time
                      tumor localization algorithms for MRI-guided radiotherapy.
                      By enabling more accurate motion management and adaptive
                      treatment strategies, this dataset has the potential to
                      advance the field of radiotherapy significantly.},
      keywords     = {Radiotherapy, Image-Guided: methods / Humans / Magnetic
                      Resonance Imaging / Neoplasms: diagnostic imaging /
                      Neoplasms: radiotherapy / Time Factors / Databases, Factual
                      / Image Processing, Computer-Assisted / MRI‐guided
                      radiotherapy (Other) / Real‐time tumor localization
                      (Other) / TrackRAD2025 (Other)},
      cin          = {MU01},
      ddc          = {610},
      cid          = {I:(DE-He78)MU01-20160331},
      pnm          = {899 - ohne Topic (POF4-899)},
      pid          = {G:(DE-HGF)POF4-899},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:40660787},
      doi          = {10.1002/mp.17964},
      url          = {https://inrepo02.dkfz.de/record/302844},
}