TotalVibeSegmentator: Full Torso Segmentation for the NAKO and UK Biobank in Volumetric Interpolated Breath-hold Examination Body Images
<|reference_start|>TotalVibeSegmentator: Full Torso Segmentation for the NAKO and UK Biobank in Volumetric Interpolated Breath-hold Examination Body Images: Objectives: To present a publicly available torso segmentation network for large epidemiology datasets on volumetric interpolated breath-hold examination (VIBE) images. Materials & Methods: We extracted preliminary segmentations from TotalSegmentator, spine, and body composition networks for VIBE images, then improved them iteratively and retrained a nnUNet network. Using subsets of NAKO (85 subjects) and UK Biobank (16 subjects), we evaluated with Dice-score on a holdout set (12 subjects) and existing organ segmentation approach (1000 subjects), generating 71 semantic segmentation types for VIBE images. We provide an additional network for the vertebra segments 22 individual vertebra types. Results: We achieved an average Dice score of 0.89 +- 0.07 overall 71 segmentation labels. We scored > 0.90 Dice-score on the abdominal organs except for the pancreas with a Dice of 0.70. Conclusion: Our work offers a detailed and refined publicly available full torso segmentation on VIBE images.<|reference_end|>
@article{graf2024totalvibesegmentator:,
    title={TotalVibeSegmentator: Full Body MRI Segmentation for the NAKO and UK
  Biobank},
    author={Robert Graf, Paul-S"oren Platzek, Evamaria Olga Riedel, Constanze
  Ramsch"utz, Sophie Starck, Hendrik Kristian M"oller, Matan Atad, Henry
  V"olzke, Robin B"ulow, Carsten Oliver Schmidt, Julia R"udebusch, Matthias
  Jung, Marco Reisert, Jakob Weiss, Maximilian L"offler, Fabian Bamberg, Bene
  Wiestler, Johannes C. Paetzold, Daniel Rueckert, Jan Stefan Kirschke},
    journal={arXiv preprint arXiv:2406.00125},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.00125},
    primaryClass={eess.IV cs.CV cs.LG}
}