DaCapo: a modular deep learning framework for scalable 3D image segmentation
<|reference_start|>DaCapo: a modular deep learning framework for scalable 3D image segmentation: DaCapo is a specialized deep learning library tailored to expedite the training and application of existing machine learning approaches on large, near-isotropic image data. In this correspondence, we introduce DaCapo's unique features optimized for this specific domain, highlighting its modular structure, efficient experiment management tools, and scalable deployment capabilities. We discuss its potential to improve access to large-scale, isotropic image segmentation and invite the community to explore and contribute to this open-source initiative.<|reference_end|>
@article{patton2024dacapo:,
    title={DaCapo: a modular deep learning framework for scalable 3D image
  segmentation},
    author={William Patton, Jeff L. Rhoades, Marwan Zouinkhi, David G. Ackerman,
  Caroline Malin-Mayor, Diane Adjavon, Larissa Heinrich, Davis Bennett, Yurii
  Zubov, CellMap Project Team, Aubrey V. Weigel, and Jan Funke},
    journal={arXiv preprint arXiv:2408.02834},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.02834},
    primaryClass={cs.CV cs.LG eess.IV q-bio.QM}
}