@article {69568,
	title = {DaCapo: a modular deep learning framework for scalable 3D image segmentation},
	journal = {arXiv},
	year = {2024},
	month = {2024 Aug 05},
	abstract = {<p>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{\textquoteright}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.</p>
},
	doi = {10.48550/arXiv.2408.02834},
	url = {https://doi.org/10.48550/arXiv.2408.02834},
	author = {Patton, William and Rhoades, Jeff L and Zouinkhi, Marwan and Ackerman, David G and Malin-Mayor, Caroline and Adjavon, Diane and Heinrich, Larissa and Bennett, Davis and Zubov, Yurii and Team, CellMap Project and Weigel, Aubrey and Funke, Jan}
}
