@article {69518,
	title = {Hot-Distance: Combining One-Hot and Signed Distance Embeddings for Segmentation},
	journal = {arXiv},
	year = {2024},
	month = {2024 Jun 25},
	pages = {2406.17936},
	abstract = {<p>Machine learning models are only as good as the data to which they are fit. As such, it is always preferable to use as much data as possible in training models. What data can be used for fitting a model depends a lot on the formulation of the task. We introduce Hot-Distance, a novel segmentation target that incorporates the strength of signed boundary distance prediction with the flexibility of one-hot encoding, to increase the amount of usable training data for segmentation of subcellular structures in focused ion beam scanning electron microscopy (FIB-SEM).</p>
},
	doi = {10.48550/arXiv.2406.17936},
	url = {https://doi.org/10.48550/arXiv.2406.17936},
	author = {Marwan Zouinkhi and Jeff L Rhoades and Aubrey V. Weigel}
}
@article {68193,
	title = {Architecture and dynamics of a novel desmosome-endoplasmic reticulum organelle},
	journal = {bioRxiv},
	year = {2022},
	month = {2022 Jul 08},
	abstract = {<p>The endoplasmic reticulum (ER) forms a dynamic network that contacts other cellular membranes to regulate stress responses, calcium signaling, and lipid transfer. Using high-resolution volume electron microscopy, we find that the ER forms a previously unknown association with keratin intermediate filaments and desmosomal cell-cell junctions. Peripheral ER assembles into mirror image-like arrangements at desmosomes and exhibits nanometer proximity to keratin filaments and the desmosome cytoplasmic plaque. ER tubules exhibit stable associations with desmosomes, and perturbation of desmosomes or keratin filaments alters ER organization and mobility. These findings indicate that desmosomes and the keratin cytoskeleton pattern the distribution of the ER network. Overall, this study reveals a previously unknown subcellular architecture defined by the structural integration of ER tubules with an epithelial intercellular junction.</p>
},
	doi = {10.1101/2022.07.07.499185},
	url = {https://doi.org/10.1101/2022.07.07.499185},
	author = {Navaneetha Krishnan Bharathan and William Giang and Jesse S. Aaron and Satya Khuon and Teng-Leong Chew and Stephan Preibisch and Eric T. Trautman and Larissa Heinrich and John Bogovic and Davis Bennett and David Ackerman and Woohyun Park and Alyson Petruncio and Aubrey V. Weigel and Stephan Saalfeld and COSEM Project Team and A. Wayne Vogl and Sara N. Stahley and Andrew P. Kowalczyk}
}
