Pumping up the volume

Catherine G. Galbraith

doi:10.1083/jcb.202212042

Pumping up the volume

Research output: Contribution to journal › Comment/debate › peer-review

Abstract

The time and cost of annotating ground-truth images and network training are major challenges to utilizing machine learning to automate the mining of volume electron microscopy data. In this issue, Gallusser et al. (2023. J. Cell Biol.https://doi.org/10.1083/jcb.202208005) present a less computationally intense pipeline to detect a single type of organelle using a limited number of loosely annotated images.

Original language	English (US)
Article number	e202212042
Journal	Journal of Cell Biology
Volume	222
Issue number	2
DOIs	https://doi.org/10.1083/jcb.202212042
State	Published - Feb 6 2023

ASJC Scopus subject areas

Cell Biology

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10.1083/jcb.202212042

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abstract = "The time and cost of annotating ground-truth images and network training are major challenges to utilizing machine learning to automate the mining of volume electron microscopy data. In this issue, Gallusser et al. (2023. J. Cell Biol.https://doi.org/10.1083/jcb.202208005) present a less computationally intense pipeline to detect a single type of organelle using a limited number of loosely annotated images.",

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note = "Funding Information: National Institutes of Health 1R01GM117188 and W. M. Keck Foundation provided financial support.",

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Pumping up the volume

Abstract

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