CAVE: Connectome Annotation Versioning Engine.

Autor:	Dorkenwald S; Princeton Neuroscience Institute, Princeton University, Princeton, USA.; Computer Science Department, Princeton University, Princeton, USA., Schneider-Mizell CM; Allen Institute for Brain Science, Seattle, USA., Brittain D; Allen Institute for Brain Science, Seattle, USA., Halageri A; Princeton Neuroscience Institute, Princeton University, Princeton, USA., Jordan C; Princeton Neuroscience Institute, Princeton University, Princeton, USA., Kemnitz N; Princeton Neuroscience Institute, Princeton University, Princeton, USA., Castro MA; Princeton Neuroscience Institute, Princeton University, Princeton, USA., Silversmith W; Princeton Neuroscience Institute, Princeton University, Princeton, USA., Maitin-Shephard J; Google Research, Mountain View, USA., Troidl J; School of Engineering and Applied Sciences, Harvard University, Boston, USA., Pfister H; School of Engineering and Applied Sciences, Harvard University, Boston, USA., Gillet V; Lund University, Department of Biology, Lund Vision Group, Lund, Sweden., Xenes D; Research & Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, United States., Bae JA; Princeton Neuroscience Institute, Princeton University, Princeton, USA.; Electrical and Computer Engineering Department, Princeton University, Princeton, USA., Bodor AL; Allen Institute for Brain Science, Seattle, USA., Buchanan J; Allen Institute for Brain Science, Seattle, USA., Bumbarger DJ; Allen Institute for Brain Science, Seattle, USA., Elabbady L; Allen Institute for Brain Science, Seattle, USA., Jia Z; Princeton Neuroscience Institute, Princeton University, Princeton, USA.; Computer Science Department, Princeton University, Princeton, USA., Kapner D; Allen Institute for Brain Science, Seattle, USA., Kinn S; Allen Institute for Brain Science, Seattle, USA., Lee K; Princeton Neuroscience Institute, Princeton University, Princeton, USA.; Brain & Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, USA., Li K; Computer Science Department, Princeton University, Princeton, USA., Lu R; Princeton Neuroscience Institute, Princeton University, Princeton, USA., Macrina T; Princeton Neuroscience Institute, Princeton University, Princeton, USA.; Computer Science Department, Princeton University, Princeton, USA., Mahalingam G; Allen Institute for Brain Science, Seattle, USA., Mitchell E; Princeton Neuroscience Institute, Princeton University, Princeton, USA., Mondal SS; Princeton Neuroscience Institute, Princeton University, Princeton, USA.; Electrical and Computer Engineering Department, Princeton University, Princeton, USA., Mu S; Princeton Neuroscience Institute, Princeton University, Princeton, USA., Nehoran B; Princeton Neuroscience Institute, Princeton University, Princeton, USA.; Computer Science Department, Princeton University, Princeton, USA., Popovych S; Princeton Neuroscience Institute, Princeton University, Princeton, USA.; Computer Science Department, Princeton University, Princeton, USA., Takeno M; Allen Institute for Brain Science, Seattle, USA., Torres R; Allen Institute for Brain Science, Seattle, USA., Turner NL; Princeton Neuroscience Institute, Princeton University, Princeton, USA.; Computer Science Department, Princeton University, Princeton, USA., Wong W; Princeton Neuroscience Institute, Princeton University, Princeton, USA., Wu J; Princeton Neuroscience Institute, Princeton University, Princeton, USA., Yin W; Allen Institute for Brain Science, Seattle, USA., Yu SC; Princeton Neuroscience Institute, Princeton University, Princeton, USA., Reid RC; Allen Institute for Brain Science, Seattle, USA., da Costa NM; Allen Institute for Brain Science, Seattle, USA., Seung HS; Princeton Neuroscience Institute, Princeton University, Princeton, USA.; Computer Science Department, Princeton University, Princeton, USA., Collman F; Allen Institute for Brain Science, Seattle, USA.
Jazyk:	angličtina
Zdroj:	BioRxiv : the preprint server for biology [bioRxiv] 2023 Jul 28. Date of Electronic Publication: 2023 Jul 28.
DOI:	10.1101/2023.07.26.550598
Abstrakt:	Advances in Electron Microscopy, image segmentation and computational infrastructure have given rise to large-scale and richly annotated connectomic datasets which are increasingly shared across communities. To enable collaboration, users need to be able to concurrently create new annotations and correct errors in the automated segmentation by proofreading. In large datasets, every proofreading edit relabels cell identities of millions of voxels and thousands of annotations like synapses. For analysis, users require immediate and reproducible access to this constantly changing and expanding data landscape. Here, we present the Connectome Annotation Versioning Engine (CAVE), a computational infrastructure for immediate and reproducible connectome analysis in up-to petascale datasets (~1mm 3 ) while proofreading and annotating is ongoing. For segmentation, CAVE provides a distributed proofreading infrastructure for continuous versioning of large reconstructions. Annotations in CAVE are defined by locations such that they can be quickly assigned to the underlying segment which enables fast analysis queries of CAVE's data for arbitrary time points. CAVE supports schematized, extensible annotations, so that researchers can readily design novel annotation types. CAVE is already used for many connectomics datasets, including the largest datasets available to date. Competing Interests: Competing interests T. Macrina, K. Lee, S. Popovych, D. Ih, N. Kemnitz, and H. S. Seung declare financial interests in Zetta AI.
Databáze:	MEDLINE
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