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VAST (Volume Annotation and Segmentation Tool): Efficient Manual and Semi-Automatic Labeling of Large 3D Image Stacks

Author(s): Berger, Daniel R; Seung, H Sebastian; Lichtman, Jeff W

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dc.contributor.authorBerger, Daniel R-
dc.contributor.authorSeung, H Sebastian-
dc.contributor.authorLichtman, Jeff W-
dc.date.accessioned2021-10-08T19:45:04Z-
dc.date.available2021-10-08T19:45:04Z-
dc.date.issued2018-10-16en_US
dc.identifier.citationBerger, Daniel R., H. Sebastian Seung, and Jeff W. Lichtman. "VAST (volume annotation and segmentation tool): efficient manual and semi-automatic labeling of large 3D image stacks." Frontiers in Neural Circuits 12 (2018): pp. 88:1-15. doi:10.3389/fncir.2018.00088en_US
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/pr1t52q-
dc.description.abstractRecent developments in serial-section electron microscopy allow the efficient generation of very large image data sets but analyzing such data poses challenges for software tools. Here we introduce Volume Annotation and Segmentation Tool (VAST), a freely available utility program for generating and editing annotations and segmentations of large volumetric image (voxel) data sets. It provides a simple yet powerful user interface for real-time exploration and analysis of large data sets even in the Petabyte range.en_US
dc.format.extent88:1-15en_US
dc.languageengen_US
dc.language.isoen_USen_US
dc.relation.ispartofFrontiers in Neural Circuitsen_US
dc.rightsFinal published version. This is an open access article.en_US
dc.titleVAST (Volume Annotation and Segmentation Tool): Efficient Manual and Semi-Automatic Labeling of Large 3D Image Stacksen_US
dc.typeJournal Articleen_US
dc.identifier.doi10.3389/fncir.2018.00088-
dc.identifier.eissn1662-5110-
pu.type.symplectichttp://www.symplectic.co.uk/publications/atom-terms/1.0/journal-articleen_US

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