Ultrastructurally-smooth thick partitioning and volume stitching for larger-scale connectomics

FIB-SEM has become an essential tool for studying neural tissue at resolutions below 10×10×10 nm, producing datasets superior for automatic connectome tracing. We present a technical advance, ultrathick sectioning, which reliably subdivides embedded tissue samples into chunks (20 µm thick) optimally...

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Detalles Bibliográficos
Autores principales: Hayworth, Kenneth J., Xu, C. Shan, Lu, Zhiyuan, Knott, Graham W., Fetter, Richard D., Tapia, Juan Carlos, Lichtman, Jeff W., Hess, Harald F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2015
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4382383/
https://www.ncbi.nlm.nih.gov/pubmed/25686390
http://dx.doi.org/10.1038/nmeth.3292
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author Hayworth, Kenneth J.
Xu, C. Shan
Lu, Zhiyuan
Knott, Graham W.
Fetter, Richard D.
Tapia, Juan Carlos
Lichtman, Jeff W.
Hess, Harald F.
author_facet Hayworth, Kenneth J.
Xu, C. Shan
Lu, Zhiyuan
Knott, Graham W.
Fetter, Richard D.
Tapia, Juan Carlos
Lichtman, Jeff W.
Hess, Harald F.
author_sort Hayworth, Kenneth J.
collection PubMed
description FIB-SEM has become an essential tool for studying neural tissue at resolutions below 10×10×10 nm, producing datasets superior for automatic connectome tracing. We present a technical advance, ultrathick sectioning, which reliably subdivides embedded tissue samples into chunks (20 µm thick) optimally sized and mounted for efficient, parallel FIB-SEM imaging. These chunks are imaged separately and then ‘volume stitched’ back together, producing a final 3D dataset suitable for connectome tracing.
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spelling pubmed-43823832015-10-01 Ultrastructurally-smooth thick partitioning and volume stitching for larger-scale connectomics Hayworth, Kenneth J. Xu, C. Shan Lu, Zhiyuan Knott, Graham W. Fetter, Richard D. Tapia, Juan Carlos Lichtman, Jeff W. Hess, Harald F. Nat Methods Article FIB-SEM has become an essential tool for studying neural tissue at resolutions below 10×10×10 nm, producing datasets superior for automatic connectome tracing. We present a technical advance, ultrathick sectioning, which reliably subdivides embedded tissue samples into chunks (20 µm thick) optimally sized and mounted for efficient, parallel FIB-SEM imaging. These chunks are imaged separately and then ‘volume stitched’ back together, producing a final 3D dataset suitable for connectome tracing. 2015-02-16 2015-04 /pmc/articles/PMC4382383/ /pubmed/25686390 http://dx.doi.org/10.1038/nmeth.3292 Text en http://www.nature.com/authors/editorial_policies/license.html#terms Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Hayworth, Kenneth J.
Xu, C. Shan
Lu, Zhiyuan
Knott, Graham W.
Fetter, Richard D.
Tapia, Juan Carlos
Lichtman, Jeff W.
Hess, Harald F.
Ultrastructurally-smooth thick partitioning and volume stitching for larger-scale connectomics
title Ultrastructurally-smooth thick partitioning and volume stitching for larger-scale connectomics
title_full Ultrastructurally-smooth thick partitioning and volume stitching for larger-scale connectomics
title_fullStr Ultrastructurally-smooth thick partitioning and volume stitching for larger-scale connectomics
title_full_unstemmed Ultrastructurally-smooth thick partitioning and volume stitching for larger-scale connectomics
title_short Ultrastructurally-smooth thick partitioning and volume stitching for larger-scale connectomics
title_sort ultrastructurally-smooth thick partitioning and volume stitching for larger-scale connectomics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4382383/
https://www.ncbi.nlm.nih.gov/pubmed/25686390
http://dx.doi.org/10.1038/nmeth.3292
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