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The Viking viewer for connectomics: scalable multi-user annotation and summarization of large volume data sets
Modern microscope automation permits the collection of vast amounts of continuous anatomical imagery in both two and three dimensions. These large data sets present significant challenges for data storage, access, viewing, annotation and analysis. The cost and overhead of collecting and storing the...
Autores principales: | , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Blackwell Publishing Ltd
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3017751/ https://www.ncbi.nlm.nih.gov/pubmed/21118201 http://dx.doi.org/10.1111/j.1365-2818.2010.03402.x |
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author | ANDERSON, JR MOHAMMED, S GRIMM, B JONES, BW KOSHEVOY, P TASDIZEN, T WHITAKER, R MARC, RE |
author_facet | ANDERSON, JR MOHAMMED, S GRIMM, B JONES, BW KOSHEVOY, P TASDIZEN, T WHITAKER, R MARC, RE |
author_sort | ANDERSON, JR |
collection | PubMed |
description | Modern microscope automation permits the collection of vast amounts of continuous anatomical imagery in both two and three dimensions. These large data sets present significant challenges for data storage, access, viewing, annotation and analysis. The cost and overhead of collecting and storing the data can be extremely high. Large data sets quickly exceed an individual's capability for timely analysis and present challenges in efficiently applying transforms, if needed. Finally annotated anatomical data sets can represent a significant investment of resources and should be easily accessible to the scientific community. The Viking application was our solution created to view and annotate a 16.5 TB ultrastructural retinal connectome volume and we demonstrate its utility in reconstructing neural networks for a distinctive retinal amacrine cell class. Viking has several key features. (1) It works over the internet using HTTP and supports many concurrent users limited only by hardware. (2) It supports a multi-user, collaborative annotation strategy. (3) It cleanly demarcates viewing and analysis from data collection and hosting. (4) It is capable of applying transformations in real-time. (5) It has an easily extensible user interface, allowing addition of specialized modules without rewriting the viewer. |
format | Text |
id | pubmed-3017751 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Blackwell Publishing Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-30177512011-01-19 The Viking viewer for connectomics: scalable multi-user annotation and summarization of large volume data sets ANDERSON, JR MOHAMMED, S GRIMM, B JONES, BW KOSHEVOY, P TASDIZEN, T WHITAKER, R MARC, RE J Microsc Original Articles Modern microscope automation permits the collection of vast amounts of continuous anatomical imagery in both two and three dimensions. These large data sets present significant challenges for data storage, access, viewing, annotation and analysis. The cost and overhead of collecting and storing the data can be extremely high. Large data sets quickly exceed an individual's capability for timely analysis and present challenges in efficiently applying transforms, if needed. Finally annotated anatomical data sets can represent a significant investment of resources and should be easily accessible to the scientific community. The Viking application was our solution created to view and annotate a 16.5 TB ultrastructural retinal connectome volume and we demonstrate its utility in reconstructing neural networks for a distinctive retinal amacrine cell class. Viking has several key features. (1) It works over the internet using HTTP and supports many concurrent users limited only by hardware. (2) It supports a multi-user, collaborative annotation strategy. (3) It cleanly demarcates viewing and analysis from data collection and hosting. (4) It is capable of applying transformations in real-time. (5) It has an easily extensible user interface, allowing addition of specialized modules without rewriting the viewer. Blackwell Publishing Ltd 2011-01 /pmc/articles/PMC3017751/ /pubmed/21118201 http://dx.doi.org/10.1111/j.1365-2818.2010.03402.x Text en Journal compilation © 2011 Royal Microscopical Society http://creativecommons.org/licenses/by/2.5/ Re-use of this article is permitted in accordance with the Creative Commons Deed, Attribution 2.5, which does not permit commercial exploitation. |
spellingShingle | Original Articles ANDERSON, JR MOHAMMED, S GRIMM, B JONES, BW KOSHEVOY, P TASDIZEN, T WHITAKER, R MARC, RE The Viking viewer for connectomics: scalable multi-user annotation and summarization of large volume data sets |
title | The Viking viewer for connectomics: scalable multi-user annotation and summarization of large volume data sets |
title_full | The Viking viewer for connectomics: scalable multi-user annotation and summarization of large volume data sets |
title_fullStr | The Viking viewer for connectomics: scalable multi-user annotation and summarization of large volume data sets |
title_full_unstemmed | The Viking viewer for connectomics: scalable multi-user annotation and summarization of large volume data sets |
title_short | The Viking viewer for connectomics: scalable multi-user annotation and summarization of large volume data sets |
title_sort | viking viewer for connectomics: scalable multi-user annotation and summarization of large volume data sets |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3017751/ https://www.ncbi.nlm.nih.gov/pubmed/21118201 http://dx.doi.org/10.1111/j.1365-2818.2010.03402.x |
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