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  4. Opportunities and considerations for visualising neuroimaging data on very large displays.
 
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Opportunities and considerations for visualising neuroimaging data on very large displays.
File(s)
f1000_matthew_wall.pdf (4.74 MB)
Published version
Author(s)
Wall, MB
Birch, D
Yong, MY
Type
Journal Article
Abstract
Neuroimaging experiments can generate impressive volumes of data and many images of the results. This is particularly true of multi-modal imaging studies that use more than one imaging technique, or when imaging is combined with other assessments. A challenge for these studies is appropriate visualisation of results in order to drive insights and guide accurate interpretations. Next-generation visualisation technology therefore has much to offer the neuroimaging community. One example is the Imperial College London Data Observatory; a high-resolution (132 megapixel) arrangement of 64 monitors, arranged in a 313 degree arc, with a 6 metre diameter, powered by 32 rendering nodes. This system has the potential for high-resolution, large-scale display of disparate data types in a space designed to promote collaborative discussion by multiple researchers and/or clinicians. Opportunities for the use of the Data Observatory are discussed, with particular reference to applications in Multiple Sclerosis (MS) research and clinical practice. Technical issues and current work designed to optimise the use of the Data Observatory for neuroimaging are also discussed, as well as possible future research that could be enabled by the use of the system in combination with eye-tracking technology.
Date Issued
2016-09-02
Date Acceptance
2016-08-30
Citation
F1000Res, 2016, 5, pp.2157-2157
URI
http://hdl.handle.net/10044/1/53092
DOI
https://www.dx.doi.org/10.12688/f1000research.9522.1
ISSN
2046-1402
Publisher
F1000 Research Ltd
Start Page
2157
End Page
2157
Journal / Book Title
F1000Res
Volume
5
Copyright Statement
© 2016 Wall MB et al. This is an open access article distributed under the terms of the , which
Copyright: Creative Commons Attribution Licence
permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/27703670
Subjects
Neuroimaging
PET
data observatory
display technology
eye-tracking
fMRI
multiple sclerosis.
visualisation
Publication Status
Published
Coverage Spatial
England
Date Publish Online
2016-09-02
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