SuperCUT, an unsupervised multimodal image registration with deep learning for biomedical microscopy
SuperCUT, an unsupervised multimodal image registration with deep learning for biomedical microscopy
About this item
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Publisher
England: Oxford University Press
Journal title
Language
English
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Publication information
Publisher
England: Oxford University Press
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Scope and Contents
Contents
Abstract
Numerous imaging techniques are available for observing and interrogating biological samples, and several of them can be used consecutively to enable correlative analysis of different image modalities with varying resolutions and the inclusion of structural or molecular information. Achieving accurate registration of multimodal images i...
Alternative Titles
Full title
SuperCUT, an unsupervised multimodal image registration with deep learning for biomedical microscopy
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Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10938542
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10938542
Other Identifiers
ISSN
1467-5463
E-ISSN
1477-4054
DOI
10.1093/bib/bbae029
