Correcting bias in cardiac geometries derived from multimodal images using spatiotemporal mapping
Correcting bias in cardiac geometries derived from multimodal images using spatiotemporal mapping
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Publisher
London: Nature Publishing Group UK
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Language
English
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London: Nature Publishing Group UK
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Contents
Cardiovascular imaging studies provide a multitude of structural and functional data to better understand disease mechanisms. While pooling data across studies enables more powerful and broader applications, performing quantitative comparisons across datasets with varying acquisition or analysis methods is problematic due to inherent measurement bi...
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Full title
Correcting bias in cardiac geometries derived from multimodal images using spatiotemporal mapping
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TN_cdi_doaj_primary_oai_doaj_org_article_c1bf624dbcde4207ba2acf57d0feb0bd
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_c1bf624dbcde4207ba2acf57d0feb0bd
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ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-023-33968-5
