Segmentation-based cardiomegaly detection based on semi-supervised estimation of cardiothoracic rati...
Segmentation-based cardiomegaly detection based on semi-supervised estimation of cardiothoracic ratio
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Publisher
London: Nature Publishing Group UK
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Language
English
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Publisher
London: Nature Publishing Group UK
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The successful integration of neural networks in a clinical setting is still uncommon despite major successes achieved by artificial intelligence in other domains. This is mainly due to the black box characteristic of most optimized models and the undetermined generalization ability of the trained architectures. The current work tackles both issues...
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Full title
Segmentation-based cardiomegaly detection based on semi-supervised estimation of cardiothoracic ratio
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TN_cdi_doaj_primary_oai_doaj_org_article_a8ddf02b11134a88bd8f5030b6ba5617
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_a8ddf02b11134a88bd8f5030b6ba5617
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ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-024-56079-1
