Improved performance and consistency of deep learning 3D liver segmentation with heterogeneous cance...
Improved performance and consistency of deep learning 3D liver segmentation with heterogeneous cancer stages in magnetic resonance imaging
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Publisher
United States: Public Library of Science
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Language
English
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Publisher
United States: Public Library of Science
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Accurate liver segmentation is key for volumetry assessment to guide treatment decisions. Moreover, it is an important pre-processing step for cancer detection algorithms. Liver segmentation can be especially challenging in patients with cancer-related tissue changes and shape deformation. The aim of this study was to assess the ability of state-of...
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Full title
Improved performance and consistency of deep learning 3D liver segmentation with heterogeneous cancer stages in magnetic resonance imaging
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TN_cdi_plos_journals_2605185726
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2605185726
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ISSN
1932-6203
E-ISSN
1932-6203
DOI
10.1371/journal.pone.0260630
