Development of a Three-Dimensional Carotid Ultrasound Image Segmentation Workflow for Improved Effic...
Development of a Three-Dimensional Carotid Ultrasound Image Segmentation Workflow for Improved Efficiency, Reproducibility and Accuracy in Measuring Vessel Wall and Plaque Volume and Thickness
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Basel: MDPI AG
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English
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Basel: MDPI AG
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Automated segmentation of carotid lumen-intima boundary (LIB) and media-adventitia boundary (MAB) by deep convolutional neural networks (CNN) from three-dimensional ultrasound (3DUS) images has made assessment and monitoring of carotid atherosclerosis more efficient than manual segmentation. However, training of CNN still requires manual segmentati...
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Full title
Development of a Three-Dimensional Carotid Ultrasound Image Segmentation Workflow for Improved Efficiency, Reproducibility and Accuracy in Measuring Vessel Wall and Plaque Volume and Thickness
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TN_cdi_doaj_primary_oai_doaj_org_article_61fab318e13c49ef902c363c94cbd501
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_61fab318e13c49ef902c363c94cbd501
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ISSN
2306-5354
E-ISSN
2306-5354
DOI
10.3390/bioengineering10101217
