Ten Fast Transfer Learning Models for Carotid Ultrasound Plaque Tissue Characterization in Augmentation Framework Embedded with Heatmaps for Stroke Risk Stratification

Ten Fast Transfer Learning Models for Carotid Ultrasound Plaque Tissue Characterization in Augmentation Framework Embedded with Heatmaps for Stroke Risk Stratification

<i>Background and Purpose:</i> Only 1–2% of the internal carotid artery asymptomatic plaques are unstable as a result of >80% stenosis. Thus, unnecessary efforts can be saved if these plaques can be characterized and classified into symptomatic and asymptomatic using non-invasive B-mo...

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Autores principales: Skandha S. Sanagala, Andrew Nicolaides, Suneet K. Gupta, Vijaya K. Koppula, Luca Saba, Sushant Agarwal, Amer M. Johri, Manudeep S. Kalra, Jasjit S. Suri
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
Materias:
stroke
carotid plaque characterization
symptomatic vs. asymptomatic
artificial intelligence
transfer learning
heatmaps
Medicine (General)
R5-920
Acceso en línea:https://doaj.org/article/328b577cc70340eaa8d8697fe1e80bbb
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https://doaj.org/article/328b577cc70340eaa8d8697fe1e80bbb

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