Cargando…
Deep learning‐based carotid media‐adventitia and lumen‐intima boundary segmentation from three‐dimensional ultrasound images
PURPOSE: Quantification of carotid plaques has been shown to be important for assessing as well as monitoring the progression and regression of carotid atherosclerosis. Various metrics have been proposed and methods of measurements ranging from manual tracing to automated segmentations have also bee...
Autores principales: | Zhou, Ran, Fenster, Aaron, Xia, Yujiao, Spence, J. David, Ding, Mingyue |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6851826/ https://www.ncbi.nlm.nih.gov/pubmed/31071228 http://dx.doi.org/10.1002/mp.13581 |
Ejemplares similares
-
Automated 3D geometry segmentation of the healthy and diseased carotid artery in free‐hand, probe tracked ultrasound images
por: de Ruijter, Joerik, et al.
Publicado: (2020) -
Retinal layer segmentation of macular OCT images using boundary classification
por: Lang, Andrew, et al.
Publicado: (2013) -
Development and verification of radiomics framework for computed tomography image segmentation
por: Gu, Jiabing, et al.
Publicado: (2022) -
Transfer learning for data‐efficient abdominal muscle segmentation with convolutional neural networks
por: McSweeney, Dónal M., et al.
Publicado: (2022) -
An unsupervised automatic segmentation algorithm for breast tissue classification of dedicated breast computed tomography images
por: Caballo, Marco, et al.
Publicado: (2018)