Automated classification of coronary plaque calcification in OCT pullbacks with 3D deep neural networks

Significance: Detection and characterization of coronary atherosclerotic plaques often need reviews of a large number of optical coherence tomography (OCT) imaging slices to make a clinical decision. However, it is a challenge to manually review all the slices and consider the interrelationship betw...

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Detalles Bibliográficos
Autores principales: He, Chunliu, Wang, Jiaqiu, Yin, Yifan, Li, Zhiyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Photo-Optical Instrumentation Engineers 2020
Materias:
General
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7481437/
https://www.ncbi.nlm.nih.gov/pubmed/32914606
http://dx.doi.org/10.1117/1.JBO.25.9.095003

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7481437/
https://www.ncbi.nlm.nih.gov/pubmed/32914606
http://dx.doi.org/10.1117/1.JBO.25.9.095003

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