Dual-Energy CT Texture Analysis With Machine Learning for the Evaluation and Characterization of Cervical Lymphadenopathy

PURPOSE: To determine whether machine learning assisted-texture analysis of multi-energy virtual monochromatic image (VMI) datasets from dual-energy CT (DECT) can be used to differentiate metastatic head and neck squamous cell carcinoma (HNSCC) lymph nodes from lymphoma, inflammatory, or normal lymp...

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Detalles Bibliográficos
Autores principales: Seidler, Matthew, Forghani, Behzad, Reinhold, Caroline, Pérez-Lara, Almudena, Romero-Sanchez, Griselda, Muthukrishnan, Nikesh, Wichmann, Julian L., Melki, Gabriel, Yu, Eugene, Forghani, Reza
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6682309/
https://www.ncbi.nlm.nih.gov/pubmed/31406557
http://dx.doi.org/10.1016/j.csbj.2019.07.004

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6682309/
https://www.ncbi.nlm.nih.gov/pubmed/31406557
http://dx.doi.org/10.1016/j.csbj.2019.07.004

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