Radiomics and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography in the Breast Lesions Classification

The aim of the study was to estimate the diagnostic accuracy of textural features extracted by dual-energy contrast-enhanced mammography (CEM) images, by carrying out univariate and multivariate statistical analyses including artificial intelligence approaches. In total, 80 patients with known breas...

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Detalles Bibliográficos
Autores principales: Fusco, Roberta, Piccirillo, Adele, Sansone, Mario, Granata, Vincenza, Rubulotta, Maria Rosaria, Petrosino, Teresa, Barretta, Maria Luisa, Vallone, Paolo, Di Giacomo, Raimondo, Esposito, Emanuela, Di Bonito, Maurizio, Petrillo, Antonella
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8146084/
https://www.ncbi.nlm.nih.gov/pubmed/33946333
http://dx.doi.org/10.3390/diagnostics11050815

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8146084/
https://www.ncbi.nlm.nih.gov/pubmed/33946333
http://dx.doi.org/10.3390/diagnostics11050815

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