Performance of machine learning software to classify breast lesions using BI-RADS radiomic features on ultrasound images

BACKGROUND: The purpose of this work was to evaluate computable Breast Imaging Reporting and Data System (BI-RADS) radiomic features to classify breast masses on ultrasound B-mode images. METHODS: The database consisted of 206 consecutive lesions (144 benign and 62 malignant) proved by percutaneous...

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Detalles Bibliográficos
Autores principales: Fleury, Eduardo, Marcomini, Karem
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2019
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6682836/
https://www.ncbi.nlm.nih.gov/pubmed/31385114
http://dx.doi.org/10.1186/s41747-019-0112-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6682836/
https://www.ncbi.nlm.nih.gov/pubmed/31385114
http://dx.doi.org/10.1186/s41747-019-0112-7

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