An Automated In-Depth Feature Learning Algorithm for Breast Abnormality Prognosis and Robust Characterization from Mammography Images Using Deep Transfer Learning

SIMPLE SUMMARY: Diagnosing breast cancer masses and calcification clusters is crucial in mammography, which reduces disease consequences and initiates treatment at an early stage. A misinterpretation of mammography may lead to an unneeded biopsy of the false-positive results, decreasing the patient’...

Descripción completa

Detalles Bibliográficos
Autores principales: Mahmood, Tariq, Li, Jianqiang, Pei, Yan, Akhtar, Faheem
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8468800/
https://www.ncbi.nlm.nih.gov/pubmed/34571736
http://dx.doi.org/10.3390/biology10090859

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8468800/
https://www.ncbi.nlm.nih.gov/pubmed/34571736
http://dx.doi.org/10.3390/biology10090859

Ejemplares similares