Applied Machine Learning in Spiral Breast-CT: Can We Train a Deep Convolutional Neural Network for Automatic, Standardized and Observer Independent Classification of Breast Density?

The aim of this study was to investigate the potential of a machine learning algorithm to accurately classify parenchymal density in spiral breast-CT (BCT), using a deep convolutional neural network (dCNN). In this retrospectively designed study, 634 examinations of 317 patients were included. After...

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Detalles Bibliográficos
Autores principales: Landsmann, Anna, Wieler, Jann, Hejduk, Patryk, Ciritsis, Alexander, Borkowski, Karol, Rossi, Cristina, Boss, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8775263/
https://www.ncbi.nlm.nih.gov/pubmed/35054348
http://dx.doi.org/10.3390/diagnostics12010181

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8775263/
https://www.ncbi.nlm.nih.gov/pubmed/35054348
http://dx.doi.org/10.3390/diagnostics12010181

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