Breast Cancer Diagnosis in Two-View Mammography Using End-to-End Trained EfficientNet-Based Convolutional Network

Some recent studies have described deep convolutional neural networks to diagnose breast cancer in mammograms with similar or even superior performance to that of human experts. One of the best techniques does two transfer learnings: the first uses a model trained on natural images to create a "...

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Veröffentlicht in:	IEEE access 2022, Vol.10, p.77723-77731
Hauptverfasser:	Petrini, Daniel G. P., Shimizu, Carlos, Roela, Rosimeire A., Valente, Gabriel Vansuita, Folgueira, Maria Aparecida Azevedo Koike, Kim, Hae Yong
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence Artificial neural networks Breast cancer Breast cancer diagnosis Classifiers convolutional neural network Convolutional neural networks Datasets deep learning Lesions mammogram Mammography Medical imaging Training Transfer learning
Online-Zugang:	Volltext
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