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Use of a deep learning algorithm for non-mass enhancement on breast MRI: comparison with radiologists’ interpretations at various levels
PURPOSE: To evaluate the diagnostic performance of deep learning using the Residual Networks 50 (ResNet50) neural network constructed from different segmentations for distinguishing malignant and benign non-mass enhancement (NME) on breast magnetic resonance imaging (MRI) and conduct a comparison wi...
Autores principales: | Goto, Mariko, Sakai, Koji, Toyama, Yasuchiyo, Nakai, Yoshitomo, Yamada, Kei |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Nature Singapore
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10543141/ https://www.ncbi.nlm.nih.gov/pubmed/37071250 http://dx.doi.org/10.1007/s11604-023-01435-w |
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