Examining the effectiveness of a deep learning-based computer-aided breast cancer detection system for breast ultrasound

PURPOSE: This study aimed to evaluate the clinical usefulness of a deep learning-based computer-aided detection (CADe) system for breast ultrasound. METHODS: The set of 88 training images was expanded to 14,000 positive images and 50,000 negative images. The CADe system was trained to detect lesions...

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Detalles Bibliográficos
Autores principales: Fujioka, Tomoyuki, Kubota, Kazunori, Hsu, Jen Feng, Chang, Ruey Feng, Sawada, Terumasa, Ide, Yoshimi, Taruno, Kanae, Hankyo, Meishi, Kurita, Tomoko, Nakamura, Seigo, Tateishi, Ukihide, Takei, Hiroyuki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Nature Singapore 2023
Materias:
Original Article–Breast & Thyroid
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10556122/
https://www.ncbi.nlm.nih.gov/pubmed/37400724
http://dx.doi.org/10.1007/s10396-023-01332-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10556122/
https://www.ncbi.nlm.nih.gov/pubmed/37400724
http://dx.doi.org/10.1007/s10396-023-01332-9

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