Application of Deep Convolutional Neural Networks for Discriminating Benign, Borderline, and Malignant Serous Ovarian Tumors From Ultrasound Images

OBJECTIVE: This study aimed to evaluate the performance of the deep convolutional neural network (DCNN) to discriminate between benign, borderline, and malignant serous ovarian tumors (SOTs) on ultrasound(US) images. MATERIAL AND METHODS: This retrospective study included 279 pathology-confirmed SOT...

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Detalles Bibliográficos
Autores principales: Wang, Huiquan, Liu, Chunli, Zhao, Zhe, Zhang, Chao, Wang, Xin, Li, Huiyang, Wu, Haixiao, Liu, Xiaofeng, Li, Chunxiang, Qi, Lisha, Ma, Wenjuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8720926/
https://www.ncbi.nlm.nih.gov/pubmed/34988015
http://dx.doi.org/10.3389/fonc.2021.770683

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8720926/
https://www.ncbi.nlm.nih.gov/pubmed/34988015
http://dx.doi.org/10.3389/fonc.2021.770683

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