A Comparative Study of Multiple Deep Learning Models Based on Multi-Input Resolution for Breast Ultrasound Images

PURPOSE: The purpose of this study was to explore the performance of different parameter combinations of deep learning (DL) models (Xception, DenseNet121, MobileNet, ResNet50 and EfficientNetB0) and input image resolutions (REZs) (224 × 224, 320 × 320 and 488 × 488 pixels) for breast cancer diagnosi...

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Detalles Bibliográficos
Autores principales: Wu, Huaiyu, Ye, Xiuqin, Jiang, Yitao, Tian, Hongtian, Yang, Keen, Cui, Chen, Shi, Siyuan, Liu, Yan, Huang, Sijing, Chen, Jing, Xu, Jinfeng, Dong, Fajin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9302001/
https://www.ncbi.nlm.nih.gov/pubmed/35875151
http://dx.doi.org/10.3389/fonc.2022.869421

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9302001/
https://www.ncbi.nlm.nih.gov/pubmed/35875151
http://dx.doi.org/10.3389/fonc.2022.869421

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